phd thesis samuel coenen.pdf

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U n i v e r s i t y o f A n t w e r p F a c u l t y o f M e d i c i n e D e p a r t m e n t o f G e n e r a l P r a c t i c e

Antibiotics for coughing in general practice exploring, describing and optimising prescribing

Antibiotica voor hoestklachten in de huisartspraktijk exploreren, beschrijven en optimaliseren van het voorschrijven

Dissertation for the degree of doctor in Medical Science at the University of Antwerp - Universitaire Instelling Antwerpen

to be defended by

Samuel COENEN

Paul Van Royen Joke Denekens Antwerp, 2003

Exam commission Supervisors:

Prof. Dr. J. Denekens, University of Antwerp Prof. Dr. P. Van Royen, University of Antwerp Doctoral commission:

Prof. Dr. M. De Broe (chair) , University of Antwerp Prof. Dr. W. De Backer, University of Antwerp Prof. Dr. A. Meheus, University of Antwerp External members: Prof. Dr. G-J. Dinant, University of Maastricht Prof. Dr. P. Little, University of Southampton

Antibiotics for coughing in general practice: exploring, describing and optimising prescribing.

Samuel Coenen

ISBN 90-5728-039-6

Department of General Practice University of Antwerp Universiteitsplein 1 BE 2610 Antwerp Belgium E-mail: [email protected]

Table of contents

Chapter I Introduction 1

Chapter II A qualitative decision analysis Fam Pract 2000;17:380-5 Huisarts Nu 2001;30:390-7

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Chapter III A questionnaire study to quantify and condense the reasons for prescribing BMC Family Practice 2002;3:16 (10p) Huisarts Nu 2003;32:180-9

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Chapter VI GPs’ perception of patients’ requests determines prescription behaviour

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Chapter V A clinical practice guideline Huisarts Nu 2002;31;391-411

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Chapter VI Cluster randomised controlled trial of a tailored professional intervention to optimise prescribing

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Chapter VII Patients’ views on respiratory symptoms and antibiotics 109

Chapter VIII General discussion 121

Summary 133 Samenvatting 145

Curriculum vitae 159

List of Publications 161

Dankwoord 167

1

I

Antibiotics for coughing in general practice:

General introduction

The research activities described in this dissertation were performed in general practice and with general practitioners (GPs). For a good understanding this introduction (Chapter I of this dissertation) will consider some of the particular characteristics and the interrelation of this setting, coughing, and antibiotics.

General practice

GPs can play a key role in the organisation of health care. Dealing with a large variety of reasons for encounter they decide whether the patient needs health care or not, and in the former case whether this can be provided in primary care or not. This so-called ‘filter-function’ , also referred to as ‘gatekeeping’ , therefore can result in a rational use of resources.1 2 On the other hand the means to perform as a GP are limited. After all primary care is characterised by low technology and low cost. Furthermore, for the many problems encountered in primary care the evidence base is limited. As a result it is unavoidable that GPs have to deal with uncertainty in daily practice. Establishing an operational diagnosis for every day complaints often is difficult, as is deciding which patient will benefit from a specific treatment.

Chapter I

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Guidelines form a potentially valuable bridge between evidence-based medicine and clinical practice. Adherence to guidelines can improve quality of care, reduce inappropriate variations in practice and improve cost effectiveness.3 However studies in general practice indicate poor compliance with guidelines or limited effects upon patient outcomes.4 If guidelines are to address variability, we need to understand how and why variation occurs in general practice and to develop reliable ways of identifying unacceptable variations. These topics will be covered in this thesis.

Coughing

Complaints about coughing are a good example of an every day reason for encounter which the GP has to manage as a gatekeeper, ensuring rational use of resources, despite limited means and lacking evidence.

In general practice, medical decisions are prompted most often by complaints about coughing, especially for respiratory tract infections (RTIs). The frequency of coughing as a reason for encounter at the start of a new illness episode was found to be 5.3% by Jan De Maeseneer in 1989 for Belgium,5 and stable at 5.4% by Lambrechts et al. for over a decade in the Netherlands.6 For Belgium recent figures linking patients’ complaints to diagnoses are not available. In the Netherlands however per 1000 patients visiting their GP in the last year 168.9 consult with coughing as (one of) the most prominent complaint(s). Irrespective of their age more than three quarters of the final diagnoses are RTIs.6 Using the International Classification of Primary Care,7 upper RTIs, including laryngitis/tracheitis and sinusitis, represent nearly half of the final diagnoses. Acute bronchitis is the final diagnosis in a quarter of the consultations. Proven influenza and pneumonia each only account for about 2% of the final diagnoses. These final diagnoses are part of the top 10 of most frequent final diagnoses for new illness episodes with coughing as reason for encounter. Asthma can be found in this top 10 too. Notwithstanding the difficulties to distinguish between respiratory infections and not infectious causes of coughing such as for example asthma, the validity of the diagnostic criteria used to classify respiratory infections is questionable. It is hard to distinguish upper from lower RTIs, and history and clinical examination do not allow to differentiate between acute bronchitis and pneumonia.8 Therefore in this thesis all research activities depart from complaints about coughing and


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not from doubtful diagnoses. Furthermore, technical investigations such as blood or sputum analysis, or X-ray examination are not considered suitable and/or feasible in general practice for the differential diagnoses above, nor to discriminate between viral and bacterial infections.9 10 Finally, and this is more important, there is no evidence allowing GPs to identify patients with acute bronchitis or acute cough who might benefit from antibiotics.11 12

Antibiotics

Antibiotic use for coughing in general practice, finally, is a good example of misuse of available resources, resulting in sub-optimal patient care.

The discovery of antibiotics (penicillin) by Alexander Fleming in 1928 triggered enormous progress in the field of medicine. However, as early as 1944 Fleming observed that some bacteria were able to destroy penicillin, and he warned that the misuse of antibiotics could lead to selection of resistant bacteria, making antibiotics loose their effectiveness in the treatment of life-threatening infections. This warning was lost in the first flush of the discovery of increasing numbers of antibiotics and the success of these medicines, especially in the treatment of RTIs.

A decade ago the increase of bacterial resistance to antimicrobial agents was declared a crisis.13 At the same time the Alexander Project was established in Europe and the USA to examine the antimicrobial susceptibility of community-acquired lower RTIs’ bacterial pathogens. Up to now, the causative agent of the most frequent life-threatening bacterial infection, Streptococcus pneumoniae - or pneumococcus for short -, has become even less sensitive to penicillin and other antibiotics world-wide.14 15 According to the most recent data from the Belgian Streptococcus pneumoniae Reference Lab (Jan Verhaegen, Leuven) more than 30% of pneumococci isolated are resistant to erytromycin and tetracycline, whereas more than 5% show full penicillin resistance (Figure 1).

The increase in bacterial resistance is associated with the increased use of antibiotics, both in animals and in humans. In addition, both agricultural use (50%) and human use (50%) of antibiotics is inappropriate.16 In the case of humans, 80% is used in the community, this means outside the hospital, especially in general practice and for RTI. Evidence for the misuse of

Chapter I

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antibiotics can be found in the variation in outpatient antibiotic consumption in Europe (Figure 2).17 Especially the pronounced difference between neighbouring countries such as Belgium and the Netherlands, 26.7 vs. 8.9 Daily Defined Doses (DDD) per 1000 inhabitants per day, is unlikely to be caused by differences in frequency of bacterial infections. Furthermore, although differences in health care system, cultural and social factors, and maybe in physicians’ and patients’ attitudes to antibiotics might explain these international differences, even in the Netherlands – with the lowest antibiotic consumption in Europe – it was estimated that antibiotics for respiratory complaints were most probably indicated for only half of those prescribed one.18 Furthermore, the variation in the use of different kinds of antibiotics between countries most likely is associated with inappropriate prescribing too.

Data from the National Sickness and Invalidity Insurance Institute (NSIII): Health Care Service, in Belgium are very similar compared to the data presented by Cars and colleagues. These data only relate to reimbursed drugs prescribed in ambulant care, that is for patients outside the hospital, and delivered by the pharmacist. In cost and in volume (DDD) over 80% of these drugs are prescribed by GPs. The same goes for antibiotics of which about 20 DDDs per 1000 inhabitants per day are prescribed by certified GPs in Belgium. Since 1997 prescribing of both antibiotics in general and different classes of antibiotics has been rather stable according to the currently available NSIII data (Figure 3). These data also provide more details about combinations of antibiotics compared to the data presented by Cars and colleagues. The most striking finding in this regard is the volume of penicillins, including beta-lactamase inhibitor (Anatomic Therapeutic Chemical Classification (ATC): J01CR), c.q. the combination of amoxicillin and clavulanic acid, prescribed in Belgium: 4.1 DDDs per 1000 inhabitants per day, or over 20% of all antibiotics prescribed by GPs in Belgium. The variation in the use of different kinds of antibiotics most likely is associated with inappropriate prescribing within one country as well. After all the share different kinds of antibiotics have in the total antibiotic prescribing (in DDD) shows a large variation between certified GPs in Belgium (Figure 4). And there is no evidence that this variation can be explained entirely by differences in frequency or aetiology of the encountered infectious diseases, nor by differences in antimicrobial resistance of the causative microbes.


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Figure 1 Penicillin, tetracycline and erythromycin susceptibility of Belgian isolates of Streptococcus pneumonia: percentage of non susceptible isolates in the period 1986-2002.(1)

(1) Data from the Belgian Streptococcus pneumoniae Reference Lab (Jan Verhaegen, Leuven). For 2002

36,2 % of the isolates are resistant to Erythromycin (Macrolide), 30,9 % to Tetracycline, 15,2 % to Penicillin, and – not presented in the figure – 0,5 % to Ofloxacine (Quinolone).

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Chapter I

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Figure 2 The volumes of non-hospital antibiotic sales (Anatomic Therapeutic Chemical (ATC) J01) in 1997 in 15 member states of the European Union, expressed as defined daily doses (DDD) per 1000 inhabitants per day.(1)

(1) Data from Cars O, Mölstad S, Melander S. Variation in antibiotic use in the European Union. Lancet

2001; 357:1851-1853. The WHO ATC-DDD-classification of 1997 is used. (2) Includes amphenicols (J01BA), aminoglycosides (J01GB), sulphonamides (J01E), some combinations

(J01CR) within beta-lactam antibacterials, penicillins (J01C) and the entire J01X (glycopeptides (J01XA), polymyxines (J01XB), steroid antimicrobials (J01XC) and other antimicrobials (J01XX)), but not nitrofuran derivates (J01XE).

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Figure 3 The volumes of dispensed antibiotics (Anatomic Therapeutic Chemical (ATC) J01) in the period 1997-2001 in Belgium, prescribed by certified general practitioners, expressed as defined daily doses (DDD) per 1000 inhabitants per day.(1)

(1) Data from the National Sickness and Invalidity Insurance Institute (NSIII): Health Care Service, in

Belgium. The WHO ATC-DDD classification of January 2003 is used. (2) Includes amphenicols (J01BA), aminoglycosides (J01GB), glycopeptides (J01XA), polymyxines (J01XB),

steroid antimicrobials (J01XC) and other antimicrobials (J01XX), but not nitrofuran derivatives (J01XE)

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Chapter I

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Figure 4 The share four kinds of antibiotics have in the total antibiotic prescribing (in DDD) of all GPs in Belgium:(1) box and whiskers plot.(2)

(1) Data from the Conjoint Sickness Funds Data Agency. The WHO ATC-DDD-classification of 2000 is

used. (2) Bar represents 50th percentile, box 25th and 75th percentile, and whiskers 1st and 99th percentile

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It has been shown that community antibiotic sales mirror patterns of antibiotic resistance in Western Europe.19 Others have observed that changes in antibiotic use may be followed by changes in antibiotic resistance.20 21 Consequently, the best way of preserving the effectiveness of antibiotics is to use them more appropriately, i.e. in cases where patients will actually benefit. The alternative of continuing to develop new antibiotics will only solve the problem of antibiotic resistance if the principles of judicious use of antibiotics are implemented at the same time. The growth in resistance is progressing faster than the development of new antibiotics.

Aims

This dissertation aims to contribute to the development of effective strategies for a more appropriate use of antibiotics. Since coughing is one of the most common complaints in general practice, and most antibiotics are prescribed by GPs and for this condition, the appropriate use of antibiotics to treat coughing is a key area of action in order to tackle the resistance problem. Consequently, by describing, exploring and optimising the prescription of antibiotics for coughing we can safeguard a major development in the field of medicine, i.e. the use of antibiotics in the treatment of life-threatening infections.

In the first part of the dissertation we explore the way GPs manage patients who consult them with complaints about coughing to contribute to the necessary understanding of the complex prescribing decision. In a qualitative study (Chapter II), we explored the diagnostic and therapeutic decisions by Flemish general practitioners regarding adult patients who consult them complaining about a cough as well as the determinants of their decisions by means of focus groups. A questionnaire (Chapter III) was used to quantify and condense the determinants of the antibiotic prescribing decision generated in the focus group study. In order to validate the focus group and questionnaire findings and to obtain a valid estimate of the effect of these determinants on GPs’ prescription of antibiotics we recorded their management of patients consulting with acute cough as one of the most prominent complaints (Chapter IV).

The second part of this dissertation provides recommendations for changing current practices and specifically for optimising the use of antibiotics for acute

Chapter I

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cough in general practice. According to a standardized methodology defined by the Scientific College of Flemish General Practitioners (WVVH) the guideline for good clinical practice: acute cough was developed (Chapter V). In a prospective, cluster-randomised, controlled, ‘before-and-after’ study we assessed the effect of an educational intervention, implementing a clinical practice guideline by means of academic detailing (Chapter VI).

The third part addresses the perspective of the patient, the end consumer of all medical treatment, in this case antibiotics. For a better understanding of patients' views about frequent respiratory symptoms, cough, earache and sore throat, and antibiotic treatment, we performed a postal questionnaire study with patients in Belgium, in the UK and in the Netherlands. For this dissertation the emphasis will be laid on the results for Belgium (Chapter VII).

Finally, we summarise and discuss the results of this dissertation, and conclude with opportunities for further research (Chapter VIII).

References

1. Dixon J, Holland P, Mays N. Primary care: core values. Developing primary care: gatekeeping, commissioning, and managed care. BMJ 1998;317:125-8.

2. Coenen S, Avonts D, Van Royen P, Denekens J. Chronic obstructive pulmonary disease: don’ t forget the gatekeeper [letter]. Lancet 1998;352:649.

3. Grimshaw J, Russell I. Effect of clinical guidelines on medical practice: a systematic review of rigorous evaluations. Lancet 1993;342:1317-22.

4. Worrall G, Chaulk P, Freake D. The effects of clinical practice guidelines on patient outcomes in primary care: a systematic review. CMAJ 1997;156:1705-12.

5. De Maeseneer J. Huisartsgeneeskunde: een verkenning [General practice: an exploration]. Proefschrift [Dissertation] Rijksuniversiteit Gent, 1989.

6. Okkes I, Oskam S, Lamberts H. Van klacht naar diagnose [From complaint to diagnosis]. Bussum: Coutinho, 1998.


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7. Lamberts H, Wood M. ICPC. International classification of Primary Care. Oxford: Oxford University Press, 1987.

8. Metlay J, Kapoor W, Fine M. Does This Patient Have Community-Acquired Pneumonia? Diagnosing Pneumonia by History and Physical Examination. JAMA 1997;278:1440-5.

9. Jonsson J, Sigurdsson J, Kristinsson K, Gudnadóttir M, Magnusson S. Acute bronchitis in adults. How close do we come to its aetiology in general practice? Scand J Prim Health Care 1997;15:156-60.

10. Johnson P, Macfarlane J, Humphreys H. How is sputum microbiology used in general practice? Resp Med 1996;90:87-8.

11. Fahey T, Stocks N, Thomas T. Quantitative systematic review of randomised controlled trials comparing antibiotic with placebo for acute cough in adults. BMJ 1998;316:906-10.

12. Smucny J, Becker L, Glazier R, McIsaac W. Are Antibiotics Effective Treatment for Acute Bronchitis? A Meta-Analysis. J Fam Pract 1998;47:453-60.

13. Neu H. Crisis of antibiotic resistance. Science 1992;257:1064-73.

14. Felmingham D, Feldman C, Hryniewicz W, Klugman K, Kohno S, Low D, et al. Surveillance of resistance in bacteria causing community-acquired respiratory tract infections. Clin Microbiol Inf 2002;8:12-42.

15. Schito GC, Debbia EA, Marchese A. The evolving threat of antibiotic resistance in Europe: new data from the Alexander Project. J Antimicrob Chemother 2000;46:3-9.

16. Wise R, Hart T, Cars O, Streulens M, Helmuth R, Huovinen P, Sprenger M. Antimicrobial resistance. Is a major threat to public health [editorial]. BMJ 1998;317:609-10.

17. Cars O, Mölstad S, Melander S. Variation in antibiotic use in the European Union. Lancet 2001;357:1851-3.

Chapter I

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18. De Melker R. Efficacy of antibiotics in frequently occurring airway infections in Family Practice. Ned Tijdschr Geneeskd 1998;142:452-6.

19. Bronzwaer S, Cars O, Buchholz U, Molstad S, Goettsch W, Veldhuijzen I, et al. A European study on the relationship between antimicrobial use and antimicrobial resistance. Emerg Infect Dis 2002;8:278-8.

20. Seppala H, Klaukka T, Vuopio-Varkila J, Muotiala A, Helenius H, Lager K, et al. The Effect of Changes in the Consumption of Macrolide Antibiotics on Erythromycin Resistance in Group A Streptococci in Finland. NEJM 1997;337:441-6.

21. Molstad S, Cars O. Major change in the use of antibiotics following a national programme: Swedish Strategic Programme for the Rational Use of Antimicrobial Agents and Surveillance of Resistance (STRAMA). Scand J Infect Dis 1999;31:191-5.

Published in Fam Pract 2000;17:380-5. 13

II


A qualitative decision analysis

Introduction

Medical decision analysis regarding respiratory tract infections (RTIs) mainly focuses on the differential diagnosis between viral and bacterial RTIs, between upper and lower RTIs and between different clinical syndromes such as bronchitis and pneumonia.1 2 And establishing the appropriate treatment is directly linked to the diagnosis of RTIs.3 But researchers such as Melbye et al. have recognised that there is no single yardstick for these diagnoses.4 Thus, it may be questioned whether general practitioners (GPs) can work this way in actual practice.

More than 80% of the excessive use of antibiotics in RTIs is caused by GPs’ prescription behaviour.5 This does not only result in a medicalising effect, but also has enormous financial implications and contributes significantly to an increase in bacterial resistance.6

In general practice complaints about coughing very often constitute the starting point of medical decision-making regarding RTIs. Therefore, this study examines the diagnostic decisions of GPs based on complaints about coughing by adult patients. The determinants of these decisions were derived from an exploratory, descriptive focus group investigation.

Chapter II

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Methods

In order to generate a discussion of the topic among GPs on the basis of their own experience, a focus group investigation was set up.7 This research method generates the rich details of complex experiences and the reasoning behind actions, beliefs, perceptions and attitudes of people.

By means of snowball sampling8 139 GPs from the Antwerp area in Belgium were recruited. They were contacted by telephone in order to find out whether they would be willing to participate. Eventually, a purposeful sample of sixty GPs were invited to the university campus in order to collect the determinants from a broad spectrum of GPs, in terms of sex, general practice experience as well as university of graduation, instead of just from a representative sample.

The number of focus groups was determined by content saturation, i.e. the moment at which answers to the questions provided did not contain any new elements. For the purpose of flexibility, six focus groups were put forth, but in the end four groups proved sufficient. For each focus group, a maximum of twelve GPs received a written invitation in order to ensure the participation of four to eight GPs.

In order not to hinder the free exchange of views, the composition of the groups was homogeneous in terms of sex as well as general practice experience (Table 1). Each group also had a moderator (IH) and an observer (SC). Each semi-structured discussion was guided by the moderator, lasted 90 minutes and centred on the following questions:

1.You are consulted by one of your adult patients who complains about coughing. Which diagnoses come to mind?

2. How do you differentiate between the various possibilities in your patient?

3. You suspect an infection of the respiratory tract. Do you differentiate in any way? Which distinctions do you make?



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Non-verbal information regarding the discussion was logged by the observer on a specially designed scoring sheet9 10 and afterwards conferred with the moderator. She, a psychologist, was familiar with the principles of general practice medical decision-making.11

The recordings were transcribed and subsequently analysed by two researchers, i.e. SC and EV, independently and in accordance with the principles of “qualitative content analysis”.12 All codes with their labels and definitions and the transcriptions were imported into QSR NUD*IST software for computerised analysis.13

Interpretation of the coded texts enabled a classification of the codes and the establishment of relationships between the various codes or categories. This resulted in hypotheses on GPs’ decision-making regarding complaints about coughing.

Results

In March 1998 four focus groups met in which 24 of the 48 invited GPs participated. The only excuse given for not participating was lack of time. The participants did not differ from those who declined in terms of age, sex and university of graduation (Table 1).

The interpretation of the coded texts enabled a classification of the codes. The categories to which the most relevant codes for determinants were assigned, are: epidemiology, prior knowledge, history, clinical examination, doctor- and patient-related factors.

The process of generating hypotheses based on the relationship between these categories and the GPs’ decisions is illustrated by representative answers to the four key questions (Table 2).

Chapter II

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Possible diagnoses for adult patients with complaints about coughing

Independent of prior knowledge of the patient the first answer and diagnoses that comes to mind was RTI in all focus groups (Table 2: text 1). Other possible hypotheses which emerged in all focus groups were obstructive lung diseases (COPD and asthma), allergy, (gastro-oesophageal) reflux, cardiac decompensation, pulmonary oedema, smoking and other irritations, side effects of ACE-I and tumours. Other hypotheses mentioned in three of the focus groups were psychogenic cough, pulmonary embolism and foreign body. These diagnoses were made based on prior knowledge of the patient (Table 2:2).

Decision-making in complaints about coughing

In cases where these GPs had reason to suspect hypotheses other than infectious coughing, they had been able to check these hypotheses, but the questions asked were far from routine questions. The GPs believed that infectious coughing had the highest probability (Table 2:1) and, as a result, they ask routine questions to confirm this hypothesis (Table 2:3). GPs stated that they were better able to confirm certain hypotheses than to rule them out explicitly (Table 2:4).

Possible diagnoses and decision-making regarding complaints about coughing and suspected RTI

In all focus groups, GPs made a distinction between upper and lower RTIs, viral and bacterial RTIs, chronic and acute RTIs, and between different clinical syndromes (e.g. bronchitis and pneumonia).

In the analysis of the different texts coded as determinants, a distinction was made between those determining the probability of a particular condition, e.g. clinical signs and symptoms and those only influencing the action thresholds, i.e. Pauker’ s ‘Testing’ and ‘Test-treatment’ thresholds.14 Determining the probability. GPs tried to make a distinction between the different types of RTIs on the basis of medical history and clinical examination, e.g. sputum colour (Table 2:5). Furthermore it was argued that this can only lead to a suspected distinction between viral and bacterial RTIs, while it is difficult to distinguish between bronchitis and pneumonia (Table 2:6). The value or feasibility of technical investigations such as blood analysis, sputum examination (Table 2:5) or medical imaging was questioned.


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Table 1 Composition of focus groups according to number, age, sex, university of graduation and the number of single- and duo practices of participants, compared to the dropouts for age, sex, university of graduation.

(1) University of Antwerp (2) 3 General practitioners working in a group practice participated. (3) 5 General Practitioners in Professional Training participated (GPPT): a duo-practice then means a solo-practice with a GPPT.

Invited GPs

Participants Drop- outs

Groups Total Total Total

1 2 3 4

Number 48 7 6 4 7 24 24

Mean age

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45

(39-63)

29

(26-32)

28

(26-29)

40

(37-44)

35

(26-63)

35

(26-50)

Man/Woman 24/24 7/0 0/6 4/0 0/7 11/13 13/11

UA(1)/other 29/19 3/4 4/2 1/3 6/1 14/10 15/9

Solo-practices 3/7(2) 1/6(2) 0/4 4/7 8/24(2)

Duo-practices 3/7(2) 3/6(2,3) 4/4(3) 3/7 13/24(2,3)

Chapter II

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Table 2 Representative extracts. 1. A: …The first thing that comes to mind is a common, simple, ordinary infection of the upper or lower respiratory tract.

2. MO: Is that all you think of when someone complains about coughing ? Is there anything else ?

K: No, I don’t think all these things come to mind; it rather depends on the person that comes in.

3. P. Consider whether there is an atopical constitution, in the family or whether they have a history of hay fever, asthma, or eczema. [Several participants agree]

MO: Do you always ask these questions or... ?

P: No, it is directed you know, if your intuition…, if you have a feeling, then you will ask questions about it, definitely not routine questions.

MO: Which are the routine questions you ask a patient with complaints about coughing - an adult patient ?

P: How long have you had this cough ? Do you cough up something, is it a dry cough, is it a cough that is productive ? Are there any other symptoms, such as a fever?

4. MO: How do know that it is not, that it is not asthma.

R: That it is not ? [Laughter]

MO: Yes, I always say …

R: If, for example, the complaint is infectious, yes, then it can still be asthma but that is not your first diagnosis, you know. Yes, on the whole I can tell when it is asthma.

5. W: If you read about it, or hear about is, you can’t tell in advance that green is bacterial and white is viral, although you get the impression in general practice that it is possible to say this.

…

P: This is a rough division you make, because as a general practitioner you don’t have the possibility to say “could you spit in this pot please” and I don’t immediately have a culture, so you have to use the means which you have at your disposal and otherwise, yes. You are somewhat limited.

…

G: But if there are coloured sputa, you’re going to take it seriously ?

P: That is for instance a stronger argument than fever of course, for me at least [agreement].

6. MO: But can you tell the difference between bacterial or whether it is a virus ? [Several participants shake their heads]

MO: This is not possible ?

K: Only suspect, you know.

MO: Is there always a clear difference between bronchitis and pneumonia ? [Several participants: no.]


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A: No, this involves a bit of guesswork.

7. S: Often also things patients say, “Oh, with me it sinks very quickly [K agrees: yes].

S: Or “ I always take antibiotics” or “My other general practitioner prescribed antibiotics and it works well”. Then you already know, well, if I don’t prescribe antibiotics, then he will call back within two days.

N: Or never again.

8. E: Nowadays, there are also adults who ask “give me an antibiotic because I have to work.”

K: You are not going to prescribe antibiotics, are you ?

9. E: And probably also a bit [depending] on your experience in the period before. For instance, I once missed a pneumonia. Then you realise, you are not going to wait for those three weeks anymore, but more rapidly [agreement] and then it eases off again.

10. P: … Usually you have to say, I ‘m going to start something [antibiotics] here or I’m not going to start anything. You can’t say, I’m going to wait until something is cultured, because this will take three days. So, you have to rely on something in order to possibly start something. Well, this is not only the colour of the sputa, but a number of elements taken together which will push you across a certain threshold whether or not to prescribe antibiotics.

11. G: And tracheitis, then the pain is situated low in the neck, right here, above the windpipe.

MO: Yes.

P: These are welcome diagnoses?

G: If they tell you this, you are really satisfied.

P: Yes. In such a complaint you are certain that you don’t have to prescribe antibiotics and it will be all right.

12. P: You don’t know this in bronchitis, you know. And you will conclude more easily that you have to prescribe something here. This is what I meant earlier when I said that antibiotics are frequently prescribed when not really necessary.

13. W: If it is bacterial, you have to prescribe antibiotics, if it is viral it doesn’t really matter whether you prescribe them or not.

K: Eventually, you give … too much.

14. M: Yes, they blame you, yes. You are blamed for not prescribing antibiotics when necessary. I heard a colleague of mine saying: ”I regret a couple of things, that is that I did not prescribe antibiotics, it was at a lecture … Someone from the emergency unit said that we prescribed far too many antibiotics. Yet, try not prescribing antibiotics and then having to find out afterwards that there was something.

15. K: We try to differentiate. We are already satisfied if we can establish the difference between bacterial and viral. Several participants agree.

M: We explain why we don’t prescribe antibiotics.

K agrees: Explain why we don’t. But to differentiate between all these different viruses, personally, I can’t do that.

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Determining the action thresholds. Also other determinants play a role, such as patients’ expectations, time pressure during consultation or fear of loosing patients (Table 2:7). A distinction can be made between patient-related (for instance the patient’ s willingness to take medicines) and GP-related factors (for instance recent experiences) (Table 2:8-9). These factors are determinants of the decision whether or not to prescribe antibiotics (Table 2:7-8). GPs suggested that in the end they make this (therapeutic) decision in complaints about coughing and suspected RTI (Table 2:10).

Eventually the decision-making process is related to GPs’ diagnostic (un)certainty. Pain in the trachea for instance was regarded as a sure diagnosis of tracheïtis and this argument provided certainty as to whether or not to prescribe antibiotics (Table 2:11). In the case of bronchitis, however, GPs were less certain of the diagnosis (Table 2:6), which caused uncertainty in prescription behaviour, and in a number of cases antibiotics were unnecessarily prescribed (Table 2:14). Such a decision in favour of antibiotics can be explained by qualitative decision analysis:15 prescribing antibiotics unnecessarily is considered less inappropriate (Table 2:13) – i.e. caused GPs less chagrin – than inappropriately not prescribing antibiotics (Table 2:14).

From the above it may be concluded that the decision to prescribe antibiotics is better explained by both types of determinants than by conventional diagnostic groups of RTIs. Although, GPs explain this prescribing decision to the patient by refering to the diagnosis (Table 2:15).

In light of this interpretation of the texts, hypotheses were generated which constitute the actual results of this kind of investigation (Table 3).

Discussion

Qualitative research in general and focus group research in particular is not often used in medical research, where there is a clear preference for randomised controlled trials. Clinical researchers have a problem with the fact that qualitative methods replace testing hypotheses by generating hypotheses,


21

that measurements are replaced by explanations and generalisations by interpretations.

The creation of an evidence-based medical culture will depend, however, on contributions from both quantitative and qualitative traditions. Qualitative methods allow the examination of areas inaccessible to quantitative methods. They are more suited to understand complex topics than to show their relevance. As a result, these methods are very useful to investigate medical decision-making by exploring the explained as well as the implicit routines and rules adhered to by GPs.16 Focus group research yields data more quickly than participant observation. The interaction during discussions affords a better insight into the development of knowledge and ideas than in-depth interviews.

The weakness of qualitative research concerns bias and generalisation. Compared to quantitative research, the methods are more valid but less reliable.17 In order to ensure the trustworthiness of the results, the data were analysed by two researchers, who worked blind and independently of each other. This made it possible to reach a consensus about the code book and the assignment of codes to the texts. Furthermore, the hypotheses are supported by the data. Presenting the results orally to Flemish and European GPs and researchers, their feedback confirmed our interpretation of the texts.18 19 For this written report, only the most representative texts have been translated.

In March 1998 there was an increase in the number of consultations for acute RTIs.20 For some GPs the increased workload associated with this epidemic was probably the reason for not participating. As far as the participants were concerned, however, this epidemic created suitable conditions for this survey, and yielded valid information on the complex decision-making processes by participating GPs.

Our sampling method, composition of groups and working towards saturation, provided a broad range of data.7 Non-verbal information showed all group members were actively involved and clearly stated their opinions and disagreements. The latter concerned the importance of determinants for the prescribing decision. After content analysis, however, the evidence for two distinct categories of determinants emerged from all focus groups.

The survey was both exploratory and descriptive. Although the results do not represent the norm, it is possible on the basis of data in the literature to design an evidence-based decision-making model, which closely relates to the GPs’

Chapter II

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way of thinking. As a result of the selection bias and the non-statistical nature of the sample, the results cannot be generalised. Hence, the results have to be quantified formally.

In order to test the validity of the hypotheses, they were compared against results of other research methods, a process commonly referred to as triangulation. It is clear that GPs only explicitly work on diagnoses, which seem plausible, while collecting fewer arguments for less evident diagnoses. (Table 3: hypotheses 1-2). It seems as if they can only confirm diagnoses. Gatekeepers though, are mainly expected to be good at excluding diagnoses. Indeed, GP assessment is a relatively powerful excluder in patients suffering from RTIs.1 This apparent contradiction may be explained by the fact that the determinants to rule out hypotheses – such as a GP’ s judgement – could not be made sufficiently explicit by means of the method used. (Table 2:5)

According to the participants, the differentiation between RTIs was based on a low degree of certainty (Table 3:3). In coughing and suspected RTI, GPs can only provide weak arguments for the diagnosis of RTI – e.g. pneumonia – on the basis of medical history and clinical examination.1 GPs question the value and/or feasibility of technical investigations such as blood or sputum analysis, or X-ray examination.2 According to Kassirer, the fact of aiming for diagnostic certainty results in excessive testing, whereas certainty is not a precondition for good therapeutic decisions. Dealing with diagnostic uncertainty is related to the therapies available.21 If GPs consider antibiotics highly effective and almost risk free (Table 2:15), it is logical that they will decide to use them in treatments even if there is a certain degree of uncertainty. In the prescription of antibiotics, also other factors such as patients’ expectations play a role (Table 3:4). If there is diagnostic uncertainty, this is almost unavoidable.22 In addition, Butler’ s research has shown that irrational prescription behaviour regarding sore throats can be explained by the desire to avoid straining the doctor-patient relationship.23 The organisation of healthcare in Belgium, where there is no official relationship between doctors and patients and where doctors are paid fee for service, may also account for the excessive use of antibiotics.24 All these factors fall within Feinstein’ s “Chagrin factor”.15 GPs considered it less appropriate not to have prescribed antibiotics when this proved to be necessary (Table 2:18), than having prescribed antibiotics when not necessary (Table 2:17). The latter caused less “chagrin” to the GPs. Then, “when necessary” does not only mean “necessary” to cure patients, but also


23

Table 3 Hypotheses on GPs’ decision-making regarding complaints about coughing and on the determinants underlying their decisions.

1. The first diagnosis that comes to a GP’s mind is respiratory tract infection (RTI). This diagnosis is reached independent of the patient. Other hypotheses emerge only if they are considered plausible as a result of prior knowledge of the patient.

2. GPs ask routine questions to confirm only the most likely diagnoses. Explicitly ruling out other diagnoses is less often used in decision-making.

3. In suspected RTI, GPs want to make a distinction between clinical syndromes such as bronchitis and pneumonia, viral and bacterial RTI and upper and lower RTI. This cannot be achieved with certainty on the basis of medical history and clinical examination. Dealing with diagnostic uncertainty, GPs’ decisions are directed at whether or not to prescribe antibiotics.

4. For this (therapeutic) decision, also doctor- and patient-related factors play a role. These factors give rise to a shift in the action thresholds in favour of antibiotics, a phenomenon explained by the “Chagrin factor”. The decision to prescribe antibiotics is better explained by both types of determinants than by the conventional diagnostic groups of RTIs.

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“necessary” to function as adequately as possible as a GP without losing patients as a result of unfulfilled expectations or undetected serious diseases.

Finally our results are in line with Howie’ s hypothesis: although GPs’ therapeutic decisions are normally described using a diagnostic label, in reality it is often better to view them in terms of symptoms and signs and influenced by factors (Table 3:4).25 A diagnosis is then formulated as a justification for a therapeutic decision (Table 2:17).

In patients with complaints about coughing GPs need manageable arguments to select patients who may or may not benefit from antibiotics. These data have to be collected in further research and lead to answers to the following questions derived from the hypotheses:

1. Does ruling out less likely diagnoses add something to merely trying to diagnose a (certain) RTI?

2. Do GPs prescribe antibiotics to a lesser degree and more adequately when they have stronger clinical evidence to support their decisions?

3. Are diagnostic syndromes on the basis of this strong clinical evidence more manageable in general practice than classical syndromes?

So far, such clinical evidence is unknown both for patients with coughs and for bronchitis. Meta-analyses also show that in most cases antibiotics do not offer any benefits, which outweigh the possible side effects.3 26 As a result, research into a more effective use of antibiotics has to pay special attention to the doctor- and patient-related factors in the relationship and communication between GPs and patients.

The authors are developing an educational intervention that builds on these findings, aiming to reduce antibiotic use and cost, while preserving patient outcomes.


25

References


2. Jonsson J, Sigurdsson J, Kristinsson K, Gudnadóttir M, Magnusson S. Acute bronchitis in adults. How close do we come to its aetiology in general practice? Scand J Prim Health Care 1997;15:156-60.

3. Becker L, Glazier R, McIsaac W, Smucny J. Antibiotics for Acute Bronchitis (Cochrane Review). In: The Cochrane Library, Issue 4, 1999. Oxford: Update Software.

4. Melbye H, Straume B, Aasebo U, Dale K. Diagnosis of pneumonia in adults in general practice. Relative importance of typical symptoms and abnormal chest signs evaluated against a radiographic reference standard. Scand J Prim Health Care 1992;10:226-33.


6. Butler C, Rollnick S, Kinnersley P, Jones A, Stott N. Reducing antibiotics for respiratory tract symptoms in primary care: consolidating 'why' and considering 'how'. Br J Gen Pract 1998;48:1865-70.

7. Morgan D, Krueger R. The Focus group Kit, Volumes 1-6. London: Sage Publications, 1998.

8. Marshall M. Sampling for qualitative research. Fam Pract 1996;13:522-5.

9. Douglas T. Groepswerk in de praktijk [Groupwork in practice]. 's Gravenhage: VUGA, 1979.

10. Alblas G. Groepsprocessen: het functioneren in taakgerichte groepen [Groupprocesses: functioning in task-oriented groups]: Van Loghum-Slaterus, 1983.

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11. Van den Ende J, Derese A, Debaene L, de Béthune X, Lemiengre M, Van Puymbroek H, et al. Medische besliskunde: een nieuw accent in de Vlaamse huisartsgeneeskunde [Medical decision analysis: a new accent in Flemish general practice]. Huisarts Nu 1996;9:281-344.

12. Morgan D. Qualitative content analysis: a guide to paths not taken. Qual Health Res 1993;3:112-1.

13. Q.R.S.NUD.IST 4 user guide. London: Sage Publications Software, 1997.

14. Pauker S, Kassirer J. The threshold approach to clinical decision making. NEJM 1980;302:1109-17.

15. Feinstein A. The 'Chagrin Factor' and Qualitative Decision Analysis. Arch Intern Med 1985;145:1257-9.

16. Britten N, Jones R, Murphy E, Stacy R. Qualitative research methods in general practice and primary care. Fam Pract 1995;12:104-14.

17. Britten N, Fisher B. Qualitative research and general practice [editorial]. Br J Gen Pract 1993;43:270-1.

18. Coenen S, Van Royen P, Vermeire E, Hermann I, Denekens J. Met welke argumenten voert de huisarts zijn diagnostisch beleid bij de contactreden 'hoesten' [General practitioners’ arguments to make diagnostical decisions when coughing is the reason for encounter]. VHI Referatendag [Lecture-day of the Flemish General Practitioners’ Institute]; 1999; Gent.

19. Coenen S, Van Royen P, Vermeire E, Hermann I, Denekens J. What determines medical decision-making in patients with coughing as the reason for encounter? Focus group research with general practitioners. First European Networks Open Conference WONCA '99; 1999; Palma de Mallorca.

20. Ducoffre G. Surveillance van Infectieuze Aandoeningen door een Netwerk van Laboratoria voor Microbiologie 1997 + Epidemiologische Trends 1983-1996 [Surveillance of Infectious Disease by a Network of Laboratories for Microbiology 1997 + Epidemiological Trends 1983-1996]. Brussel: Ministerie van Sociale Zaken, Volksgezondheid en Leefmilieu, Wetenschappelijk Instituut Volksgezondheid-Louis Pasteur [Ministry of Social Affairs, Public


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Health and Environment, Scientific Institute of Public Health-Louis Pasteur], 1998.

21. Kassirer J. Our stubborn quest for diagnostic certainty. A cause of excessive testing. NEJM 1989;320:1489-91.

22. Fahey T. Antibiotics for respiratory tract symptoms in general practice [editorial]. Br J Gen Pract 1998;48:1815-6.

23. Butler CC, Rollnick S, Pill R, Maggs-Rapport F, Stott N. Understanding the culture of prescribing: qualitative study of general practitioners' and patients' perceptions of antibiotics for sore throats. BMJ 1998;317:637-42.

24. Grol R, De Maeseneer J, Whitfield M, Mokkink H. Disease-Centred Versus Patient-Centred Attitutes: Comparison of General Practitioners in Belgium, Britain and The Netherlands. Fam Pract 1990;7:100-3.

25. Howie J. Diagnosis, the Achilles heel? J R Coll Gen Pract 1972;22:310-5.


Published in BMC Fam Pract 2002;3:16 (10p). 29

III


A questionnaire study to quantify and condense the reasons for prescribing

Introduction

Antibiotics are being overprescribed in ambulant care,1 especially for respiratory tract infections (RTIs).2 For this prescribing decision different types of determinants are already highlighted. 3-6 However, gaining insight into the actual reasons for context specific prescribing remains important to design effective strategies to optimise antibiotic prescribing.7

In general practice, medical decisions (concerning RTIs) are prompted most often by complaints about coughing: 169 times per 1000 patients per year for a new illness episode.8 Since there is no evidence base for the prescription of antibiotics for coughing in case of suspected RTI,9 and since antibiotic prescribing results in financial costs to the patient and society, adverse effects and development of bacterial resistance,10 we explored the diagnostic and therapeutic decisions of Flemish general practitioners (GPs) regarding adult patients who consult them with complaints about coughing by means of focus groups.11 We found medical as well as non-medical reasons for antibiotic prescriptions in case of suspected RTI.12 Our hypotheses on Flemish GPs' decisions were in line with previous research. The differentiation between

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RTIs, e.g. acute bronchitis and pneumonia, could not be achieved with certainty on the basis of medical history and clinical examination:13 i.e. medical reasons. Dealing with this diagnostic uncertainty, GPs' decisions were directed at whether or not to prescribe antibiotics.14 Determinants playing an important role in this decision are physician related, e.g. having missed pneumonia once, or patient related, e.g. patient expectations:15 i.e. non-medical reasons.

Since it is time for action,16 besides a better understanding of the actual determinants for context specific prescribing of antibiotics, we also have to make them operational for the design of an intervention. Therefore, we aimed to quantify and to condense the determinants generated in the focus group study. By means of this postal questionnaire study in Flemish general practice, we assessed to what extent Flemish GPs consider those determinants in decision making in case of suspected RTI in a coughing patient and how strongly the determinants support or counter antibiotic treatment.

Methods

Design

We performed an explanatory study comparing GPs' responses from a self-administered questionnaire based upon focus group findings.12

Setting and sample

We approached Flemish GPs who were willing to participate in previous studies of our research unit.12 17 The questionnaire was sent to this selected group by mail early September 1999. A reminder was sent to all non-responders two weeks later. Responses were accepted until the end of September 1999. The survey was pilot tested.

Of the 316 GPs originally selected to be in the sample, 7 were no longer practising, 5 returned surveys with more than 20% of items unanswered, 116 failed to respond before the end of September 1999, leaving 188 GPs who completed the survey. The overall response rate was 59.5%.


31

Instrument

To assess the importance of determinants for the antibiotic prescribing decision the GPs were sent one questionnaire in two parts, one (Q1) assessing to what extent they consider these determinants in decision making in case of suspected RTI in a coughing patient, and another (Q2) assessing how strongly these determinants support or counter antibiotic treatment. The response set for each item was a 5-point verbal rating scale (VRS). For Q1 the VRS ranged from 1 (never), 2 (seldom), over 3 (sometimes), to 4 (often) and 5 (always), for Q2 from 2 (strongly in favour), 1 (in favour), over 0 (neutral), to -1 (against) and -2 (strongly against). 'See addendum for the original questionnaire(in Dutch) used in this study'

Focus groups, exploring the determinants of GPs' diagnostic and therapeutic decisions in adult patients with complaints about coughing, provided the items proposed in the questionnaire.12 The main categories at which we ordered the determinants were: epidemiology, e.g. an influenza epidemic, prior knowledge of the patient, e.g. he/she is smoking, symptoms, e.g. a sputum producing cough, clinical signs, e.g. a normal lung auscultation, patient related non-medical determinants, e.g. patient's demand for antibiotics, physician related non-medical determinants, e.g. having missed pneumonia once. There were also: first impression, e.g. patient looks very ill, laboratory results, e.g. normal erythrocyte sedimentation rate, and natural course, e.g. the illness is worsening.

For the questionnaire (Q1 and Q2) items were chosen from all the above categories to include a meaningful selection of all the issues mentioned in the focus group study. Concerning their content the items were to be manageable in daily practice and to determine the decision whether or not to prescribe antibiotics. Therefore no issues about laboratory results were included: blood or sputum analysis, or X-ray examination are seldom performed in – Flemish [Coenen, unpublished] – general practice in case of suspected RTI.8 Determinants only used to confirm other possible diagnoses with coughing as principal complaint, e.g. risk factors for pulmonary oedema, were also excluded. The items were to allow clear and brief formulation as well. Five physicians staffing our Centre, including two authors of the report (PVR and SC) selected the issues in the decision to prescribe in consensus and rephrased them into questionnaire items faithful to the original formulation.

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Analysis

All statistical analyses were performed using Statistica 5.1 (StatSoft, Inc., Tulsa, OK, USA). To make the selected issues operational for an intervention trial, exploratory factor analyses on the questionnaire's items in Q1 and Q2 were performed, using the principal axis method and varimax normalised rotation. The relative importance of the operational factors yielded was assessed using Wilcoxon Matched Pairs test. For comparison of ordinal variables between two groups, the Mann-Whitney test was used.

Results

The mean age (SD) of the GPs was 42.8 years (7.7), 65.9% were men. 46.9 % of the GPs worked single-handed. GPs were predominantly rewarded by fee for service; 24.9% had more than 120 patient encounters per week.

Considering the determinants in decision making

Assessing to what extent GPs consider the determinants for antibiotic prescribing in decision making (Q1), on average GPs considered all 42 items. Factor analysis suggests groups of variables whose values are similar, in this case GPs' responses to Q1 items. Factor analysis of all items from Q1 yielded three factors, i.e. groups of items which GPs considered similarly, explaining 33 % of the variance (Figure 1). Factor 1 included all the items relating to the lung auscultation. Factor 2 included only items relating to non-medical reasons, either patient or physician related. Factor 3 included items determining whether or not there is something unusual happening. Each factor grouping had good internal consistency, with Cronbach � equal to .90 for factor 1, .86 for factor 2 and .87 for factor 3.


33

(1) Part 1 of the questionnaire (Q1) is assessing to what extent the questionnaire items are considered in decision making in case of suspected RTI in a coughing patient. Only items with factor loading > .40 to the yielded factor are presented.

(2) Factor loadings to the yielded factors are presented. Factor 1 (F1) includes all the items relating to the lung auscultation. Factor 2 (F2) includes only items relating to non-medical reasons, either patient or physician related. Factor 3 (F3) includes items determining whether or not there is something unusual happening.

(3) The small box represents the median, the larger box the interquartile range, the wiskers the scoring range.

Figure 1 Items from part 1 of the questionnaire (Q1)(1): distribution of scores and factor loadings per yielded factor.

Factor loadings(2) Distribution of scores(3) Items from Q1(1)

F1 F2 F3 1 2 3 4 5

Crepitations at lung auscultation 0,84 -0,06 0,13

Ronchi at lung auscultation 0,92 0,01 0,17

Wheezing at lung auscultation 0,79 0,09 0,14

Reduced vesicular breathing 0,74 0,01 0,20

Patient asks for medication in general 0,05 0,68 0,32

Patient needs quick recovery for work 0,15 0,70 0,05

Patient asks for antibiotics 0,07 0,81 0,16

Patient expects antibiotics according to you 0,07 0,78 0,07

You will be blamed not having prescribed antibiotics, if it subsequently appears to be necessary 0,05 0,68 0,14

Patient will already reconsult within two days if not better and not prescribed antibiotics 0,14 0,51 0,22

You work under pressure of time -0,02 0,52 0,00

Dyspnoea 0,38 0,10 0,55

Flu-like complaints 0,21 0,01 0,53

Complaint existing less than three days 0,08 0,24 0,49

Deteriorating general condition 0,14 0,08 0,70

Fever getting higher 0,16 0,09 0,66

Complaints improving spontaneously 0,19 0,27 0,61

Respiration rate is to high 0,23 0,12 0,50

Hoarseness 0,28 0,19 0,55

Localised thoracic pain 0,10 0,05 0,61

Mainly lying in bed 0,09 0,11 0,73

Never Sometimes Always Seldom Often

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The median (interquartile range) scores as defined by factor analysis were 5.0 (from 5.0 to 5.0) for factor 1, lung auscultation, 3.0 (form 2.8 to 4.0) for factor 2, non-medical reasons, and 4.0 (from 4.0 to 5.0) for factor 3, unusual or not.

Using Wilcoxon Matched Pairs test to compare the scores of the factors – scores of factor 1 did not approximate a normal distribution – the differences between all three factors are significant at P < 0.001 (Figure 2). Since the differences between the scores approximate a normal distribution, this test is almost as powerful as the t-test.

Figure 2 Factors from part 1 of the questionnaire: comparing scores as defined by factor analysis.

Part 1 of the questionnaire (Q1) is assessing to what extent the questionnaire items are considered in decision making in case of suspected RTI in a coughing patient. Factor 1 includes all the items relating to the lung auscultation. Factor 2 includes only items relating to non-medical reasons, either patient or physician related. Factor 3 includes items determining whether or not there is something unusual happening. Asterisk means that the factor's score significantly differs from the other factors' scores (p < .001).

Max Min 75% 25% Median

Never

1

Seldom

2

Sometimes

3

Often

4

Always

5

Factor 1 *

Factor 2 *

Factor 3 *


35

Of course, GPs also considered items from Q1 not presented in figure 1 (factor loading � .40 to the yielded three factors); always (median = 5) whether the patient has fever, is coughing up sputum and whether the sputum is coloured, whether the patient is looking ill and whether he/she has a medical history of COPD or smoking; often (median = 4) whether the coughing is frequent or started suddenly and whether the patient consults for the first time with this complaint, is saying he/she is feeling ill, is older than 60 years of age, tried self-management first, is known to you or has a red throat, as well as whether there is an RTI epidemic and whether the patient rapidly consults and will reconsult if not better; sometimes (median = 3) whether the patient is compliant, or is recovering slowly even under antibiotic treatment; seldom (median = 2) whether the patient is visited at home or that you make the patient reconsult anyway after 3 to 4 days. For most items the interquartile range was 1.

In favour or against antibiotics

Assessing how strongly the determinants for antibiotic prescribing support or counter antibiotic treatment (Q2), none of the 63 items is strongly in favour or against antibiotic treatment. Factor analysis of all items from Q2 yielded two factors, i.e. groups of items which according to the GPs support antibiotic treatment similarly. The factors included items expressing a need for antibiotic treatment, and no need for antibiotic treatment respectively. This confirmed our construction of Q2.

In favour

Factor analysis of all 37 items that support antibiotic treatment according to their mean and sumscore, yielded two factors, i.e. groups of items which according to the GPs are equally in favour of antibiotic treatment, explaining 24% of the variance (Figure 3). Factor 1 only included items relating to medical reasons, either from the lung auscultation or determining whether or not there is something unusual happening, factor 2 only included items relating to non-medical reasons, either patient or physician related. Each factor grouping had good internal consistency, with Cronbach � equal to .82 for factor 1, .83 for factor 2.

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Figure 3 Items in favour of antibiotic treatment from part 2 of the questionnaire (Q2)(1): distribution of scores and factor loadings per yielded factor.

Factor loadings(2) Distribution of scores(3) Items Q2

in favour of antibiotic treatment(1) F1 F2 -2 -1 0 1 2

Deteriorating general condition 0,55 0,06

Percussion dullness 0,41 0,08

More than three days of fever 0,52 0,15

More than three days in bed with fever 0,60 0,10

Ronchi at lung auscultation 0,57 0,18

Looking ill 0,61 0,17

A child getting higher fever 0,42 0,22

High fever (> 38.5°C) 0,51 0,09

Patient says he/she is feeling ill 0,60 0,25

Wheezing at lung auscultation 0,53 0,14

Swollen cervical lymph nodes 0,41 0,12

Coughing up sputum 0,42 0,19

You are not easy about it 0,23 0,48

Patient needs quick recovery for work 0,24 0,49

You will be blamed not having prescribed antibiotics, if it subsequently appears to be necessary 0,25 0,69

You won’t see the patient again, if not recovering 0,14 0,56

A child’s parent pressure you 0,17 0,72

Patient expects antibiotics according to you 0,14 0,73

Patient asks for antibiotics 0,21 0,71

You work under pressure of time -0,06 0,41

Strongly against

Neutral Strongly in favour

Against In favour

(1) Part 2 of the questionnaire (Q2) is assessing how strong the questionnaire items argue in favour or against antibiotic treatment in case of suspected RTI in a coughing patient. Only items that on average argue in favour of antibiotic treatment, with factor loading > .40 to only one of the yielded factors are presented.

(2) Factor loadings to the yielded factor are presented. Factor 1 (F1) only includes items relating to medical reasons, either from the lung auscultation or determining whether or not there is something unusual happening, factor 2 (F2) only includes items relating to non-medical reasons, either patient or physician related.



37

The median (interquartile range) scores as defined by factor analysis were 1.0 (from 0.5 to 1.0) for factor 1, medical reasons and 0.0 (from 0.0 to 1.0) for factor 2, non-medical reasons. Using Wilcoxon Matched Pairs test the scores of the two factors differed significantly at P < 0.001 (Figure 4).

Figure 4 Factors from part 2 of the questionnaire: comparing scores as defined by factor analysis.

Part 2 of the questionnaire (Q2) is assessing how strong the questionnaire items argue in favour or against antibiotic treatment in case of suspected RTI in a coughing patient. Factors 'in favour' include items which according to their mean and sumscore support antibiotic treatment. Factor 1 only includes items relating to medical reasons, either from the lung auscultation or determining whether or not there is something unusual happening, factor 2 only includes items relating to non-medical reasons, either patient or physician related. Factors 'against' include items which according to their mean and sumscore fail to support antibiotic treatment. Factor 1 only includes items expressing no need for antibiotic treatment, either medical or non-medical. Asterisk means that the factor's score significantly differs from the other factors' scores (p < 0.001)

Max Min 75% 25% Median

Strongly against -

2

Against

- 1

Neutral

0

In favour

1

Strongly in favour

Factor 1 *

Factor 2 *

Factor 1 *

IN FAVOUR

AGAINST

2

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Against

Factor analysis of all 26 items that fail to support antibiotic treatment according to their mean and sumscore, yielded only one factor, i.e. group of items which according to the GPs are equally against antibiotic treatment, explaining 17% of the variance (Figure 5). The factor only included items expressing no need for antibiotic treatment, either medical or non-medical. Factor grouping had good internal consistency, with Cronbach � equal to .80.

The median (interquartile range) score as defined by factor analysis was -1.0 (from -1.0 to -0.5). Using Wilcoxon Matched Pairs test the score of this factors differed significantly at P < 0.001 form the scores of the two factors in favour of antibiotics (Figure 4).

Items from Q2 not presented in figure 3, and figure 5 respectively (factor loading � .40 to the yielded three factors) support or counter antibiotic treatment as well. In favour (median = 1) are crepitations at lung auscultation, medical history of COPD, onset of new complaints in a viral syndrome, consulting for the second time, dyspnoea, tachypnoea, localised thoracic pain, painful teeth or sinuses, coloured sputum, haemoptysis, reduced vesicular breathing, red throat with exudates on the tonsils, the patient being older than 60 years of age and not consulting rapidly. Neutral (median = 0) are smoking, home visit, frequent coughing, no swollen cervical lymph nodes, no localised thoracic pain, medication demand, as well as an RTI epidemic, a dry cough, a red throat without exudates on the tonsils, the patient is known to you, that you make the patient reconsult anyway after 3 to 4 days, that without antibiotic treatment the patient will already reconsult within two days, if not better and bad compliance with antibiotics. Against (median = -1) are consulting rapidly, influenza-like symptoms, no worsening after two days and not wanting antibiotic treatment. For most items the interquartile range was 1.

No relation between the response groups characteristics and the scores as defined by factor analyses of Q1 and Q2 was found to be relevant and significant.


39

Figure 5 Items against antibiotic treatment from part 2 of the questionnaire (Q2)(1): distribution of scores and factor loadings per yielded factor.

Factor loadings(2) Distribution of scores(3) Items from Q2

against antibiotic treatment(1) F1 -2 -1 0 1 2

Hoarseness 0,50

No smoker 0,40

First consult 0,51

Younger than 60 years of age 0,40

You will see the patient again, if not recovering 0,52

No Chronic Obstructive Pulmonary Disease 0,59

White sputum 0,42

Complaint existing less than three days 0,57

You rest easy about it 0,60

Not looking ill 0,56

Normal lung auscultation, no crepitations nor ronchi 0,41

Improving under own (home) medication 0,62

Strongly against

Neutral Strongly in favour

Against In favour (1) Part 2 of the questionnaire is assessing how strong the questionnaire items argue in favour or against antibiotic treatment in case of

suspected RTI in a coughing patient. Only items that on average argue against antibiotic treatment, with factor loading > .40 to the yielded factor are presented.

(2) Factor loadings to the yielded factor are presented. Factor 1 (F1)only includes items expressing no need for antibiotic treatment, either medical or non-medical.


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Discussion

This questionnaire study with adequate response18 enabled us to quantify and condense the focus group determinants and confirmed our focus group finding, that GPs' decisions to prescribe antibiotics are determined by both medical and non-medical reasons.12

Neither the internal validity nor the reliability of the questionnaire was formally assessed, but was assumed acceptable: the questionnaire was developed based upon our focus group study and, notwithstanding other factor loadings, the factor analysis of a sample of all GPs in professional training in June 1999 yielded the same results [Coenen, unpublished]. The results of the factor analysis thus seem independent of selection bias. The quantification results though may be biased due to the recruitment and non-response of GPs. The response group characteristics however approximate that of all Flemish GPs, and for a postal survey of general practitioners a response rate of 59.5% is good according to the literature.18 Self report also might have limited our data by underestimating the importance of the non-medical reasons. Nevertheless our data show that non-medical reasons determine antibiotic prescribing as well.

In their decision making Flemish GPs seem to consider all the determinants included in the questionnaire. Since the complexity of the prescribing decision, we were not surprised the yielded factors explained only little variance. Nevertheless, the GPs almost always consider the operational factor 'lung auscultation', often 'whether or not there is something unusual happening' – both medical reasons – and to a lesser extent 'non-medical reasons', either patient or physician related. According to the GPs non-medical as well as medical reasons are in favour of antibiotic treatment, the non-medical reasons to a lesser extent.

Yet, for patients with acute (productive) cough the benefit from antibiotics is limited: antibiotics do not influence the duration of productive cough, nor that of limitation in work or activities; out of every 10 patients with acute (productive) cough more than 8 will be clinically improved after 7–11 days regardless the use of antibiotics; less than one patient extra will be improved due to antibiotics, but as many patients will experience the side effects of treatment.9 19 And although there is a strong association between focal chest signs and radiographic pneumonia, which suggests presence of focal chest


41

signs may be an important medical reason for antibiotic prescribing, there are no clinical criteria to identify subsets of patients who are most likely to benefit form antibiotic treatment.20 The presence of focal chest signs however is associated with antibiotic prescribing.21

Also non-medical reasons such as patient expectations have been shown to affect prescribing behaviour of GPs for both upper22 and lower5 RTIs. And, it has been suggested that GPs' perception of patient expectations may be the strongest determinant for antibiotic prescribing.23 24 In addition there is little agreement between patient expectations and GPs' perception of these.24 25 And, for as long as it is difficult in the primary care setting to identify patients for whom antibiotics will be beneficial, these non medical reasons will inevitably keep on playing an important role in the decision to prescribe antibiotics.26

Hence good clinical practice guidelines and interventions to optimise antibiotic prescribing for acute cough in Flemish general practice have to take non-medical reasons into account.

In the Flemish guideline for acute cough, for example, we recommend a clinical and stepwise approach to assess the cause of acute cough. First, possibly life-threatening, treatable conditions such as life-threatening pneumonia should be ruled out.27-29 Although this first step may automatically and quickly be undertaken, we like to explicitly stress its importance. Next, we would like awareness of other not immediately life threatening conditions. Asthma, postnasal drip or gastro-oesophageal reflux are not as prevalent as an RTI, but require specific treatment.27 Even though such conditions may not be obvious in a first encounter, it is worthwhile to take them into account. If finally an RTI seems to be the most likely cause, there are no clinical criteria to determine 'which patient will benefit from antibiotics'.13 Nevertheless, this is the question GPs are confronted with.12 Because the benefits from antibiotics are outweighed by their harm – side effects, financial cost and bacterial resistance – we promote reassurance, information and treatment without antibiotics in case of suspicion of an RTI. To support this treatment decision, we recommend to involve the patient and to make the non-medical reasons explicit.

In a cluster randomised controlled trial we evaluate whether an educational intervention based on the Flemish guideline for acute cough optimises antibiotic prescribing for acute cough, i.e. achieves the goals of the Belgian

Chapter III

42

public campaign: "Antibiotics, use them less often, but better," (www.red-antibiotica.org/english/index.html) without affecting the patients' symptom resolution.30 We focus on the non-medical reasons for prescribing, more specifically on the GP's perception of patient expectations. Using the baseline data of this controlled before and after study we will also validate the importance of determining whether there is something unusual happening, the lung auscultation, and non-medical reasons in the prescribing decision of Flemish GPs.

Conclusions

This study assessed the importance for the antibiotic prescribing decision of the determinants of previous focus group research and confirmed it's findings.12 According to the GPs non-medical as well as medical reasons can argue in favour of antibiotic treatment. Good clinical practice guidelines and interventions to optimise antibiotic prescribing have to take non-medical reasons for antibiotic prescribing into account.

References



3. Howie JG. Clinical judgement and antibiotic use in general practice. BMJ 1976;2:1061-4.

4. Kuyvenhoven M, de Melker R, van der Velden K. Prescription of antibiotics and prescribers' characteristics. A study into prescription of antibiotics in upper respiratory tract infections in general practice. Fam Pract 1993;10:366-70.


43

5. Macfarlane J, Holmes W, Macfarlane R, Britten N. Influence of patients' expectations on antibiotic management of acute lower respiratory tract illness in general practice: questionnaire study. BMJ 1997;315:1211-4.

6. Coenen S, Kuyvenhoven M, Butler C, Van Royen P, Verheij T. Variation in European antibiotic use [letter]. Lancet 2001;358:1272.

7. De Sutter AI, De Meyere MJ, De Maeseneer JM, Peersman WP. Antibiotic prescribing in acute infections of the nose or sinuses: a matter of personal habit? Fam Pract 2001;18:209-13.




11. Coenen S, van Royen P, Denekens J. Reducing antibiotics for respiratory tract symptoms in primary care: 'why' only sore throat, 'how' about coughing? [letter]. Br J Gen Pract 1999;49:400-1.

12. Coenen S, Van Royen P, Vermeire E, Hermann I, Denekens J. Antibiotics for coughing in general practice: a qualitative decision analysis. Fam Pract 2000;17:380-5.




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16. Huovinen P, Cars O. Control of antimicrobial resistance: time for action [editorial]. BMJ 1998;317:613-4.

17. Michiels B, Avonts D, Van Royen P, Denekens J, Vander Auwera J-C. Lower incidence of the upper respiratory tract infections among general practitioners as compared to their patients. Eur J Epidemiol 2001;17:1059-61.

18. McAvoy B, Kaner E. General practice postal surveys: a questionnaire too far? BMJ 1996; 313: 732-733. BMJ 1996;313:732-3.

19. Smucny J, Fahey T, Becker L, Glazier R, McIsaac W. Antibiotics for acute bronchitis (Cochrane Review). In: The Cochrane Library, Issue 4, 2002. Oxford: Update Software.

20. Macfarlane J, Holmes W, Gard P, Macfarlane R, Rose D, Weston V, et al. Prospective study of the incidence, aetiology and outcome of adult lower respiratory tract illness in the community. Thorax 2001;56:109-14.

21. Macfarlane J, Lewis SA, Macfarlane R, Holmes W. Contemporary use of antibiotics in 1089 adults presenting with acute lower respiratory tract illness in general practice in the U.K.: implications for developing management guidelines. Respir Med 1997;91:427-34.

22. Little P, Williamson I, Warner G, Gould C, Gantley M, Kinmonth AL. Open randomised trial of prescribing strategies in managing sore throat [see comments]. BMJ 1997;314:722-7.

23. Cockburn J, Pit S. Prescribing behaviour in clinical practice: Patients' expectations and doctors' perceptions of patients' expectations - a questionnaire study. BMJ 1997;315:520-3.

24. Britten N, Ukoumunne O. The influence of patients' hopes of receiving a prescription on doctors' perceptions and the decision to prescribe: a questionnaire survey [see comments]. BMJ 1997;315:1506-10.

25. Dosh S, Hickner J, Mainous AI, Ebell M. Predictors of antibiotic prescribing for nonspecific upper respiratory tract infections, acute bronchitis, and acute sinusitis. J Fam Pract 2000;49:407-14.


45

26. Fahey T. Antibiotics for respiratory tract symptoms in general practice. Br J Gen Pract 1998;48:1815-6.

27. Managing Cough as a Defense Mechanism and as a Symptom. A Consensus Panel Report of the American College of Chest Physicians. CHEST 1998;114(suppl):133S-181S.

28. Huchon G, Woodhead M. Management of adult community-acquired lower respiratory tract infections. Eur Respir Rev 1998;8:391-426.

29. BTS Guidelines for the Management of Community Acquired Pneumonia in Adults. Thorax 2001;56(Suppl 4):1iv-64iv.

30. Coenen S, Van Royen P, Michiels B, Denekens J. Promotion of rational antibiotic use in Flemish general practice: implementation of a guideline for acute cough [abstract]. Prim Care Respir J 2002;11:56.

Chapter III

46

Addendum: The original questionnaire (in Dutch) used in this study.

Een aantal persoonlijke gegevens, die anoniem verwerkt worden.

In te vullen of schrappen wat niet past Postcode praktijkadres: …………………… Geboortedatum: ……/……/19 …… Geslacht: vrouw / man Jaar van promotie als arts: 19 … … Universiteit van promotie als arts: KUL / RUG / UIA / VUB / andere: … … Aantal jaren praktijkervaring als huisarts: … … jaar Gemiddeld aantal patiëntencontacten per week: ………… patiëntencontacten per week Ik krijg hoofdzakelijk een vast loon: Ja / Neen Ik word hoofdzakelijk betaald per prestatie: Ja / Neen / andere: ……………………… Totaal aantal huisartsen in uw praktijk vorig semester: ………… waarvan …………HIBO(s) Huisarts of HIBO: Huisarts / HIBO �� Huisarts: Hoeveel jaren heb je als HIBO gewerkt: 0 / 1 (= huidige 7de jaar arts) / 2 / 3 / …… �� HIBO: Hoeveelste jaar als HIBO: 1e (= huidige 7de jaar arts) / 2e / 3e / ……


47

Beschouw een patiënt met hoestklachten, waarbij je een luchtweginfectie vermoedt. In welke mate ga je volgende punten na?

Voorbeeld: Als je wilt aangeven dat je weinig frequent let op de kleur van de ogen van de patiënt, antwoord je: Nooit Weinig Soms Vaak Altijd Welke kleur de ogen van de patiënt hebben. X In te vullen: Nooit Weinig Soms Vaak Altijd Of het plots begonnen is. Of je de patiënt op huisbezoek ziet. Of er een epidemie van luchtweginfecties is. Of de patiënt ouder is dan 60 jaar. Of de patiënt vlug naar de dokter gaat. Of de patiënt bekend is met COPD. Of de patiënt rookt. Of de patiënt zich hiermee voor het eerst aanbiedt. Of de patiënt er ziek uitziet. Of de patiënt vertelt zich ziek te voelen. Of de patiënt frequent hoest. Of er sputum wordt opgehoest. Of het sputum gekleurd is. Of de klacht minder dan drie dagen bestaat. Of er koorts is. Of de klacht gepaard gaat met heesheid. Of er gelokaliseerde thoraxpijn is. Of de klachten griepaal zijn, d.w.z. spierpijn, algemene malaise… Of de patiënt kortademig is. Of de patiënt een rode keel heeft. Of de patiënt zijn ademhalingsfrequentie te snel is. Of er bij longauscultatie verminderd ademgeruis is. Of er bij longauscultatie wheezing te horen is. Of er bij longauscultatie crepitaties te horen zijn. Of er bij longauscultatie vochtige ronchi te horen zijn. Of de patiënt zijn klachten spontaan gebeterd zijn. Of de patiënt hoofdzakelijk in bed ligt. Of de patiënt zijn algemene toestand achteruitgaat. Of de patiënt meer koorts krijgt. Of de patiënt eerst eigen middeltjes probeerde. Of de patiënt onder antibiotica niet snel geneest. Of de patiënt vraagt naar medicatie in het algemeen. Of de patiënt antibiotica vraagt. Of de patiënt snel beter moet zijn voor zijn werk. Of de patiënt wel terugkomt als het niet betert. Of de patiënt therapietrouw is. Of je de patiënt kent. Of het je kwalijk zal genomen worden, als je geen antibiotica hebt gegeven waar het achteraf nodig bleek.

Dat je de patiënt toch laat terugkomen na 3 à 4 dagen. Of je onder grote tijdsdruk staat. Of de patiënt volgens jou antibiotica verwacht.

Chapter III

48

Beschouw een patiënt met hoestklachten, waarbij je een luchtweginfectie vermoedt. Hoe sterk vóór of tegen pleiten de volgende gegevens om te behandelen

met een antibioticum?

Voorbeeld: Als voor jou het hebben van blauwe ogen , sterk voor het behandelen m et een antibioticum pleit, antwoord je: Sterk voor Voor Neutraal Tegen Sterk tegen … i.v.m . het behandelen m et een antibioticum … Dat de patiënt blauwe ogen heeft. X

In te vullen: Sterk voor Voor Neutraal Tegen Sterk tegen … i.v.m. het behandelen met een antibioticum … Dat je de patiënt op huisbezoek ziet. Dat er een epidemie van luchtweginfecties is. Dat de patiënt jonger is dan 60 jaar. Dat de patiënt ouder is dan 60 jaar. Dat de patiënt vlug naar de dokter gaat. Dat de patiënt niet vlug naar de dokter gaat. Dat de patiënt geen COPD heeft. Dat de patiënt bekend is met COPD. Dat de patiënt niet rookt. Dat de patiënt rookt. Dat de patiënt zich hiermee voor het eerst aanbiedt. Dat de patiënt zich hiermee voor de tweede keer aanbiedt. Dat de patiënt er niet ziek uitziet. Dat de patiënt er ziek uitziet. Dat de patiënt vertelt zich ziek te voelen. Dat de patiënt frequent hoest. Dat de patiënt een droge hoest heeft. Dat de klacht minder dan drie dagen bestaat. Dat er sputum wordt opgehoest. Dat het sputum wit is. Dat het sputum gekleurd is. Dat de klacht gepaard gaat met hemoptoe of bloedfluimen. Dat de klacht gepaard gaat met heesheid. Dat er wel gelokaliseerde thoraxpijn is. Dat er geen gelokaliseerde thoraxpijn is. Dat de klachten griepaal zijn, d .w.z. spierpijn, algemene malaise… Dat er bij het hoesten ook hoge koorts (> 38.5°C) is. Dat er naast het hoesten ook pijn is t.h.v. tanden, sinussen. Dat het hoesten gepaard gaat met meer dan drie dagen koorts. Dat de patiënt geen gezwollen cervicale lymfeklieren heeft. Dat de patiënt gezwollen cervicale lymfeklieren heeft. Dat de patiënt kortademig is. Dat de patiënt een rode keel heeft zonder witte stippen. Dat de patiënt een rode keel heeft met witte stippen. Dat de patiënt zijn ademhalingsfrequentie te snel is.


49

Nogmaals bedankt voor uw inspanning en uw tijd, nodig om deze vragenlijst in te vullen.

Idem, in te vullen: Sterk voor Voor Neutraal Tegen Sterk tegen … i.v.m. het behandelen met een antibioticum … Dat de longauscultatie normaal is, d.w.z. geen ronchi of crepitaties. Dat er bij longauscultatie verminderd ademgeruis is. Dat er bij longauscultatie wheezing te horen is. Dat er bij longauscultatie crepitaties te horen zijn. Dat er bij longauscultatie vochtige ronchi te horen zijn. Dat er bij percussie demping is. Dat het na twee dagen niet verergerd is. Dat een kind meer koorts krijgt. Dat het met eigen (thuis)medicatie al beter ging. Dat de patiënt nieuwe klachten ontwikkelt bij een griepaal syndroom.

Dat de patiënt antibiotica slecht inneemt. Dat de patiënt medicatie in het algemeen vraagt. Dat de patiënt geen antibiotica wil. Dat de patiënt antibiotica vraagt. Dat de ouders van een kind druk uitoefenen. Dat je de patiënt kent. Dat je gerust bent Dat je je niet gerust voelt. Dat als de patiënt niet geneest, je de patiënt wel zal terugzien. Dat als de patiënt niet geneest, je de patiënt niet meer terugziet. Dat je de patiënt toch doet terugkomen na 3 à 4 dagen. Dat de patiënt al drie dagen in bed ligt met koorts. Dat de algemene toestand van de patiënt achteruitgaat. Dat de patiënt snel beter moet zijn voor zijn werk. Dat het je zal kwalijk genomen worden, als je geen antibiotica hebt gegeven, waar het achteraf nodig bleek.

Dat je onder grote tijdsdruk staat. Dat de patiënt volgens jou antibiotica verwacht. Dat zonder antibiotica de patiënt binnen twee dagen al zal terug komen, als er geen beterschap is.

51

IV


GPs’ perception of patients’ requests determines prescription behaviour

Introduction

In general practice, medical decisions are prompted most often by complaints about coughing: 169 times per 1000 patients per year for a new illness episode, especially for acute respiratory tract infections (RTIs).1 Despite the lack of evidence to support the prescription of antibiotics for coughing in case of suspected RTIs,2 3 antibiotics are being overprescribed for this condition, especially in primary care.4 5 This results in an unnecessary financial burden on both the patient and society, as well as adverse effects and development of bacterial resistance.6 Because it is difficult to establish accurate diagnoses of RTIs in general practice, we chose to study this acute problem in primary care based on the most frequent symptom, i.e. coughing.7 When we explored the diagnostic and therapeutic decisions of Flemish general practitioners (GPs) regarding adult coughing patients by means of focus groups,8 we found medical as well as non-medical reasons for antibiotic prescriptions in case of a suspected RTI.9 Our hypotheses on Flemish GPs' decisions were in line with previous research. In the case of suspected RTI, there is a low degree of certainty in the differentiation between RTIs, e.g. between acute bronchitis and pneumonia.10 11 Clinical signs and symptoms, i.e. medical reasons, often leave

Chapter IV

52

GPs with diagnostic uncertainty. In the end, the decision whether or not to prescribe antibiotics is taken.12 Prescription behaviour is also determined by doctor- and patient-related factors, e.g. patient expectations and the GP’ s perception of them.13 These are clearly non-medical reasons.

A questionnaire study assessing the importance of the focus group determinants for the decision to prescribe antibiotics confirmed that non-medical as well as medical reasons may give rise to antibiotic treatment.14 Patients' request for an antibiotic was mentioned in the focus groups and scored high in the questionnaire study as a non-medical reason for antibiotic prescribing.

To validate this focus group and questionnaire study finding and to contribute to the necessary understanding of the complex prescription decision, this study aims to establish a valid estimate of the effect by GPs’ perception of patients’ request for an antibiotic on their prescription of antibiotics, specifically for patients consulting with acute cough as one of the most prominent complaints.

Methods

Design

We performed an explanatory analysis of data collected during a cluster randomized controlled trial (cRCT)15 to obtain a valid estimate of the relationship between the GPs’ perception of the patients’ request for an antibiotic and their prescription of antibiotics.

Setting and sample

We approached 149 Flemish GPs not reluctant to take part in further study on this topic at the time of the postal questionnaire study.14 Eighty-five GPs agreed to participate in the cRCT by returning a completed and signed form to collect their characteristics (Figure 1 and Table 1). These GPs were asked to include 20 consecutive adult acute cough patients (inclusion criteria, see box 1) in the periods February-April 2000 and 2001.


53

Figure 1. Flow of general practitioners (GPs) through the study.

Box 1. Inclusion criteria of adult acute cough patients

18 - 65 years old

No compromised immunity

New or worsening cough

- present for less than 30 days

- as (one of the) most prominent complaint(s)

- as reason for first encounter at the GP’s practice

GPs responding in questionnaire study (n=193)

GPs approached for this study (n=149)

GPs recruited for this study (n=85)

GPs including patients for this study (n=72)

GPs reluctant to take part in further study on this topic (n=44)

GPs not willing to take part in this study (n=64)

GPs not including patients for this study (n=13)

Chapter IV

54

Table 1 Characteristics of participating general practitioners (1).

Variable N = 72

Figures are numbers (percentages) (2)

MEN 53 (74)

UA GRADUATES 32 (44)

PROFFESIONAL TRAINING 19 (28)

FEE FOR SERVICE 69 (96)

NOT SINGLE-HANDED 35 (49)

GPPTs IN PRACTICE (3) 16 (22)

PART TIME 13 (19)

PROVINCE

Antwerp 44 (61)

Brussels 2 (3)

Limburg 5 (7)

West Flanders 12 (17)

East Flanders 9 (13)

PEAKFLOW METER 67 (93)

SPIROMETER 16 (22)

TRAINING PRACTICE 24 (33)

ACADEMIC LINK 23 (32)

RECORDS OF HOME VISITS 59 (82)

COMPUTERIZED RECORDS 51 (71)

COMPLEMENTARY MEDICINE 2 (3)

Figures are means (standard deviation)

AGE AT START OF THIS STUDY 44 (8)

PATIENT ENCOUNTERS PER WEEK 104 (42)

HOME VISITS PER WEEK 34 (19)

MEDICAL REPRESENTATIVES PER MONTH 15 (10)

ATC J COST RATIO (4) 15 (7)

ATC J VOLUME RATIO (4) 3 (1)

(1) General practitioners including the 1448 patients eligible for analysis. Their characteristics do not

differ from the characteristics of the other GPs who agreed to participate in this study (n=13). (2) Denominators vary due to missing values (3) General Practitioners in Professional Training (4) The ratios the gross amount for antimicrobials for systemic use (ATC J)/ the gross amount for all

pharmaceutical specialties and the volume (Daily Defined Dosage) DDD)) of ATC J/ the volume for all pharmaceutical specialties are both expressed as percentages on individual prescribing feedback from the National Sickness and Invalidity Insurance Institution (NSIII) to GPs. We asked the participating GPs for these percentages and calculated their mean.


55

Data Collection and Measures

The GPs were asked to use pre-printed forms to record patient demographics, the presence of co-morbidity and risk, symptoms, signs, as well as the circumstances of the consultation, the tests ordered, and the prescription of a follow up visit, of a referral and of an antibiotic (Table 2). For co-morbidity and risk, symptoms, signs, and for the circumstances ’ requests for antibiotics’ and ‘requests for other medication’ the three possible answer categories were yes, no, and don’ t know. For the circumstances ‘workload’ and ‘impression’ the three categories were low, high, and very high, and not ill, ill, and very ill, respectively. For ‘tests ordered’ and ‘prescriptions’ , there were only two possible answer categories, viz. yes and no.

Statistical Analyses

We calculated frequency distributions of individual variables and assessed univariate associations between each variable and the prescription of antibiotics. Continuous variables were converted to categorical data for the univariate analyses but treated as continuous data for the multivariate analysis.

We developed a model to obtain a valid estimate of the relationship between the GPs’ perception of the patients’ request for an antibiotic and their prescription of antibiotics. We used a hierarchical backwards elimination procedure described by Kleinbaum,16 taking clustering of the data into account (see box 2). Before starting the procedure, all categorical variables were dichotomised. Since we aimed to estimate the effect of the perception of a request for an antibiotic, and since we wanted to control the above relationship only for the presence of the other covariates, we dichotomised co-morbidity and risk, symptoms, signs, and the circumstance ‘requests antibiotics’ and ‘requests other medication’ by recoding don’ t know into no, and the circumstances ‘workload’ and ‘impression’ by recoding very high into high, and very ill into ill, respectively. To deal with collinearity, the variables ‘reduced breathing sounds’ , ‘wheezing’ , ‘ronchi’ , and ‘crepitations’ were replaced by the variable ‘lung auscultation’ , representing the number of abnormal auscultatory findings, while a new dichotomous variable ‘higher risk’ was created based upon Fine’ s prediction rule to identify patients with community-acquired pneumonia at low risk for mortality or complications (Table 2).17

Chapter IV

56

Statistical analyses were performed with SAS statistical software.18

Results

72 GPs participated in the study (Fig. 1), with 1448 patients eligible for analysis. According to these GPs 218 (15%) asked for an antibiotic and 500 (35%) were prescribed an antibiotic (Table 2).

Univariate analysis

The prescription of antibiotics was associated with medical and non-medical information. The categorical variables and conversion of the continuous variables into categorical data reveals that antibiotics were prescribed more often for the oldest patients, in cases of prolonged coughing and more abnormal auscultatory findings. There is also a higher incidence of antibiotic prescription among younger GPs, those with the highest number of patient encounters and home visits on a weekly basis, GPs seeing a high number of medical representatives per month, and GPs prescribing relatively more antimicrobials for systemic use (ATC J) in cost and in volume (ATC J cost ratio and ATC J volume ratio respectively) (Table 3). In the event of a medical history of COPD, a patient reporting a feeling of sickness, symptoms like sputum, fever and shortness of breath, or signs such as percussion dullness, antibiotics were prescribed more often too (Table 2). Likewise, there was a strong link between the GP’ s perception of a patient’ s request for an antibiotic and the prescription of one (OR = 4.64 (95% CI: 2.96-7.26)) (Table 2).

For these associations, the dependence of a pair of responses belonging to the same cluster was highly significant, with the intra-cluster correlation coefficient being 0.20 on average.


57

Box 2 Hierarchical backwards elimination procedure and cluster data

To obtain a valid estimate of the relationship between the GPs’ perception of the patients’ request for an antibiotic (E) and the prescription of antibiotics by GPs (X), we estimated a logistic model which contained all covariates (V’s) as possible confounders and all E*V interaction terms as possible effect modifiers: logit P(X) = � + � E +� � V + � � E*V. The covariates were the other information the GPs recorded about the patients, as well as their characteristics. We also added the interaction terms of gender and age, and gender and year of birth, respectively, as well as the variables year, group and year*group to control for the cRCT design. If some of the Vs or E*Vs dropped out of the starting model due to collinearity, confounding and interaction were evaluated in a stratified analysis of E versus X controlling for each V separately.

First, interactions were assessed by eliminating one by one the interaction term with least significant type 3 score statistics. Only significant E*Vs were retained in a ‘gold standard’ model. P-values of E*V parameter estimates would be considered significant if smaller than 0.01 instead of smaller than 0.05 only if necessary for a clear interpretation of the effect of E on X. Second, the confounding effect of all Vs not in significant E*Vs in the full model was assessed, followed by precision considerations. We looked for a subset of V's for which the model gave roughly the same parameter estimates for E and the significant E*Vs, but with narrower confidence intervals.

We adjusted logistic regression estimates for clustering within our data (patients are nested within GPs).19 We used alternating logistic regression (ALR), a technique closely related to generalized estimating equations (GEE).20 With ALR, estimating equations are specified for marginal and association parameters. The association between pairs of responses is measured by log odds ratios(�), instead of correlations as with ordinary GEE. The advantage of ALR over GEE is that the association between measurements can be modelled and that uncertainty measures are attached to the estimated dependence parameters. Using GEE we can also provide an order of magnitude for the intra-cluster correlation coefficient (�) which is related to � in ALR.21

The marriage of GEE or ALR with goodness-of-fit (GOF) is not an easy one.22-25 Our approach to fit a broader model with interactions and to test whether the additional terms are significant is regarded as an appropriate way to determine the fit as well.25 Furthermore, an extension of the Hosmer and Lemeshow GOF statistic to marginal regression models for repeated binary responses was used to determine whether the model fits the data.25 In order to assess the significance of the proposed GOF statistic score statistics were used. A significant score statistic indicates that the proposed model leaves a substantial amount of variability in the data not taken into account. The original Hosmer and Lemeshow GOF statistic for ordinary logistic regression by assessing agreement between predicted and observed risk by decile of predicted risk was also used.26 �

Chapter IV

58

Tabl

e2

Pre

dict

ors

ofth

epr

escr

iptio

nof

antib

iotic

sby

Fle

mis

hge

nera

lpra

ctiti

oner

s(G

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ults

acut

eco

ugh

patie

nts.

Figu

res

are

num

bers

(per

cent

age)

ofa

dults

(1)

Pre

scrib

edN

ot p

resc

ribed

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de o

dds

ratio

Adj

uste

d od

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tio(2

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tibio

tics

antib

iotic

s(9

5% C

I)(3)

(95%

CI)(

3)D

emog

raph

ics

AG

E1,

01(1

,00

to1,

02)

†1,

02(1

,00

to1,

04)

ME

N22

0(4

7)39

1(4

3)1,

07(0

,90

to1,

28)

2,20

(0,7

3to

6,59

)C

o-m

orbi

dity

& R

isk

AS

TH

MA

51(1

0)87

(9)

1,31

(0,9

7 to

1,7

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52(0

,21

to 1

,26)

CO

PD

(C

AR

A)

54(1

1)57

(6)

2,39

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7 to

3,6

4)†

0,77

(0,3

5 to

1,6

9)A

CE

-INH

IBIT

OR

17(3

)18

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9)A

SP

IRA

TIO

N R

ISK

6(1

)8

(1)

2,85

(1,8

7 to

4,3

4)†

14,7

9(1

,24

to 1

76,7

1)

†T

RO

MB

O-E

MB

OLI

C R

ISK

17(3

)50

(5)

1,07

(0,6

9 to

1,6

4)0,

55(0

,15

to 2

,08)

SM

OK

ING

183

(37)

281

(30)

1,56

(1,2

5 to

1,9

5)†

1,00

(0,5

9 to

1,6

8)C

ircu

mst

ance

sH

IGH

WO

RK

LOA

D27

4(5

5)53

8(5

8)1,

14(0

,88

to 1

,47)

1,04

(0,6

8 to

1,5

9)IM

PR

ES

SIO

N O

F S

ICK

NE

SS

295

(61)

319

(35)

3,04

(2,2

9 to

4,0

4)†

2,28

(1,4

7 to

3,5

3)

†

RE

QU

ES

T F

OR

AN

TIB

IOT

ICS

125

(25)

93(1

0)4,

64(2

,96

to 7

,26)

†20

,83

(8,8

6 to

48,

99)

†

RE

QU

ES

T F

OR

ME

DIC

AT

ION

253

(52)

480

(51)

0,97

(0,7

4 to

1,2

6)0,

98(0

,62

to 1

,54)

Sym

ptom

sD

UR

AT

ION

OF

CO

UG

HIN

G1,

05(1

,03

to 1

,07)

†1,

04(0

,99

to 1

,10)

SP

UT

UM

374

(75)

458

(49)

3,04

(2,3

2 to

3,9

7)†

2,52

(1,6

2 to

3,9

2)

†F

EV

ER

166

(33)

243

(26)

1,49

(1,1

7 to

1,8

9)†

1,11

(0,6

7 to

1,8

3)R

UN

NY

NO

SE

306

(62)

581

(62)

1,04

(0,7

9 to

1,3

7)0,

96(0

,60

to 1

,53)

HE

AD

AC

HE

281

(57)

446

(48)

1,38

(1,1

2 to

1,7

1)†

1,57

(1,0

3 to

2,3

7)

†M

US

CLE

AC

HE

175

(36)

301

(33)

1,27

(1,0

1 to

1,5

9)†

0,75

(0,4

8 to

1,1

7)S

OA

R T

HR

OA

T29

9(6

1)52

5(5

6)0,

96(0

,77

to 1

,19)

1,22

(0,7

7 to

1,9

6)W

HE

EZI

NG

138

(28)

136

(15)

2,34

(1,7

8 to

3,0

7)†

0,63

(0,3

4 to

1,1

7)S

HO

RT

OF

BR

EA

TH

185

(38)

216

(23)

2,38

(1,8

5 to

3,0

5)†

1,27

(0,6

8 to

2,3

7)C

HE

ST

PA

IN21

5(4

4)26

3(2

9)2,

02(1

,61

to 2

,52)

†1,

68(1

,07

to 2

,65)

†

LOS

S O

F A

PP

ET

ITE

164

(34)

194

(22)

2,20

(1,6

9 to

2,8

7)†

1,22

(0,7

4 to

2,0

2)LI

MIT

ED

AC

TIV

ITY

255

(52)

374

(41)

1,92

(1,4

7 to

2,5

2)†

1,73

(0,8

7 to

3,4

2)S

igns

Hig

her

risk(

4)

212

(42)

323

(34)

1,38

(1,1

1 to

1,7

1)†

1,21

(0,7

8 to

1,8

7)N

umbe

r of

abn

orm

al a

uscu

ltato

ry fi

ndin

g(5)

2,53

(2,0

2 to

3,1

8)†

3,04

(2,0

3 to

4,5

4)

†P

ER

CU

SS

ION

DU

LNE

SS

9(2

)6

(1)

6,15

(0,7

1 to

53,

21)

1,46

(0,1

5 to

13,

80)

Tes

t ord

erin

gR

AD

IOG

RA

PH

21(4

)22

(2)

2,99

(1,4

9 to

6,0

3)†

2,41

(0,5

8 to

10,

06)

SP

UT

UM

AN

ALY

SIS

7(1

)8

(1)

2,90

(0,9

7 to

8,6

9)0,

45(0

,07

to 2

,82)

INFE

CT

ION

PA

RA

ME

TE

RS

17(4

)13

(1)

3,72

(1,3

7 to

10,

11)

†28

,04

(2,8

6 to

274

,54)

†S

ER

OLO

GY

6(1

)12

(1)

1,72

(0,5

4 to

5,4

9)0,

11(0

,01

to 1

,31)

OT

HE

R11

(2)

28(3

)1,

50(0

,73

to 3

,06)

1,76

(0,5

6 to

5,5

6)P

resc

ript

ions

RE

FER

RA

L13

(3)

21(2

)1,

71(0

,98

to 3

,00)

0,04

(0,0

1 to

0,1

4)

†F

OLL

OW

UP

CO

NT

AC

T69

(14)

68(8

)3,

06(1

,99

to 4

,69)

†2,

18(0

,81

to 5

,85)

Tabl

e2

Pre

dict

ors

ofth

epr

escr

iptio

nof

antib

iotic

sby

Fle

mis

hge

nera

lpra

ctiti

oner

s(G

Ps)

inad

ults

acut

eco

ugh

patie

nts.

Figu

res

are

num

bers

(per

cent

age)

ofa

dults

(1)

Pre

scrib

edN

ot p

resc

ribed

Cru

de o

dds

ratio

Adj

uste

d od

dsra

tio(2

)an

tibio

tics

antib

iotic

s(9

5% C

I)(3)

(95%

CI)(

3)D

emog

raph

ics

AG

E1,

01(1

,00

to1,

02)

†1,

02(1

,00

to1,

04)

ME

N22

0(4

7)39

1(4

3)1,

07(0

,90

to1,

28)

2,20

(0,7

3to

6,59

)C

o-m

orbi

dity

& R

isk

AS

TH

MA

51(1

0)87

(9)

1,31

(0,9

7 to

1,7

6)0,

52(0

,21

to 1

,26)

CO

PD

(C

AR

A)

54(1

1)57

(6)

2,39

(1,5

7 to

3,6

4)†

0,77

(0,3

5 to

1,6

9)A

CE

-INH

IBIT

OR

17(3

)18

(2)

2,13

(1,0

1 to

4,4

9)†

1,05

(0,2

6 to

4,1

9)A

SP

IRA

TIO

N R

ISK

6(1

)8

(1)

2,85

(1,8

7 to

4,3

4)†

14,7

9(1

,24

to 1

76,7

1)

†T

RO

MB

O-E

MB

OLI

C R

ISK

17(3

)50

(5)

1,07

(0,6

9 to

1,6

4)0,

55(0

,15

to 2

,08)

SM

OK

ING

183

(37)

281

(30)

1,56

(1,2

5 to

1,9

5)†

1,00

(0,5

9 to

1,6

8)C

ircu

mst

ance

sH

IGH

WO

RK

LOA

D27

4(5

5)53

8(5

8)1,

14(0

,88

to 1

,47)

1,04

(0,6

8 to

1,5

9)IM

PR

ES

SIO

N O

F S

ICK

NE

SS

295

(61)

319

(35)

3,04

(2,2

9 to

4,0

4)†

2,28

(1,4

7 to

3,5

3)

†

RE

QU

ES

T F

OR

AN

TIB

IOT

ICS

125

(25)

93(1

0)4,

64(2

,96

to 7

,26)

†20

,83

(8,8

6 to

48,

99)

†

RE

QU

ES

T F

OR

ME

DIC

AT

ION

253

(52)

480

(51)

0,97

(0,7

4 to

1,2

6)0,

98(0

,62

to 1

,54)

Sym

ptom

sD

UR

AT

ION

OF

CO

UG

HIN

G1,

05(1

,03

to 1

,07)

†1,

04(0

,99

to 1

,10)

SP

UT

UM

374

(75)

458

(49)

3,04

(2,3

2 to

3,9

7)†

2,52

(1,6

2 to

3,9

2)

†F

EV

ER

166

(33)

243

(26)

1,49

(1,1

7 to

1,8

9)†

1,11

(0,6

7 to

1,8

3)R

UN

NY

NO

SE

306

(62)

581

(62)

1,04

(0,7

9 to

1,3

7)0,

96(0

,60

to 1

,53)

HE

AD

AC

HE

281

(57)

446

(48)

1,38

(1,1

2 to

1,7

1)†

1,57

(1,0

3 to

2,3

7)

†M

US

CLE

AC

HE

175

(36)

301

(33)

1,27

(1,0

1 to

1,5

9)†

0,75

(0,4

8 to

1,1

7)S

OA

R T

HR

OA

T29

9(6

1)52

5(5

6)0,

96(0

,77

to 1

,19)

1,22

(0,7

7 to

1,9

6)W

HE

EZI

NG

138

(28)

136

(15)

2,34

(1,7

8 to

3,0

7)†

0,63

(0,3

4 to

1,1

7)S

HO

RT

OF

BR

EA

TH

185

(38)

216

(23)

2,38

(1,8

5 to

3,0

5)†

1,27

(0,6

8 to

2,3

7)C

HE

ST

PA

IN21

5(4

4)26

3(2

9)2,

02(1

,61

to 2

,52)

†1,

68(1

,07

to 2

,65)

†

LOS

S O

F A

PP

ET

ITE

164

(34)

194

(22)

2,20

(1,6

9 to

2,8

7)†

1,22

(0,7

4 to

2,0

2)LI

MIT

ED

AC

TIV

ITY

255

(52)

374

(41)

1,92

(1,4

7 to

2,5

2)†

1,73

(0,8

7 to

3,4

2)S

igns

Hig

her

risk(

4)

212

(42)

323

(34)

1,38

(1,1

1 to

1,7

1)†

1,21

(0,7

8 to

1,8

7)N

umbe

r of

abn

orm

al a

uscu

ltato

ry fi

ndin

g(5)

2,53

(2,0

2 to

3,1

8)†

3,04

(2,0

3 to

4,5

4)

†P

ER

CU

SS

ION

DU

LNE

SS

9(2

)6

(1)

6,15

(0,7

1 to

53,

21)

1,46

(0,1

5 to

13,

80)

Tes

t ord

erin

gR

AD

IOG

RA

PH

21(4

)22

(2)

2,99

(1,4

9 to

6,0

3)†

2,41

(0,5

8 to

10,

06)

SP

UT

UM

AN

ALY

SIS

7(1

)8

(1)

2,90

(0,9

7 to

8,6

9)0,

45(0

,07

to 2

,82)

INFE

CT

ION

PA

RA

ME

TE

RS

17(4

)13

(1)

3,72

(1,3

7 to

10,

11)

†28

,04

(2,8

6 to

274

,54)

†S

ER

OLO

GY

6(1

)12

(1)

1,72

(0,5

4 to

5,4

9)0,

11(0

,01

to 1

,31)

OT

HE

R11

(2)

28(3

)1,

50(0

,73

to 3

,06)

1,76

(0,5

6 to

5,5

6)P

resc

ript

ions

RE

FER

RA

L13

(3)

21(2

)1,

71(0

,98

to 3

,00)

0,04

(0,0

1 to

0,1

4)

†F

OLL

OW

UP

CO

NT

AC

T69

(14)

68(8

)3,

06(1

,99

to 4

,69)

†2,

18(0

,81

to 5

,85)

Tabl

e2

Pre

dict

ors

ofth

epr

escr

iptio

nof

antib

iotic

sby

Fle

mis

hge

nera

lpra

ctiti

oner

s(G

Ps)

inad

ults

acut

eco

ugh

patie

nts.

Figu

res

are

num

bers

(per

cent

age)

ofa

dults

(1)

Pre

scrib

edN

ot p

resc

ribed

Cru

de o

dds

ratio

Adj

uste

d od

dsra

tio(2

)an

tibio

tics

antib

iotic

s(9

5% C

I)(3)

(95%

CI)(

3)D

emog

raph

ics

AG

E1,

01(1

,00

to1,

02)

Tabl

e2

Pre

dict

ors

ofth

epr

escr

iptio

nof

antib

iotic

sby

Fle

mis

hge

nera

lpra

ctiti

oner

s(G

Ps)

inad

ults

acut

eco

ugh

patie

nts.

Figu

res

are

num

bers

(per

cent

age)

ofa

dults

(1)

Pre

scrib

edN

ot p

resc

ribed

Cru

de o

dds

ratio

Adj

uste

d od

dsra

tio(2

)an

tibio

tics

antib

iotic

s(9

5% C

I)(3)

(95%

CI)(

3)D

emog

raph

ics

AG

E1,

01(1

,00

to1,

02)

†1,

02(1

,00

to1,

04)

ME

N22

0(4

7)39

1(4

3)1,

07(0

,90

to1,

28)

2,20

(0,7

3to

6,59

)C

o-m

orbi

dity

& R

isk

AS

TH

MA

51(1

0)87

(9)

1,31

(0,9

7 to

1,7

6)0,

52(0

,21

to 1

,26)

CO

PD

(C

AR

A)

54(1

1)57

(6)

2,39

(1,5

7 to

3,6

4)†

0,77

(0,3

5 to

1,6

9)

†1,

02(1

,00

to1,

04)

ME

N22

0(4

7)39

1(4

3)1,

07(0

,90

to1,

28)

2,20

(0,7

3to

6,59

)C

o-m

orbi

dity

& R

isk

AS

TH

MA

51(1

0)87

(9)

1,31

(0,9

7 to

1,7

6)0,

52(0

,21

to 1

,26)

CO

PD

(C

AR

A)

54(1

1)57

(6)

2,39

(1,5

7 to

3,6

4)†

0,77

(0,3

5 to

1,6

9)A

CE

-INH

IBIT

OR

17(3

)18

(2)

2,13

(1,0

1 to

4,4

9)†

1,05

(0,2

6 to

4,1

9)A

SP

IRA

TIO

N R

ISK

6(1

)8

(1)

2,85

(1,8

7 to

4,3

4)†

14,7

9(1

,24

to 1

76,7

1)

†T

RO

MB

O-E

MB

OLI

C R

ISK

17(3

)50

(5)

1,07

(0,6

9 to

1,6

4)0,

55(0

,15

to 2

,08)

SM

OK

ING

183

(37)

281

(30)

1,56

(1,2

5 to

1,9

5)†

1,00

(0,5

9 to

1,6

8)

AC

E-IN

HIB

ITO

R17

(3)

18(2

)2,

13(1

,01

to 4

,49)

†1,

05(0

,26

to 4

,19)

AS

PIR

AT

ION

RIS

K6

(1)

8(1

)2,

85(1

,87

to 4

,34)

†14

,79

(1,2

4 to

176

,71)

†

TR

OM

BO

-EM

BO

LIC

RIS

K17

(3)

50(5

)1,

07(0

,69

to 1

,64)

0,55

(0,1

5 to

2,0

8)S

MO

KIN

G18

3(3

7)28

1(3

0)1,

56(1

,25

to 1

,95)

†1,

00(0

,59

to 1

,68)

Cir

cum

stan

ces

HIG

H W

OR

KLO

AD

274

(55)

538

(58)

1,14

(0,8

8 to

1,4

7)1,

04(0

,68

to 1

,59)

IMP

RE

SS

ION

OF

SIC

KN

ES

S29

5(6

1)31

9(3

5)3,

04(2

,29

to 4

,04)

†2,

28(1

,47

to 3

,53)

†R

EQ

UE

ST

FO

R A

NT

IBIO

TIC

S12

5(2

5)93

(10)

4,64

(2,9

6 to

7,2

6)†

20,8

3(8

,86

to 4

8,99

)

†R

EQ

UE

ST

FO

R M

ED

ICA

TIO

N25

3

Cir

cum

stan

ces

HIG

H W

OR

KLO

AD

274

(55)

538

(58)

1,14

(0,8

8 to

1,4

7)1,

04(0

,68

to 1

,59)

IMP

RE

SS

ION

OF

SIC

KN

ES

S29

5(6

1)31

9(3

5)3,

04(2

,29

to 4

,04)

†2,

28(1

,47

to 3

,53)

†R

EQ

UE

ST

FO

R A

NT

IBIO

TIC

S12

5(2

5)93

(10)

4,64

(2,9

6 to

7,2

6)†

20,8

3(8

,86

to 4

8,99

)

†R

EQ

UE

ST

FO

R M

ED

ICA

TIO

N25

3(5

2)48

0(5

1)0,

97(0

,74

to 1

,26)

0,98

(0,6

2 to

1,5

4)S

ympt

oms

DU

RA

TIO

N O

F C

OU

GH

ING

1,05

(1,0

3 to

1,0

7)†

1,04

(0,9

9 to

1,1

0)S

PU

TU

M37

4(7

5)45

8(4

9)3,

04(2

,32

to 3

,97)

†2,

52(1

,62

to 3

,92)

†

FE

VE

R16

6(3

3)24

3(2

6)1,

49(1

,17

to 1

,89)

†1,

11(0

,67

to 1

,83)

(52)

480

(51)

0,97

(0,7

4 to

1,2

6)0,

98(0

,62

to 1

,54)

Sym

ptom

sD

UR

AT

ION

OF

CO

UG

HIN

G1,

05(1

,03

to 1

,07)

†1,

04(0

,99

to 1

,10)

SP

UT

UM

374

(75)

458

(49)

3,04

(2,3

2 to

3,9

7)†

2,52

(1,6

2 to

3,9

2)

†F

EV

ER

166

(33)

243

(26)

1,49

(1,1

7 to

1,8

9)†

1,11

(0,6

7 to

1,8

3)R

UN

NY

NO

SE

306

(62)

581

(62)

1,04

(0,7

9 to

1,3

7)0,

96(0

,60

to 1

,53)

HE

AD

AC

HE

281

(57)

446

(48)

1,38

(1,1

2 to

1,7

1)†

1,57

(1,0

3 to

2,3

7)

†M

US

CLE

AC

HE

175

(36)

301

(33)

1,27

(1,0

1 to

1,5

9)†

0,75

(0,4

8 to

1,1

7)S

OA

R T

HR

OA

T29

9(6

1)52

5(5

6)0,

96(0

,77

to 1

,19)

1,22

(0,7

7 to

1,9

6)

RU

NN

Y N

OS

E30

6(6

2)58

1(6

2)1,

04(0

,79

to 1

,37)

0,96

(0,6

0 to

1,5

3)H

EA

DA

CH

E28

1(5

7)44

6(4

8)1,

38(1

,12

to 1

,71)

†1,

57(1

,03

to 2

,37)

†

MU

SC

LE A

CH

E17

5(3

6)30

1(3

3)1,

27(1

,01

to 1

,59)

†0,

75(0

,48

to 1

,17)

SO

AR

TH

RO

AT

299

(61)

525

(56)

0,96

(0,7

7 to

1,1

9)1,

22(0

,77

to 1

,96)

WH

EE

ZIN

G13

8(2

8)13

6(1

5)2,

34(1

,78

to 3

,07)

†0,

63(0

,34

to 1

,17)

SH

OR

T O

F B

RE

AT

H18

5(3

8)21

6(2

3)2,

38(1

,85

to 3

,05)

†1,

27(0

,68

to 2

,37)

CH

ES

TP

AIN

215

(44)

263

(29)

2,02

(1,6

1 to

2,5

2)†

1,68

(1,0

7 to

2,6

5)

†LO

SS

OF

AP

PE

TIT

E16

4(3

4)19

4(2

2)2,

20(1

,69

to 2

,87)

†1,

22(0

,74

to 2

,02)

WH

EE

ZIN

G13

8(2

8)13

6(1

5)2,

34(1

,78

to 3

,07)

†0,

63(0

,34

to 1

,17)

SH

OR

T O

F B

RE

AT

H18

5(3

8)21

6(2

3)2,

38(1

,85

to 3

,05)

†1,

27(0

,68

to 2

,37)

CH

ES

TP

AIN

215

(44)

263

(29)

2,02

(1,6

1 to

2,5

2)†

1,68

(1,0

7 to

2,6

5)

†LO

SS

OF

AP

PE

TIT

E16

4(3

4)19

4(2

2)2,

20(1

,69

to 2

,87)

†1,

22(0

,74

to 2

,02)

LIM

ITE

D A

CT

IVIT

Y25

5(5

2)37

4(4

1)1,

92(1

,47

to 2

,52)

†1,

73(0

,87

to 3

,42)

Sig

nsH

ighe

r ris

k(4)

21

2(4

2)32

3(3

4)1,

38(1

,11

to 1

,71)

†1,

21(0

,78

to 1

,87)

Num

ber

of a

bnor

mal

aus

culta

tory

find

ing(

5)2,

53(2

,02

to 3

,18)

†3,

04(2

,03

to 4

,54)

†

PE

RC

US

SIO

N D

ULN

ES

S9

(2)

6(1

)6,

15

LIM

ITE

D A

CT

IVIT

Y25

5(5

2)37

4(4

1)1,

92(1

,47

to 2

,52)

†1,

73(0

,87

to 3

,42)

Sig

nsH

ighe

r ris

k(4)

21

2(4

2)32

3(3

4)1,

38(1

,11

to 1

,71)

†1,

21(0

,78

to 1

,87)

Num

ber

of a

bnor

mal

aus

culta

tory

find

ing(

5)2,

53(2

,02

to 3

,18)

†3,

04(2

,03

to 4

,54)

†

PE

RC

US

SIO

N D

ULN

ES

S9

(2)

6(1

)6,

15(0

,71

to 5

3,21

)1,

46(0

,15

to 1

3,80

)T

est o

rder

ing

RA

DIO

GR

AP

H21

(4)

22(2

)2,

99(1

,49

to 6

,03)

†2,

41(0

,58

to 1

0,06

)S

PU

TU

M A

NA

LYS

IS7

(1)

8(1

)2,

90(0

,97

to 8

,69)

0,45

(0,0

7 to

2,8

2)IN

FEC

TIO

N P

AR

AM

ET

ER

S17

(4)

13(1

)3,

72(1

,37

to 1

0,11

)†

28,0

4(2

,86

to 2

74,5

4)†

(0,7

1 to

53,

21)

1,46

(0,1

5 to

13,

80)

Tes

t ord

erin

gR

AD

IOG

RA

PH

21(4

)22

(2)

2,99

(1,4

9 to

6,0

3)†

2,41

(0,5

8 to

10,

06)

SP

UT

UM

AN

ALY

SIS

7(1

)8

(1)

2,90

(0,9

7 to

8,6

9)0,

45(0

,07

to 2

,82)

INFE

CT

ION

PA

RA

ME

TE

RS

17(4

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(1)

3,72

(1,3

7 to

10,

11)

†28

,04

(2,8

6 to

274

,54)

†S

ER

OLO

GY

6(1

)12

(1)

1,72

(0,5

4 to

5,4

9)0,

11(0

,01

to 1

,31)

OT

HE

R11

(2)

28(3

)1,

50(0

,73

to 3

,06)

1,76

(0,5

6 to

5,5

6)P

resc

ript

ions

RE

FER

RA

L13

(3)

21(2

)1,

71(0

,98

to 3

,00)

0,04

(0,0

1 to

0,1

4)

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OLL

OW

UP

CO

NT

AC

T69

SE

RO

LOG

Y6

(1)

12(1

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72(0

,54

to 5

,49)

0,11

(0,0

1 to

1,3

1)O

TH

ER

11(2

)28

(3)

1,50

(0,7

3 to

3,0

6)1,

76(0

,56

to 5

,56)

Pre

scri

ptio

nsR

EFE

RR

AL

13(3

)21

(2)

1,71

(0,9

8 to

3,0

0)0,

04(0

,01

to 0

,14)

†

FO

LLO

W U

P C

ON

TA

CT

69(1

4)68

(8)

3,06

(1,9

9 to

4,6

9)†

2,18

(0,8

1 to

5,8

5)


59

Tabl

e2

cont

inue

d.

Pre

scrib

edN

ot p

resc

ribed

Cru

de o

dds

ratio

Adj

uste

d od

dsra

tio(2

)an

tibio

tics

antib

iotic

s(9

5% C

I)(3)

(95%

CI)(

3)G

Ps’

char

acte

rist

ics

ME

N1,

31(0

,86

to2,

02)

456,

00(0

,04

to4,

93E

+6)

UA

GR

AD

UA

TE

198

(40)

433

(46)

0,84

(0,5

3to

1,33

)1,

70(0

,71

to4,

09)

PR

OFE

SS

ION

AL

TR

AIN

ING

111

(24)

259

(29)

0,85

(0,5

6to

1,29

)0,

20(0

,10

to0,

42)

†F

EE

FO

R S

ER

VIC

E49

7(9

9)92

6(9

8)4,

06(2

,64

to6,

23)

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63(0

,10

to26

,09)

NO

T S

ING

LE-H

AN

DE

D19

9(4

1)45

1(4

8)0,

74(0

,48

to1,

15)

0,51

(0,1

8to

1,44

)G

PP

Ts

IN P

RA

CT

ICE

66(1

3)19

7(2

1)0,

65(0

,40

to1,

07)

1,11

(0,2

8 to

4,3

6)P

AR

T T

IME

59(1

2)19

8(2

1)0,

52(0

,32

to 0

,86)

†1,

35(0

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to 5

,16)

PR

OV

INC

EA

ntw

erp

269

(54)

670

(71)

11

Bru

ssel

s41

(8)

28(3

)3,

38(1

,16

to 9

,84)

†29

,20

(4,8

5 to

176

,71)

†Li

mbu

rg35

(7)

37(4

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24(0

,86

to 5

,89)

2,75

(0,8

8 to

8,6

3)W

est F

land

ers

98(2

0)93

(10)

2,07

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5 to

3,4

3)†

3,95

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0 to

9,7

6)†

Eas

t Fla

nder

s57

(11)

120

(13)

1,12

(0,6

0 to

2,1

1)1,

88(0

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to 9

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PE

AK

FLO

W M

ET

ER

483

(97)

904

(95)

1,70

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8 to

2,9

6)3,

43(0

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to 4

6,94

)S

PIR

OM

ET

ER

93(1

9)30

3(3

2)0,

61(0

,37

to 0

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44(0

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to 0

,90)

†T

RA

ININ

G P

RA

CT

ICE

137

(27)

355

(37)

0,72

(0,4

6 to

1,1

3)1,

32(0

,61

to 2

,85)

AC

AD

EM

IC L

INK

126

(25)

342

(36)

0,71

(0,4

6 to

1,1

1)1,

44(0

,67

to 3

,10)

RE

CO

RD

S O

F H

OM

E V

ISIT

S37

6(7

5)80

8(8

5)0,

61(0

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to 1

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1,38

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8 to

2,8

1)C

OM

PU

TE

RIS

ED

RE

CO

RD

S33

3(6

7)66

3(7

0)1,

08(0

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1,28

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0 to

2,7

2)C

OM

PLE

ME

NT

AR

Y M

ED

ICIN

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(3)

0,53

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0,7

0)0,

20(0

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to 1

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YE

AR

OF

BIR

TH

1,01

(0,9

9 to

1,0

3)1,

22(1

,01

to 1

,47)

†

AV

ER

AG

E N

UM

BE

R O

F P

AT

IEN

T E

NC

OU

NT

ER

PE

R W

EE

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to 1

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to 1

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ER

AG

E N

UM

BE

R O

F H

OM

E V

ISIT

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WE

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1,0

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GE

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OF

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PR

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8 to

1,0

4)1,

04(0

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to 1

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AT

C J

CO

ST

RA

TIO

(6)

1,05

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1,0

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0,94

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4 to

1,0

6)A

TC

J V

OLU

ME

RA

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1,35

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2,5

7)D

esig

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IST

RA

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EA

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0(3

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1(5

1)0,

64(0

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to 0

,80)

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74(0

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to 1

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RE

GIS

TR

AT

ION

GR

OU

P22

7(4

5)40

6(4

3)0,

99(0

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to 1

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0,75

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2 to

1,7

8)Y

EA

R*G

RO

UP

78(4

1)20

6(4

3)0,

57(0

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to 0

,82)

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72(0

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to 2

,29)

Inte

ract

ion

term

s fi

nal m

odel

RE

QU

ES

T F

OR

AN

TIB

IOT

ICS

*Num

ber

of a

bnor

mal

aus

culta

tory

find

ings

1,76

(1,3

0 to

2,3

8)0,

23(0

,13

to 0

,41)

PA

TIE

NT

GE

ND

ER

*AG

E1,

00(1

,00

to 1

,01)

0,98

(0,9

6 to

1,0

1)G

P'S

GE

ND

ER

*YE

AR

OF

BIR

TH

1,01

(1,0

0 to

1,0

1)0,

90(0

,76

to 1

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(1) D

enom

inat

ors

vary

due

to m

issi

ng v

alue

s(2

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uste

d fo

r all

varia

bles

in th

e fin

al m

odel

(3) S

core

test

usi

ng A

ltern

ativ

e Lo

gist

ic R

egre

ssio

n†

mea

ns p

<0.0

5 (4

) Pat

ient

age

> 5

0 or

pat

ient

has

con

gest

ive

hear

tfailu

re, c

ereb

rova

scul

ar d

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se, l

iver

dis

ease

, kid

ney

dise

ase

or n

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dis

ease

, or h

as a

ltere

d co

nsci

ousn

ess,

pul

se ra

te>1

25/',

re

spira

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rate

>30/

', te

mpe

ratu

re>3

8°C

or s

ysto

lic b

lood

pre

ssur

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mm

Hg

(5) L

ess

vesi

cula

r bre

athi

ng, w

heez

ing,

ronc

hi o

r cre

pita

tions

(6) T

he ra

tios

of th

e gr

oss

amou

nt fo

r ant

imic

robi

als

for s

yste

mic

use

(ATC

J)/t

he g

ross

am

ount

for a

ll ph

arm

aceu

tical

spe

cial

ties

and

the

volu

me

(Dai

ly D

efin

ed D

osag

e (D

DD

)) o

f ATC

J/th

e vo

lum

e fo

r all

phar

mac

eutic

al s

peci

altie

s ar

e bo

th e

xpre

ssed

as

perc

enta

ges

on in

divi

dual

pre

scrib

ing

feed

back

from

the

Nat

iona

l Sic

knes

s an

d In

valid

ity In

stitu

tion

(NS

II) to

GP

s.

Tabl

e2

cont

inue

d.

Pre

scrib

edN

ot p

resc

ribed

Cru

de o

dds

ratio

Adj

uste

d od

dsra

tio(2

)an

tibio

tics

antib

iotic

s(9

5% C

I)(3)

(95%

CI)(

3)G

Ps’

char

acte

rist

ics

ME

N1,

31(0

,86

to2,

02)

456,

00(0

,04

to4,

93E

+6)

UA

GR

AD

UA

TE

198

(40)

433

(46)

0,84

(0,5

3to

1,33

)1,

70(0

,71

to4,

09)

PR

OFE

SS

ION

AL

TR

AIN

ING

111

(24)

259

(29)

0,85

(0,5

6to

1,29

)0,

20(0

,10

to0,

42)

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EE

FO

R S

ER

VIC

E49

7(9

9)92

6(9

8)4,

06(2

,64

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23)

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63(0

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to26

,09)

NO

T S

ING

LE-H

AN

DE

D19

9(4

1)45

1(4

8)0,

74(0

,48

to1,

15)

0,51

(0,1

8to

1,44

)G

PP

Ts

IN P

RA

CT

ICE

66(1

3)19

7(2

1)0,

65(0

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to1,

07)

1,11

(0,2

8 to

4,3

6)P

AR

T T

IME

59(1

2)19

8(2

1)0,

52(0

,32

to 0

,86)

†1,

35(0

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to 5

,16)

PR

OV

INC

EA

ntw

erp

269

(54)

670

(71)

11

Bru

ssel

s41

(8)

28(3

)3,

38(1

,16

to 9

,84)

†29

,20

(4,8

5 to

176

,71)

†Li

mbu

rg35

(7)

37(4

)2,

24(0

,86

to 5

,89)

2,75

(0,8

8 to

8,6

3)W

est F

land

ers

98(2

0)93

(10)

2,07

(1,2

5 to

3,4

3)†

3,95

(1,6

0 to

9,7

6)†

Eas

t Fla

nder

s57

(11)

120

(13)

1,12

(0,6

0 to

2,1

1)1,

88(0

,37

to 9

,50)

PE

AK

FLO

W M

ET

ER

483

(97)

904

(95)

1,70

(0,9

8 to

2,9

6)3,

43(0

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to 4

6,94

)S

PIR

OM

ET

ER

93(1

9)30

3(3

2)0,

61(0

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to 0

,99)

†0,

44(0

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to 0

,90)

†T

RA

ININ

G P

RA

CT

ICE

137

(27)

355

(37)

0,72

(0,4

6 to

1,1

3)1,

32(0

,61

to 2

,85)

AC

AD

EM

IC L

INK

126

(25)

342

(36)

0,71

(0,4

6 to

1,1

1)1,

44(0

,67

to 3

,10)

RE

CO

RD

S O

F H

OM

E V

ISIT

S37

6(7

5)80

8(8

5)0,

61(0

,35

to 1

,07)

1,38

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8 to

2,8

1)C

OM

PU

TE

RIS

ED

RE

CO

RD

S33

3(6

7)66

3(7

0)1,

08(0

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to 1

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1,28

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0 to

2,7

2)C

OM

PLE

ME

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e Lo

gist

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ient

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0 or

pat

ient

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ease

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se ra

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lic b

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r cre

pita

tions

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he ra

tios

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e gr

oss

amou

nt fo

r ant

imic

robi

als

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mic

use

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J)/t

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ross

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ount

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ll ph

arm

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tical

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cial

ties

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ly D

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)) o

f ATC

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lum

e fo

r all

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eutic

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altie

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ity In

stitu

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) Den

omin

ator

s va

ry d

ue to

mis

sing

val

ues

(2) A

djus

ted

for a

ll va

riabl

es in

the

final

mod

el(3

) Sco

re te

st u

sing

Alte

rnat

ive

Logi

stic

Reg

ress

ion

† m

eans

p<0

.05

(4) P

atie

nt a

ge >

50

or p

atie

nt h

as c

onge

stiv

e he

artfa

ilure

, cer

ebro

vasc

ular

dis

ease

, liv

er d

isea

se, k

idne

y di

seas

e o

r neo

plas

tic d

isea

se, o

r has

alte

red

cons

ciou

snes

s, p

ulse

rate

>125

/',

resp

irato

ry ra

te>3

0/',

tem

pera

ture

>38°

C o

r sys

tolic

blo

od p

ress

ure>

90 m

mH

g(5

) Les

s ve

sicu

lar b

reat

hing

, whe

ezin

g, ro

nchi

or c

repi

tatio

ns(6

) The

ratio

s of

the

gros

s am

ount

for a

ntim

icro

bial

s fo

r sys

tem

ic u

se (A

TC J

)/the

gro

ss a

mou

nt fo

r all

phar

mac

eutic

al s

peci

altie

s an

d th

e vo

lum

e (D

aily

Def

ined

Dos

age

(DD

D))

of A

TC J

/the

volu

me

for a

ll ph

arm

aceu

tical

spe

cial

ties

are

both

exp

ress

ed a

s pe

rcen

tage

s on

indi

vidu

al p

resc

ribin

g fe

edba

ck fr

om th

e N

atio

nal S

ickn

ess

and

Inva

lidity

Inst

itutio

n (N

SII)

to G

Ps.

Chapter IV

60

Multivariate analysis

Some variables dropped out of the model due to collinearity. Of these, only the GPs’ year of birth, the number of patient encounters per week and ATC J cost ratio were significant effect modifiers of the univariate relation between the GPs’ perception of a patient’ s request for antibiotics and a prescription of antibiotics. For younger GPs (year of birth ’ 65 vs. ’ 45), GPs with fewer patient encounters per week (80 vs. 150) and GPs with a higher ATC J cost ratio (.20 vs. .10), the patients’ requests were even more strongly associated with antibiotic prescription.

This resulted in a model containing 7 interaction terms (patient age, smoking, number of abnormal auscultatory findings, GPs’ university of graduation, part-time working status, registration group (control vs. intervention) and registration year (2000 vs. 2001)) (p<0.05). After eliminating interaction terms with a p-value greater than 0.01, only one interaction term was retained in the model. In order to obtain a comprehensible and valid estimate of the effect of GPs’ perception of patients’ requests on their prescribing antibiotics, the final model controls for this interaction term and all possible confounders (Table 2).

This model fits the data well (GOFHorton = 0.71;GOFHosmer-Lemeshow = 0.72). For the patients in the final models (n=819) the univariate association between the GP’ s perception of the patients’ request for antibiotics and the prescription of an antibiotic (OR = 4.60 (2.59-8.17)) was very similar to that for all patients (n=1448).

Because of the introduction of GPs’ characteristics in this model the dependence for a pair of responses belonging to the same cluster was no longer significant, the intra-cluster correlation coefficient being 0.02.

From the final model we learn that the GPs’ perception of the patients request for antibiotics is still significantly associated with the prescription of antibiotics. This association is independent of the other information the GPs recorded and of their characteristics (Table 2). Significant confounders of this association are aspiration risk (ORadj = 14.79 (1.24-176.71)), an impression of sickness (ORadj = 2.28 (1.47-3.53)), the presence of sputum (ORadj = 2.52 (1.62-3.92)), of a headache (ORadj = 1.57 (1.03-2.37)), of thoracic pain (ORadj = 1.68 (1.07-2.65)), the number of abnormal auscultatory findings ((ORadj = 3.04 (2.03-5.54)), investigating infection parameters (ORadj = 28.04 (2.86-274.54)),


61

patient referral (ORadj = 0.04 (0.01-0.14)), the age of the GPs at the start of this study (ORadj = 1.22 (1.01-1.47)), previous professional training (ORadj = 0.20 (0.10-0.42)), having a spirometer in the practice (ORadj = 0.44 (0.21-0.90)), and the practice location (Figure 2).

However, the effect of patients’ requesting antibiotics on GP’ s prescriptions of antibiotics depends on the outcome of the lung auscultation. When a patient is perceived to be requesting antibiotics, they were prescribed significantly more often when the lung auscultation results were normal (ORadj = 20.83 (8.86-48.99) (Figure 2), or in case of only one abnormal auscultatory finding (4.79 (2.16 to 10.60)).

In case of a normal lung auscultation the adjusted predicted probability for an antibiotic prescription is 0.09 (95% CI 0.02-0.30) if no request for antibiotics is perceived compared to 0.84 (0.52-0.97) if a request is perceived. If only one abnormal auscultatory finding is present these probabilities are 0.16 (0.03-0.53), 0.98 (0.92-1.00), respectively. If there is more than one abnormal auscultatory finding there is no relevant and significant difference between a request for an antibiotic and the absence of a request.

Discussion

The GPs’ perception of patient requests for antibiotics is significantly associated with the prescription of antibiotics to adult acute cough patients, even when controlling for the other information the GPs recorded and for their characteristics. Antibiotics were prescribed significantly more often when a patient was perceived to request an antibiotic and the lung auscultation was normal or revealed only one abnormal finding. Aspiration risk, an impression of sickness, the presence of sputum, of headache, and of thoracic pain, abnormal auscultatory findings, investigating infection parameters and a younger GP were also associated with increased antibiotic prescribing. Prescribing depended on the GP’ s practice location as well. Patient referral, previous professional training and having a spirometer in the practice were associated with less prescribing.

Chapter IV

62

Tab

le3

Pre

dict

ors

of th

epr

escr

iptio

nof

antib

iotic

s by

Fle

mis

h ge

nera

l pra

ctiti

oner

s(G

Ps)

inad

ults

acut

e

coug

h pa

tient

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ateg

oric

alva

riabl

es a

ndco

ntin

uous

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bles

conv

erte

d in

to c

ateg

oric

alda

ta.

Figu

res

are

num

bers

(per

cent

age)

ofa

dults

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Cru

de o

dds

ratio

Pre

scrib

edan

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tics

Not

pre

scrib

edan

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tics

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CI)(

2)D

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raph

ics

AG

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01(1

,00

to1,

02)

†A

GE

(3)

1,11

(1,0

2 to

1,2

1)†

18-3

517

6(3

5)38

5(4

1)1

36-4

512

8(2

6)23

9(2

5)1,

16(0

,94

to 1

,44)

46-5

597

(20)

178

(19)

1,19

(0,9

2 to

1,5

2)56

-65

95(1

9)14

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5)1,

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,05

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RA

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F C

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(1,0

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1,0

7)†

DU

RA

TIO

N O

F C

OU

GH

ING

(3)

1,22

(1,1

2 to

1,3

2)†

1-3

190

(38)

451

(48)

14-

611

5(2

3)23

2(2

4)1,

28(1

,01

to 1

,64)

†7-

981

(16)

126

(13)

1,80

(1,3

2 to

2,4

6)†

10-1

227

(5)

41(4

)1,

76(1

,00

to 3

,10)

†>1

287

(17)

98(1

0)2,

12(1

,51

to 2

,98)

†S

igns

Num

ber

of a

bnor

mal

aus

culta

tory

find

ing(

4)2,

53(2

,02

to 3

,18)

†0

216

(43)

729

(77)

11

128

(26)

129

(14)

3,49

(2,5

0 to

4,8

7)†

298

(20)

60(6

)6,

85(4

,26

to 1

1,02

)†

349

(10)

27(3

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-65

71(1

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(10)

164

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210

(42)

432

(46)

0,67

(0,4

1 to

1,0

9)54

-45

202

(40)

364

(38)

0,74

(0,4

5 to

1,2

1)44

-25

17(3

)54

(6)

0,46

(0,2

8 to

0,7

4)A

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NU

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OF

PA

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NT

EN

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AG

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R O

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T E

NC

OU

NT

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PE

R W

EE

K (

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34(1

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to 1

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†<5

156

(11)

98(1

0)1

51-1

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2(3

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7(5

6)0,

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to 1

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101-

150

189

(38)

219

(23)

1,36

(0,7

6 to

2,4

3)15

1-20

048

(10)

86(9

)1,

26(0

,58

to 2

,71)

>200

25(5

)18

(2)

2,35

(1,5

9 to

3,4

9)†

Tab

le3

Pre

dict

ors

of th

epr

escr

iptio

nof

antib

iotic

s by

Fle

mis

h ge

nera

l pra

ctiti

oner

s(G

Ps)

inad

ults

acut

e

coug

h pa

tient

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ateg

oric

alva

riabl

es a

ndco

ntin

uous

varia

bles

conv

erte

d in

to c

ateg

oric

alda

ta.

Figu

res

are

num

bers

(per

cent

age)

ofa

dults

(1)

Cru

de o

dds

ratio

Pre

scrib

edan

tibio

tics

Not

pre

scrib

edan

tibio

tics

(95%

CI)(

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raph

ics

AG

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02)

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GE

(3)

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(1,0

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18-3

517

6(3

5)38

5(4

1)1

36-4

512

8(2

6)23

9(2

5)1,

16(0

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to 1

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46-5

597

(20)

178

(19)

1,19

(0,9

2 to

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2)56

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95(1

9)14

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5)1,

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DU

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F C

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ING

(3)

1,22

(1,1

2 to

1,3

2)†

1-3

190

(38)

451

(48)

14-

611

5(2

3)23

2(2

4)1,

28(1

,01

to 1

,64)

†7-

981

(16)

126

(13)

1,80

(1,3

2 to

2,4

6)†

10-1

227

(5)

41(4

)1,

76(1

,00

to 3

,10)

†>1

287

(17)

98(1

0)2,

12(1

,51

to 2

,98)

†S

igns

Num

ber

of a

bnor

mal

aus

culta

tory

find

ing(

4)2,

53(2

,02

to 3

,18)

†0

216

(43)

729

(77)

11

128

(26)

129

(14)

3,49

(2,5

0 to

4,8

7)†

298

(20)

60(6

)6,

85(4

,26

to 1

1,02

)†

349

(10)

27(3

)11

,80

(6,0

6 to

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99)

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3(1

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to 6

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GP

s’ c

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cter

istic

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to 1

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OF

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TH

(3)

0,88

(0,7

0 to

1,1

1)74

-65

71(1

4)98

(10)

164

-55

210

(42)

432

(46)

0,67

(0,4

1 to

1,0

9)54

-45

202

(40)

364

(38)

0,74

(0,4

5 to

1,2

1)44

-25

17(3

)54

(6)

0,46

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OF

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AG

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T E

NC

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NT

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to 1

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†<5

156

(11)

98(1

0)1

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2(3

6)52

7(5

6)0,

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to 1

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101-

150

189

(38)

219

(23)

1,36

(0,7

6 to

2,4

3)15

1-20

048

(10)

86(9

)1,

26(0

,58

to 2

,71)

>200

25(5

)18

(2)

2,35

(1,5

9 to

3,4

9)†

Tab

le3

Pre

dict

ors

of th

epr

escr

iptio

nof

antib

iotic

s by

Fle

mis

h ge

nera

l pra

ctiti

oner

s(G

Ps)

inad

ults

acut

e

coug

h pa

tient

s.C

ateg

oric

alva

riabl

es a

ndco

ntin

uous

varia

bles

conv

erte

d in

to c

ateg

oric

alda

ta.

Figu

res

are

num

bers

(per

cent

age)

ofa

dults

(1)

Cru

de o

dds

ratio

Pre

scrib

edan

tibio

tics

Not

pre

scrib

edan

tibio

tics

(95%

CI)(

2)D

emog

raph

ics

AG

E1,

01(1

,00

to1,

02)

†A

GE

(3)

1,11

(1,0

2 to

1,2

1)†

Tab

le3

Pre

dict

ors

of th

epr

escr

iptio

nof

antib

iotic

s by

Fle

mis

h ge

nera

l pra

ctiti

oner

s(G

Ps)

inad

ults

acut

e

coug

h pa

tient

s.C

ateg

oric

alva

riabl

es a

ndco

ntin

uous

varia

bles

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erte

d in

to c

ateg

oric

alda

ta.

Figu

res

are

num

bers

(per

cent

age)

ofa

dults

(1)

Cru

de o

dds

ratio

Pre

scrib

edan

tibio

tics

Not

pre

scrib

edan

tibio

tics

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CI)(

2)D

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raph

ics

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to1,

02)

†A

GE

(3)

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(1,0

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517

6(3

5)38

5(4

1)1

36-4

512

8(2

6)23

9(2

5)1,

16(0

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to 1

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46-5

597

(20)

178

(19)

1,19

(0,9

2 to

1,5

2)

18-3

517

6(3

5)38

5(4

1)1

36-4

512

8(2

6)23

9(2

5)1,

16(0

,94

to 1

,44)

46-5

597

(20)

178

(19)

1,19

(0,9

2 to

1,5

2)56

-65

95(1

9)14

1(1

5)1,

40(1

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to 1

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ympt

oms

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RA

TIO

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3 to

1,0

7)†

DU

RA

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N O

F C

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GH

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(3)

1,22

56-6

595

(19)

141

(15)

1,40

(1,0

5 to

1,8

6)†

Sym

ptom

sD

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ION

OF

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to 1

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to 1

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319

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8)45

1(4

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4-6

115

(23)

232

(24)

1,28

(1,0

1 to

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4)†

7-9

81(1

6)12

6(1

3)1,

80

(1,1

2 to

1,3

2)†

1-3

190

(38)

451

(48)

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611

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3)23

2(2

4)1,

28(1

,01

to 1

,64)

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981

(16)

126

(13)

1,80

(1,3

2 to

2,4

6)†

10-1

227

(5)

41(4

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76(1

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to 3

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†>1

287

(17)

98(1

0)2,

12(1

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to 2

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igns

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2 to

2,4

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10-1

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(5)

41(4

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to 3

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†>1

287

(17)

98(1

0)2,

12(1

,51

to 2

,98)

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Num

ber

of a

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aus

culta

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find

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4)2,

53(2

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to 3

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†0

216

(43)

729

(77)

11

128

(26)

129

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Num

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of a

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tory

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53(2

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to 3

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†0

216

(43)

729

(77)

11

128

(26)

129

(14)

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(2,5

0 to

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298

(20)

60(6

)6,

85(4

,26

to 1

1,02

)†

349

(10)

27(3

)11

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(6,0

6 to

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99)

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9(2

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(0)

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to 6

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(20)

60(6

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85(4

,26

to 1

1,02

)†

349

(10)

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(6,0

6 to

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99)

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25,7

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(0,7

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-65

71(1

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(10)

164

-55

210

(42)

432

(46)

0,67

(0,4

1 to

1,0

9)54

-45

202

(40)

364

(38)

0,74

(0,4

5 to

1,2

1)4474

-65

71(1

4)98

(10)

164

-55

210

(42)

432

(46)

0,67

(0,4

1 to

1,0

9)54

-45

202

(40)

364

(38)

0,74

(0,4

5 to

1,2

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17(3

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98(1

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(11)

98(1

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51-1

0018

2(3

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7(5

6)0,

62(0

,38

to 1

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101-

150

189

(38)

219

(23)

1,36

(0,7

6 to

2,4

3)15

1-20

048

(10)

86(9

)1,

26(0

,58

to 2

,71)

51-1

0018

2(3

6)52

7(5

6)0,

62(0

,38

to 1

,03)

101-

150

189

(38)

219

(23)

1,36

(0,7

6 to

2,4

3)15

1-20

048

(10)

86(9

)1,

26(0

,58

to 2

,71)

>200

25(5

)18

(2)

2,35

(1,5

9 to

3,4

9)†


63

Tab

le3

cont

inue

d.C

rude

odd

sra

tioP

resc

ribed

antib

iotic

sN

ot p

resc

ribed

antib

iotic

s(9

5% C

I)(2)

GP

s’ c

hara

cter

istic

sA

VE

RA

GE

NU

MB

ER

OF

HO

ME

VIS

ITS

PE

R W

EE

K1,

02(1

,01

to1,

03)

†A

VE

RA

GE

NU

MB

ER

OF

HO

ME

VIS

ITS

PE

R W

EE

K (

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Nat

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Chapter IV

64

Figure 2 The relation between the effect of physicians’ perception of patients’ requests on antibiotic prescribing for acute cough and the significant confounders of this relation. Adjusted odds ratios and 95% confidence limits.

0,001 0,01 0,1 1 10 100 1000

Investigating infection parameters

Request for antibiotics

Aspiration risk

# abnormal ausculatory findings

Sputum

Impression of sickness

Chestpain

Headache

Physician's year of birth

Physician's practice location

Antwerp (reference)

Brussels

Limburg

West Flanders

East Flanders

Spirometer

Professional training

Referral


65

Study limitations

It is possible that the results are biased due to the recruitment, non-response and response quality of the GPs. The GPs recruited, however, did not differ from the other 64 GPs approached for this study nor from the other 108 GPs responding in the questionnaire study in terms of age, university of graduation, the number of GPs and general practitioners in professional training (GPPTs) in the practice, the number of GPs rewarded fee for service, and the average number of patient encounters per week. Although among the participants there was a higher proportion of males (63/85 vs. 36/64: p=0.02, vs. 64/108:p=0.03 respectively), their age and gender distribution is similar to national averages. Furthermore, in terms of all recorded characteristics, the GPs who included the 1448 patients eligible for analysis did not differ from the other GPs willing to participate in the cRCT (n=13) nor did those with differ from those without patients in the final model.

Patient characteristics might also influence the results of this study. Face-to-face interviews of two samples of about 1000 people representative of the population over fourteen also that showed about fifteen percent of the respondents would request the GP for an antibiotic in Belgium (www.health.fgov.be/antibiotics/cabn.htm). There were no differences in the patients’ characteristics between those records included in the analysis (n=1448) and those records eligible for the cRCT15 (but excluded here because of incomplete data for the GP’ s perception of the patient’ s request for an antibiotic), or between those records included and those left out of the final model. Furthermore, the crude odds ratio (95 % CI) for all eligible patients (N = 1448) and that of all patients with complete information (N = 819) are 4.64 (2.96-7.26) and 4.60 (2.59-8.17), respectively, suggesting there is no bias due to the selection of patients with complete information in the final model.

There was no formal assessment of either the internal validity or the reliability of the pre-printed forms; rather, they were assumed acceptable as they had been developed based upon our focus group study9 and questionnaire study.14 Self-reporting might have limited our data as well, by underestimating the importance of the non-medical reasons. Still, our data show that a non-medical reason is independently associated with increased prescription of antibiotics.

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Acute cough

Knowledge about the determinants that play an important role in clinicians’ decisions to prescribe antibiotics for respiratory infections is useful in designing interventions to decrease inappropriate antibiotic prescribing.27 For this study, we chose to include patients with acute cough. Although it is the most frequent complaint in general practice there is much uncertainty as to the diagnosis and treatment of patients with an acute cough. Surprisingly little evidence is available to support decisions concerning these patients in daily practice.28 It is therefore not surprising that diagnostic labels such as acute bronchitis are used inconsistently in general practice.29 To avoid misclassification, rather broad definitions such as ‘lower respiratory tract illness’ are used in patients with an acute cough.30 When applying the criteria described by Hopstaken31 to our data, it was found that 624 acute cough patients (43%) had a lower respiratory tract infection (LRTI). Even more patients met the criteria described by Holmes and MacFarlane30 32 (n=1112 (77%). In about 60% of patients with a LRTI requesting for an antibiotic the lung auscultation was normal or revealed only one abnormal finding. And the effect of requesting an antibiotic on the prescription of antibiotics did not differ between patients with or without a LRTI. This suggests not only that our findings also apply to patients with a LRTI as defined in the literature, but also that choosing to study patients with acute cough is more than justified. After all, there is only little agreement between the classification of patients with acute cough when applying the above criteria to define patients with a LRTI.

Non-medical reasons

Other non-medical reasons have been shown to affect prescribing behaviour of GPs as well, such as patient expectations 33 34 and, to a greater extent, GPs’ perception of patient expectations.35 36 However, when adjusting for medical reasons associated with the prescription of antibiotics, non-medical reasons have not until now been shown to determine GPs prescribing of antibiotics.27 In this study we aimed to obtain a valid estimate of the effect of GPs’ perception of patients’ requests for an antibiotic on their prescribing antibiotics to adult acute cough patients. We used a hierarchical backwards elimination procedure, starting with interaction assessment.16 Only one interaction term was retained in the final model for a clear interpretation of the estimate of X. The more conservative model contained seven interaction terms. It would seem


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that the only meaningful description of these results is that the lower the number of auscultatory findings the more a perceived request favours antibiotic prescribing. In previous studies we also found that a positive lung auscultation in itself was associated with antibiotic prescribing9 and that diagnostic uncertainty influenced the complex decision-making process.14 The results of this study support these findings and contribute to the understanding of the prescription decision. After all, it sounds sensible that more abnormal auscultatory findings provide GPs with more certainty regarding the need of an antibiotic, and vice versa. Antibiotics are thus prescribed for medical reasons if these are available, but when GPs have to deal with diagnostic uncertainty non-medical reasons favour antibiotic prescribing. This can also be attributed to the so-called chagrin factor.9 37 In the present study GPs consider it less appropriate not to prescribe antibiotics when a patient requests them since this causes more chagrin, even if the evidence shows that the limited benefit for patients with acute (productive) cough is outweighed by the side effects,2 3 and the medicalising effect, the financial costs and the effect on antimicrobial resistance.6

Optimising the prescription of antibiotics

A good clinical practice guideline and an intervention to optimise antibiotic prescribing for acute cough in Flemish general practice have taken non-medical reasons into account. We performed a multifaceted intervention, including educational outreach visits (academic detailing),38 to implement a guideline for acute cough,15 since this might be most effective.39 40 Planning other cluster-randomised trials on this topic one should take into account an intra-cluster correlation coefficient of 0.20 to adjust power calculations.

Conclusion

This study enabled us to obtain a valid estimate of the effect of GPs’ perception of patients’ requests for antibiotics on the prescription of antibiotics and confirmed our focus group study and questionnaire study findings, i.e. that GPs’ decisions to prescribe antibiotics are determined by both medical and non-medical reasons.9 14 Hence, good clinical practice guidelines and interventions to optimise antibiotic prescribing have to take into account non-medical reasons in the prescription of antibiotics.

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References



3. Smucny J, Fahey T, Becker L, Glazier R, McIsaac W. Antibiotics for acute bronchitis. In: The Cochrane Library, Issue 4, 2002. Oxford: Update Software.


5. Koninklijke Academie voor Geneeskunde van België [Belgian Royal Academy for Medicine]. Advies inzake het overgebruik van antibiotica [Advise concerning the overuse of antibiotics]. Tijdschr Geneesk 1999;55:173-4.


7. Coenen S, Van Royen P, Denekens J. Diagnosis of Acute Bronchitis [letter; see reply]. J Fam Pract 1999;48:741-2.





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11. Zaat J, Stalman W, Assendelft W. Hoort, wie klopt daar? Een systematische literatuurstudie naar de waarde van anamnese en lichamelijk onderzoek bij verdenking op een pneumonie [Listen, who is knocking? A systematic review on the value of history and physical examination in case of suspected pneumonia]. Huisarts en Wetenschap 1998;41:461-9.



14. Coenen S, Michiels B, Van Royen P, Van der Auwera J-C, Denekens J. Antibiotics for coughing in general practice: a questionnaire study to quantify and condense the reasons for prescribing. BMC Fam Pract 2002;3:16 (10p).


16. Kleinbaum D. Logistic regression: A self-learning text. New York: Springer-Verlag Publisher, 1994.

17. Fine M, Auble T, Yealy D, Hanusa B, Weisfeld L, Singer D, et al. A prediction rule to identify low-risk patients with community-acquired pneumonia. NEJM 1997;336:243-50.

18. SAS System for Windows [program]. 8.02 version. Cary, NC: SAS Institute Inc., 2001.

19. Wears R. Advanced statistics: Statistical methods for analyzing cluster and cluster-randomized data. Acad Emerg Med 2002;9:330-41.

20. Liang K, Zeger S. Longitudinal data analysis using generalized linear models. Biometrika 1986;73:13-22.

21. Ridout M, Demétrio C, Firht D. Estimating intraclass correlation for binary data. Biometrics 1999;55:137-48.

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22. Rotnitzky, Jewell. Hypothesis testing of regression parameters in semiparametric generalized linear models for cluster correlated data. Biometrika 1990;77:485-97.

23. Pan W. GOF tests for GEE with correlated binary data. Scan J Stat 2002;29:101-10.

24. Barnhart, Williamson. GOF tests for GEE modelling with binary responses. Biometrics 1998;54:720-9.

25. Horton. GOF for GEE: an example with mental health service utilisation. Stat Med 1999;18:213-22.

26. Hosmer DJ, Lemeshow S. Applied logistic regression. New York, NY: John Wiley & Sons, 1989.

27. Dosh S, Hickner J, Mainous AI, Ebell M. Predictors of antibiotic prescribing for nonspecific upper respiratory tract infections, acute bronchitis, and acute sinusitis. J Fam Pract 2000;49:407-14.

28. Verheij T. Diagnosis and prognosis of lower respiratory tract infections: a cough is not enough. Br J Gen Pract 2001;51:174-5.

29. Hueston W, Mainous Ar, Dacus E, Hopper J. Does acute bronchitis really exist? J Fam Pract 2000;49:401-6.

30. Holmes W, Macfarlane J, Macfarlane R, Hubbard R. Symptoms, signs, and prescribing for acute lower respiratory tract illness. Br J Gen Pract 2001;51:177-181.

31. Hopstaken R, Nelemans P, Stobberingh E, Muris J, Rinkens P, Dinant G. Is roxithromycin better than amoxicillin in the treatment of acute lower respiratory tract infections in primary care? A double-blind randomized controlled trial. J Fam Pract 2002;51:329-36.

32. Macfarlane J, Holmes W, Gard P, Macfarlane R, Rose D, Weston V, et al. Prospective study of the incidence, aetiology and outcome of adult lower respiratory tract illness in the community. Thorax 2001;56:109-114.


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38. Coenen S, Van Royen P, Michels J, et al. Aanbeveling voor goede medische praktijkvoering: Acute hoest [Good Clinical Practice Guideline: Acute Cough]. Huisarts Nu 2002;31:391-411.

39. Wensing M, van der Weijden T, Grol R. Implementation guidelines and innovations in general practice: which interventions are effective? Br J Gen Pract 1998;48:991-7.

40. Gross P, Pujat D. Implementing practice guidelines for appropriate antimicrobial usage: a systematic review. Med Care 2001;39(8 Suppl 2):II55-69.

Guideline Acute Cough is published in Huisarts Nu 2002;31:391-411. 73

V


A clinical practice guideline

In Belgium, clinical practice guidelines are developed and disseminated since 1996. Clinical practice guidelines are ‘systematically developed statements to assist practitioner and patient decisions about appropriate health care for specific clinical circumstances’ .1 The main goal of guidelines is to improve the practice and outcome of medical care by reducing inappropriate variations in practice.2 Up to now the Scientific College for Flemish General Practitioners (WVVH) has produced 16 guidelines, including the guideline for acute cough. These guidelines are available on the WVVH website (www.wvvh.be). In this chapter we will present the standardized methodology defined by the WVVH according to which we developed the guideline for acute cough as well as the key messages of the resulting guideline.

The development of clinical practice guidelines by the WVVH follows a step-by-step methodology.1 3 First, the topic of the guideline is chosen and described. Developing guidelines is time and money consuming. The available means therefore are reserved primarily for the most relevant topics, namely the major causes of morbidity and mortality in the population. Since the guidelines of the WVVH are primarily meant to assist general practitioners, topics relevant for primary care are chosen. Furthermore, the aim of guideline development is to improve quality of care, reduce inappropriate variations in

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practice and improve cost effectiveness. The description of the topic entails a clear description of the targeted problem, and of the objectives of the guideline.

Second, a literature search is performed to collect the available evidence on the problem. The search for evidence must be systematic and the results critically appraised. The first step is looking for existing guidelines. Afterwards meta-analyses, systematic literature reviews (Cochrane reviews) and controlled studies are looked for.

Third, an author group is composed. Guidelines are ideally developed by a multidisciplinary team, which can also include patients, if necessary. A team manager keeps an eye on the group's process while the different authors can concentrate on the development of the guideline itself. This author group make a draft guideline in which the guideline recommendations are formulated clearly and precisely. For each of the key messages the corresponding level of evidence is stated. Three levels of evidence are described for that purpose, with level 1 for definite evidence, level 2 for likely evidence, and level 3 for an indication for evidence.4 The level of evidence depends on the quality of the individual studies and it is applicable for management decisions other than treatment.

Fourth, the draft guideline is evaluated by external experts, i.e. not part of the author group. Specialists and GP’ s can be asked to fulfil this important task. These experts look at the guideline from a scientific point of view and they can formulate remarks if these are evidence based and reference to the evidence is provided. After this evaluation procedure, all authors come together and follow a strict consensus procedure to decide about all comments and remarks.

Fifth, the feasibility of the guideline is evaluate in local groups of GPs. It is a peer review process with patient cases, critical reading of the guideline and feedback from the participating GPs own practical experience. A local moderator as well as some of the authors should be present. Also after this evaluation procedure, the comments and remarks are taken into account into a final version, after a consensus procedure.

Sixth, the current version of the guideline is validated. The validation committee, which consists of representatives of the four Flemish universities, the SCGFP, and local groups of GPs, gives the final evaluation and validation of the guideline. The task is limited to the appraisal of the guideline with


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respect to the described methodology. The international AGREE-instrument is a good basis for this appraisal.5

The final version of the guideline is published in the journal of the WVVH, Huisarts Nu, and, together with annual follow-up reports, available on the WVVH website.

To improve the quality of care, reduce inappropriate variation in practice and improve cost-effectiveness, we decided to make a guideline for the management of acute cough in general practice. Antibiotics are being over prescribed in general practice, especially for respiratory tract infections. Acute cough is one of the most frequent reasons for consulting in general practice (for respiratory tract infections). Overuse of antibiotics for respiratory tract infections wastes resources (both for the unnecessary drugs themselves and the subsequent visits6) and increases resistance.7 8 Whether to prescribe an antibiotic for acute cough or other respiratory complaints is a common dilemma in primary care. The precise diagnosis is often unclear.9-11

Hence for the guideline for acute cough we aimed to formulate recommendations for the diagnosis of the causes of acute cough and for the treatment in case of respiratory infections with acute (productive) cough, pneumonia excluded. Levels of evidence are provided for each of the recommendations.

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Diagnosis

The guideline used for the intervention recommends a clinical and stepwise approach to diagnose the cause of acute cough in patients aged greater than 12 years who complain about acute cough with or without purulent sputum that have not been treated in the preceding week with antibiotics, not patients known to have chronic obstructive pulmonary disease or a chronic cough (= more than 30 days).

First conditions such as pneumonia, pulmonary embolism, left ventricular failure (pulmonary oedema), pneumothorax, aspiration and irritation by toxic agents should be ruled out by means of history and clinical examination. Although these are not frequent conditions, and although acute cough may not be the most prominent complaint, these conditions are treatable, and possibly life-threatening. They should not be missed. (level of evidence 3)

In case of clinical suspicion of pneumonia patient at low risk for mortality or complications can be identified by means of history and clinical examination. This risk determines the place of treatment (level 2). Treating these patients at home with antibiotics is justified, ideally this decision is documented with a positive chest X-ray. (level 3)

If another cause than a respiratory infection is present (for example asthma, gastro-esophagial reflux disease, ACE-inhibitors) management needs to be adjusted accordingly. Even though such conditions may not be obvious in a first encounter, it is worthwhile to take them into account. (level 3)

If finally a respiratory infection seems to be the most likely cause, it is not feasible to distinguish between viral and bacterial infections. (level 2) Furthermore this differentiation is not meaningful for the therapeutic decision. (level 3)


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Treatment

In case of respiratory infections with acute (productive) cough, pneumonia excluded, antibiotics have no effect on the (duration of the) productive cough and limitation of work or other activities. Of each ten patients after seven to eleven days more than eight are clinically improved regardless the use of an antibiotic. Less than one patient extra improves due to the antibiotic, but as many patients experience the side effects. (level 1)The possible benefits of antibiotics are outweighed by their harm. Antibiotics are justified only in case of compromised immunity. (level 3)

We recommend to explicitate patient expectations, to reassure patients and inform them about the cause and duration of the complaints, to explain why antibiotics are not necessary, and to instruct patients when they should reconsult. (level 3)

The effectiveness of over-the-counter medicines is unclear. For the symptomatic treatment an antitussivum (dextromethorphan) or an expectorans (guaifenesine) can be prescribed. (level 3)

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References

1. Buntinx F. Een standaard der standaarden [A guideline for guidelines]. Huisarts Nu 1996;25:13-6.

2. Van Royen P. Aanbevelingen in de praktijk. Bedreiging voor vrijheid van diagnose en therapie [Guidelines in practice. A threat to freedom of diagnosis and treatment]? Huisarts Nu 1998;27:207-10.

3. Van Royen P, Coenen S, Denekens J, Dieleman P, Michels J. From practice guidelines to implementation of good clinical practice. A Flemish guideline for acute cough and rational antibiotic use in general practice [abstract]. Eur J Gen Pract 2001;8:104.

4. Van Royen P. Niveaus van bewijskracht: levels of evidence. Huisarts Nu 2002;31:54-7.

5. The AGREE Collaboration. AGREE Instrument. Available at: http://www.agreecollaboration.org. Accessibility verified December 1,2001.

6. Little P, Gould C, Williamson I, Warner G, Gantley M, Kinmonth AL. Reattendance and complications in a randomised trial of prescribing strategies for sore throat: the medicalising effect of prescribing antibiotics [see comments]. BMJ 1997;315:350-2.




10. Coenen S, Van Royen P, Denekens J. Diagnosis of acute bronchitis [letter; see reply]. J Fam Pract 1999;48:471-2.

11. Hueston W, Mainous Ar, Dacus E, Hopper J. Does acute bronchitis really exist? J Fam Pract 2000;49:401-6.

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VI


Cluster randomised controlled trial of a tailored professional intervention to optimise prescribing

Introduction

In primary care antibiotics are being overprescribed, especially for respiratory infections.1 2 This is also true for the Netherlands3 with the lowest antibiotic consumption in the European Union: 9 defined daily doses per 1000 inhabitants per day.4 The problem is particularly important for countries such as the UK with a consumption being twice, or Belgium with a consumption of nearly three times that of the Netherlands.4 After all antibacterial resistance is linked with the antibiotic consumption,5 and it is time for action.6

Decreasing the use of antibiotics has been among the most targeted issues of different strategies to improve the use of medicines. Regulatory/financial measures,7 organisational interventions,8-10 and professional interventions can be distinguished. Professional interventions use primarily evidence-based arguments on effectiveness, safety, cost and sometimes applicability for changing professional practice. Implementing evidence-based guidelines is one of the most known, and best studied examples of this approach. Most studies however were done in the US, and many targeted hospital prescribing rather than primary care prescribing.11 Nevertheless, in some studies a considerable

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decrease of antibiotic use was seen using a multifaceted intervention to implement guidelines for appropriate antimicrobial usage.12

Specific barriers to change occur at the level of the social context and at the broader context of the health care structure and culture. In Belgium most GPs are paid fee for service. There is a plethora of mostly solo practicing GPs, competition for patients and open access to secondary care. In contrast to the Netherlands pharmacotherapy is not discussed on a regular basis in local groups involving pharmacists. Furthermore, there are cultural differences and different attitudes towards respiratory symptoms and antibiotics between Belgium and the Netherlands. All of which may partly explain the large variation in antibiotic consumption between both countries.13 14

Other barriers to change relate to the credibility of the guideline and to the individual prescriber. Though most GPs are aware of the problem of antibiotic resistance at population level, there may be lack of awareness of the effect of overprescribing in individuals on the probability of future infections with resistant pathogens. Internal barriers within the prescriber relate to knowledge, attitude, but also to the decision process when prescribing an antibiotic. We looked at the antibiotic prescribing decision of Flemish GPs in patients with complaints about coughing, not patients with acute bronchitis.15 Using qualitative and quantitative research methods we found non-medical reasons played an important role in the prescribing decision, especially in case of diagnostic uncertainty.16 17 Moreover, they favoured antibiotic prescribing. Despite lacking evidence for their effectiveness18 19 GPs anticipated more 'chagrin' over not prescribing antibiotics than over prescribing them anyway, since antibiotics might prevent them from loosing patients as a result of unfulfilled patient expectations or undetected serious disease.

To optimise antibiotic prescribing in our country, we developed a context specific evidence based guideline for acute cough. The main recommendation is that most patients with acute cough do not need antibiotics. Although no single combination of approaches is clearly better than the other to implement guidelines, we preferred the individual approach of academic detailing, and tailored the intervention to identified barriers within GPs.


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A cluster randomised controlled trial was conducted to assess the effectiveness of a tailored professional intervention to support the implementation of a clinical practice guideline for the management of acute cough on antibiotic prescribing in adult patients with acute cough in general practice.

Methods

Design

We tested the main hypothesis with a cluster randomised pre-test-post-test controlled trial (cRCT). General practitioners (GPs) were randomised before the pre-test in an intervention group and a control group (Figure 1). Our intervention was preceded by a national public campaign.20 21 Only the GPs in the intervention group received a tailored intervention to support implementing a clinical practice guideline for the management of acute cough in adult patients. Pre-test data were collected during a three month period in 2000, post-test data one year later, in 2001, after both interventions.

Participants

In total 149 GPs not reluctant to take part in further study on the topic at the time of the postal questionnaire study17 were sent a letter and questionnaire inviting them to join the study. Overall, 85 GPs agreed to participate and were randomised. After sorting the questionnaire data by gender, university of promotion, and age all even records were allocated to one group, all uneven to another. After making sure GPs from the same practice ended up in the same group, tossing a coin decided which group would serve as intervention group. We included consultations for acute cough if they concerned immuno-competent patients, 18-65 years, with new or worsening coughing, present for less than 30 days as (one of) the most important complaint(s) and as the reason for first encounter at the GPs practice.

The involvement of GPs and patients in the trial is summarised in Figure 1.

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Interventions

Apart from our intervention all participating GPs received booklets and leaflets of a public campaign initiated in Belgium in November 2000 and continued until December 2000 (Figure 1).20 21 This campaign also included TV spots and radio messages informing the public on overconsumption and misuse of antibiotics, the resulting resistance problem and the self-limiting character of most frequent infections in the community. All GPs were invited to participate in the cRCT before the pre-test, reminded of the trial before the post-test by mail, and received a fee of � 24.79 or � 61.97 after each study period depending on their response. After an appointment was made by telephone they received the material and instructions for data-collection by means of a practice visit and a reminder phone call at the start of each registration period. Before the post-test period GPs in the intervention group received our tailored professional intervention (Figure 1), consisting of a clinical practice guideline for the management of acute cough in general practice, an educational outreach visit to GPs based on the principles of academic detailing,22 and a postal reminder of the key messages (Box 1).

An author group of GPs developed a clinical practice guideline according to a standardised methodology defined by the Scientific College of Flemish General Practitioners and in line with the AGREE criteria.23 Fine tuning for the specific context of Flemish GPs was based on previous descriptive studies on the management of acute cough and the determinants of antibiotic prescribing.16 17 The guideline for the intervention was reviewed by a multidisciplinary panel of experts. An educational package was developed in accordance with this guideline and key messages were formulated (Box 1).

Before the post-test all GPs in the intervention group received the guideline by mail and a telephone call. Each time GPs were asked to read the guideline in anticipation of an outreach visit at their practice delivered by one of two trained facilitators. The facilitators, not GPs, combined the educational visit with the material and instructions delivery. They rephrased the information in the guideline using simple overheads and emphasising the key messages. The educational element of this method was a dialogue on perceived barriers to adhering to the guideline.


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Figure 1 GP and patient flow, and design of the study

149 GPs invited to join the study

85 GPs agreed to participate

randomised

42 GPs in intervention group 43 GPs in control group

64 declined

Pre-Test Period: February-April 2000

Post-Test Period: February-April 2001

Consulation data (GPs)35 GPs respondno response from 8 GPs b median (ICQ) cluster size 13(9,18) a

Consultation data (GPs)36 GPs respondno response from 6 GPsmedian (ICQ) cluster size 10(4,15) a

Consultation data (patients)485 eligible for recruitment (100%) a 445 included (92%) a 365 eligible for analysis c (75%) a


Consulation data (GPs)32 GPs respond d

no response from 11 GPs e

median (ICQ) cluster size 14(7,16) a

Consultation data (GPs)27 GPs respond d

no response from 15 GPs e

median (ICQ) cluster size 10(5,16) a



Patient diaries243/365 patients responded (67%) a




Belgian public campaign: Decembre 2000 (http://www.red-antibiotica.org/english/index.html)

Intervention: January 2001

a: The proportions of patients eligible for recruitment (100%) actually included in the study, the proportions of those eligiblefor analysis c, and the proportion of the latter patients responding with patient diaries, as well as the median cluster sizes were notsignificantly different between the study groups within each study period, nor between the study periods within each study group usingGeneralised Estimating Equations and Kruskal Wallis Median Test respectively.b: 1 GP responding in the Pre-Test did not have consultation data eligible for analysis c.c: Analysis of the main outcome measures, differences in antibiotic prescribing ratesd: Only 27 GPs in the intervention and 29 GPs in the control group responded in both the Pre-Test and the Post-Teste: In the intervention group 9 GPs responding in the Pre-Test did not respond in the Post-Test, compared to 6 GPs in the controlgroup. In the control group 3 GPs not responding in the Pre-Test did so in the Post-Test.

c

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The focus of this dialogue however was on dealing with barriers within the individual prescriber, especially in dealing with diagnostic uncertainty. Using a fishbone scheme we presented what was known about the accuracy of history and clinical examination to differentiate between viral and bacterial respiratory infections, upper and lower respiratory infections, and between bronchitis and pneumonia,24 25 about the validity of a clinical prediction rule to assess prognosis in case of community-acquired pneumonia,26 about the effectiveness of antibiotics for acute cough,18 and about the effect of antibiotic consumption on bacterial resistance in the community and the individual,27 28 to conclude that after ruling out pneumonia patients with acute cough due to a respiratory infection do not need antibiotics. After all possible benefits of antibiotics are outweighed by their cost, and it is not possible to identify those patients who will benefit from antibiotics. Nevertheless, the guideline also recommended amoxicillin or doxycyclin as first choice antibiotics if for any reason the GP decides to prescribe antibiotics. We addressed the effect of patient and physician related non-medical reasons on the prescribing decision, especially in case of diagnostic uncertainty, as well. We demonstrated the mismatch between patients' expectations and GPs perceptions of these, stressing the latter are described as important determinants favouring antibiotic prescribing,29-31 and we instructed the GPs on how to make patients' expectations regarding antibiotic prescribing explicit and provided different strategies for different patient expectations. To overcome an uncomfortable prescribing decision due to GP related reasons, we stated that watchful waiting will prevent complications more effectively than antibiotics, and will not jeopardize the doctor-patient relationship. We thus tried to show that managing patients according to the guideline might result in a win-win situation, more satisfied GPs, more satisfied patients, and less antibiotic consumption. We thus tailored the interventions to overcome identified barriers.

Before the post-test all intervention GPs also received one page with the key messages of the guideline by mail as reminder (Box 1).

Our intervention was initiated in December 2000 and continued until January 2001. The study protocol was approved by the local research ethics committee. Consent was obtained from GPs and patients.


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Box 1 Key messages of the guideline for acute cough

This guideline concerns patients, aged 12 years or older, whose most prominent complaint is acute cough with or without purulent sputum, not patients with recurrent or chronic cough, chronic obstructive pulmonary disease or patients that have been treated in the preceding week with antibiotics.

First, pneumonia, pulmonary embolism, left ventricular failure (pulmonary oedema), pneumothorax, aspiration and irritation by toxic agents should be ruled out by history and clinical examination. Although these are not frequent conditions, and although acute cough may not be the most prominent complaint, these conditions are treatable, and possibly life-threatening. They should not be missed.

If another cause than a respiratory infection is present (for example asthma, gastro-oesophageal reflux disease, ACE-inhibitors) management needs to be adjusted accordingly. Even though such conditions may not be obvious in a first encounter, it is worthwhile to take them into account.

If finally a respiratory infection seems to be the most likely cause, it is not feasible to distinguish between viral and bacterial infections. Nevertheless the decision whether to prescribe antibiotics has to be made. Antibiotics are only needed for patients with compromised immunity.

Besides the scientific arguments, we also recommend to integrate the GP’s own agenda as well as that of the patient in the final therapeutic decision.

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Data

GPs were asked to collect medical (demographics, medical history & risk, circumstances of the consultation, symptoms, signs, test ordering and prescriptions) as well as non medical data (e.g. GPs workload at the time of the consultation) in 20 consecutive patients eligible for recruitment. If, due to time constraints, this was not possible, one in two or one in three patients were to be included. The GPs kept records of those patients eligible for recruitment but not included. They collected the data themselves on pre-printed forms, with clear instruction about how this should be done. To ensure patient confidentiality, GPs completed the forms using patient identification numbers only. GPs were also asked to deliver a package, containing a symptom diary and clear instructions for its use, to all included patients. Patients were asked to record their symptoms and medication consumption starting the day of the consultation for 29 days or for as long as appropriate. Each diary also contained an identification number and was to be returned to the GP in a sealed envelope. The GPs held a patient reference sheet with names of patients against those numbers. This enabled them to assess and improve their patients' response. They sent all completed data collection material to SC for analysis. The data collection method had been previously piloted. We compared data from control with data from the intervention group in each study period, and data from the pre-test period, February-April 2000, with data from the post-test period, February-April 2001 in each study group.

Outcomes

The primary outcome was the antibiotic prescribing rate by GPs for adult patients with acute cough. We were also interested in the kind of antibiotics prescribed, if any, and whether any change in antibiotic prescribing affected symptom resolution. Finally, we measured the medication cost per patient from the perspective of the National Sickness and Invalidity Insurance Institute (NSIII). We expected that implementation of the guideline would reduce the proportion of patients who were prescribed antibiotics for acute cough, increase the relative proportion of first choice antibiotics, and that this would not affect patients' symptom resolution.


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Sample size

Sample size was calculated with antibiotic prescribing for acute cough as primary outcome. Before the pre-test no data were available regarding antibiotic prescribing rate for acute cough nor about the intracluster correlation coefficient (ICC) needed to adjust the sample size because GPs rather than patients were randomised. Therefore we calculated the sample size with a method that takes into account the number of events, the expected effect, and the power of the study, but not the ICC. We thus acted as if patients were randomised, and assumed a minimum of 20 patients for each practice and a worst case control group rate of 50%. Under these assumptions we anticipated a power of 90% to detect a difference of 10% in rates between the two groups at the 5% significance level with 30 practices in each study group. We anticipated adjustment of the sample size for cluster randomisation and loss to follow up. Therefore we planned to randomise 40 GPs in each group and to adjust the number of patients to be included per practice for the post-test according to the ICC found in the pre-test.

Statistical methods

We applied cluster specific methods taking into account the dependence among patients of the same GP, known as the clustering effect: GPs rather than patients were randomised, and variance in how patients were managed would be partly explained by the GP.32 We used logistic regression to test for an effect of our intervention on antibiotic prescribing (Box 2). To test for differences in medication cost a linear regression model with random intercept was used to account for within-GP correlation. To test for differences in time to symptom resolution we used Cox's proportional hazard regression. Data were analysed assuming independence and standard errors were then corrected for within-GP correlation using a robust estimator. All models were estimated with SAS v8.02.33 All other analyses were done with Statistica v6.0.34

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Box 2 Analysis of cluster data

To assess the effect of a tailored intervention on GPs' antibiotic prescribing for acute cough, we first estimated a logistic model: logit p(X) = �0 + �1 G + �2 P + �3 G*P, where p(X) is the probability of an antibiotic prescription, G is a dichotomous variable for the study groups, which equals zero for the control and one for the intervention group, P is a dichotomous variable for the study period, which equals zero for the pre-test and one for the post-test. The same kind of model was used to test for significant differences of the covariates. All significant covariates in this analysis were included in the above model as possible confounders. Then from this multivariable analysis non significant covariates were removed, eliminating one by one the covariates with least significant type 3 score statistics. By testing the hypothesis H0:�1=0 we were able to test for differences between control and intervention group during pre-test. Second, we considered the model without the effect of the study group, forcing antibiotic prescribing rates to be equal in both study groups during the pre-test, an assumption which should hold with randomisation. Under this assumption we were tested for differences between control and intervention group during the post-test by testing the hypothesis H0: �3=0. By testing the hypothesis H0:�2+�3=0 we were able to test for differences between pre-test and post-test in the intervention group. By testing the hypothesis H0:�2=0 we were able to test for differences between pre-test and post-test in the control group. We adjusted logistic regression estimates for clustering within our data (patients are nested within GPs).32 We used generalized estimating equations (GEE).35 Using GEE we can also provide an order of magnitude for the intra-cluster correlation coefficient (ICC) �. For significance testing of the ICC estimate we used alternating logistic regression (ALR), a technique closely related to GEE. With ALR, estimating equations are specified for marginal and association parameters. The association between pairs of responses is measured by log odds ratios (�), instead of correlations (�) as with GEE. The ICC � in GEE is related to � in ALR.36


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Results

GP flow & characteristics

The randomised GPs were similar to the other Flemish GPs (invited) with respect to age and sex distribution. They all received the material and instructions for data collection. Six GPs in the intervention arm and seven GPs in the control arm did not respond in the pre-test period (Figure 1). We did not get data eligible for the analysis of the main outcome measures from one control GP. This left 36 of 42 GPs in the intervention arm and 35 of 43 GPs in the control arm for the pre-test. These 36 GPs in the intervention arm received the entire intervention. Nine GPs in the intervention arm and six GPs in the control arm did not respond in the post-test. Thus 27 GPs in the intervention arm and 29 GPs in the control arm responded in both the pre-test and the post-test. Three GPs were recovered for the post-test in the control arm. This left 27 of 42 GPs in the intervention arm and 32 of 43 GPs in the control arm for the post-test.

No significant differences were found between the intervention and control GPs (Table 1), nor between responding GPs and the non-responding group for the same characteristics.

Patient flow & characteristics

Consultation data. The GPs collected data for 1978 patients eligible for recruitment: in the pre-test 485 in the intervention group, 574 in the control group, in the post-test 398 and 521 respectively. (Figure 1). They included 1800 patients in the study (445, 531, 356 and 468 respectively), of which 1503 patients were eligible for analysis of the primary outcome (365, 445, 292 and 401 respectively). Comparing between the four groups - we mean comparing between both study groups within each study period and between both study periods within each study group - the median cluster sizes were similar (Figure 1). Likewise similar proportions of patients eligible for recruitment were actually included in the study, respectively eligible for analysis. The proportions of male patients were not different whether patients eligible for recruitment were included in the study or not. Only in the control group in the post-test the proportion of male patients eligible for recruitment was greater in those eligible for analysis than in those not eligible for analysis. Of the patients

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eligible for recruitment the patients included and those eligible for analysis were younger than those not included, respectively not eligible for analysis. Table 2 shows the characteristics of the patients with acute cough eligible for analysis by study group for the pre-test and the post-test period. Except for risk for thrombo-embolic disease, duration of cough, presence of sputum, of ronchi, of loss of appetite, and of a referral, characteristics of the patients eligible for analysis based on the data collected by the GPs were similar (Table 2).

Patients in the intervention group were less likely to be at risk for thrombo-embolic disease in the pre-test (odds ratio (OR) (95% CI)=0.17 (0.05-0.60) and the post-test (OR=0.15 (0.03-0.79)). They were less likely to produce sputum (OR=0.68 (0.47-0.98)), less likely to be referred (OR=0.23 (0.06-0.68)) and coughing significantly less days before consulting in the pre-test only (estimated difference (ED) (95%CI)= 0.96 (0.12-1.80). In the post-test patients in the control group were coughing significantly less days before consulting compared to the pre-test (ED=0.79 (0.12-1.46)) They were also less likely to produce sputum (OR=0.68 (0.48-0.97)), have loss of appetite (0.60 (0.39-0.93)) or ronchi (0.58 (0.34-1.00)).

Patient diaries. Patient diaries of 1009 patients eligible for analysis were available: in the pre-test 243 in the intervention group, 278 in the control group, in the post test 208 and 280 respectively (Figure 1). Comparing between the four groups the proportion of patients eligible for analysis responding with patient diaries is similar. Except for age, duration of coughing, smoking, ACE-Inhibitors and percussion dullness, the characteristics of the patients eligible for analysis were similar whether patients responded with patient diaries or not. Patients responding with patient diaries were significantly older (estimated difference (95%CI)= 4.00 years (2.57-5.42), and coughing not as long (0.57 days (0.04-1.11) They were more likely to be taking ACE-Inhibitors (OR=3.62 (95% CI=1.17-11.2) and less likely to be smoking (0.57 (0.44-0.73) or have a clinical examination positive for percussion dullness (0.33 (0.15-0.93). Comparing the presence of complaints on the day of the consultation (= day 1) from these patients' diaries between the four group, only for complaints about fever and headache differences were found between the study periods (Table 3). Patients in the control group were less likely to suffer from fever (0.62 (0.43-0.89)) and patients in the intervention group were more likely to suffer from headache (1.64 (1.08-2.48) in the pre-test.


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Table 1 Characteristics of study GPs in intervention and control group(1) Characteristics Intervention GPs Control GPs

N=27 N=29

Figures are numbers (percentage) (2) MEN 19 (70) 20 (69) UA GRADUATES 12 (44) 12 (41) PROFESSIONAL TRAINING 10 (40) 6 (22) FEE FOR SERVICE 26 (96) 28 (97) SINGLE-HANDED 13 (48) 15 (52) GPPTs IN PRACTICE (3) 9 (33) 3 (10) PART TIME 5 (19) 5 (17) PRACTICE IN ANTWERP 15 (56) 21 (72) PEAKFLOW METER 25 (93) 26 (90) SPIROMETER 7 (26) 9 (31) TRAINING PRACTICE 10 (37) 8 (28) ACADEMIC LINK 10 (37) 9 (31) RECORDS OF HOME VISITS 21 (78) 25 (86) COMPUTERISED RECORDS 17 (63) 21 (72) COMPLEMENTARY MEDICINE 1 (4) 1 (3)

Figures are means (standard deviation)

AGE AT START OF THIS STUDY 43.6 (8.3) 45.0 (8.1) PATIENT ENCOUNTERS PER WEEK

100 (43) 108 (43)

HOME VISITS PER WEEK 34 (21) 33 (18) MEDICAL REPRESENTATIVES PER MONTH

16 (11) 15 (11)

ATC J COST RATIO (4) 16.6 (9.0) 14 (6.1) ATC J VOLUME RATIO (4) 3.5 (1.6) 2.9 (1.2) (1) There were no significant differences between the intervention and the control group using chi-

square or Student's t test where appropriate when comparing the characteristics of the GPs responding in the Pre-Test (n=72), of those responding in the Post-Test (n=59) or of those responding in the Pre-Test and the Post-Test (n=56). The latter comparison is presented in this table.

(2) Denominators vary due to missing values (3) General Practitioner in Professional Training (4) The ratios the gross amount for antimicrobials for systemic use (ATC J)/ the gross amount for all

pharmaceutical specialities and the volume (Daily Defined Dosage) DDD)) of ATC J/ the volume for all pharmaceutical specialities are both expressed as percentages on individual prescribing feedback from the National Sickness and Invalidity Insurance Institution (NSIII) to GPs. We asked the participating GPs for these percentages and calculated their mean.

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Table 2 Characteristics of patients with acute cough: consultation data. Figures are numbers (percentage) unless otherwise stated.

PRE-TEST (2000) POST-TEST (2001)

Characteristics Intervention Control Intervention Control n=365 n=445 n=292 n=401 GEE

Demographics MEN 156 (43) 191 (43) 118 (40) 172 (43) NS History & Risk ASTHMA 26 (7) 61 (14) 21 (7) 32 (8) NS COPD (CARA) 27 (7) 39 (9) 23 (8) 30 (7) NS HEARTFAILURE 3 (1) 7 (2) 0 (0) 6 (1) a DK ACE-INHIBITOR 9 (2) 14 (3) 5 (2) 8 (2) NS CV-DISEASE 8 (2) 10 (2) 1 (0) 6 (1) NS ASPIRATION RISK 0 (0) 10 (2) 0 (0) 4 (1) a DK LIVER DISEASE 3 (1) 13 (3) 1 (0) 8 (2) NS RENAL DISEASE 2 (1) 7 (2) 0 (0) 2 (0) a DK NEOPLASTIC DISEASE 3 (1) 9 (2) 2 (1) 4 (1) NS TROMBO-EMBOLIC RISK 5 (1) 39 (9) 3 (1) 25 (6) b,c S SMOKING 119 (33) 158 (36) 80 (27) 135 (34) NS Circumstances HIGH WORKLOAD 196 (54) 242 (54) 153 (52) 243 (61) NS SICK IMPRESSION 158 (43) 197 (44) 112 (38) 171 (43) NS REQUEST AB 37 (10) 88 (20) 27 (9) 66 (16) NS REQUEST MED 175 (48) 216 (49) 163 (56) 180 (45) NS Symptoms SPUTUM 198 (54) 285 (64) 159 (54) 222 (55) b,d S FEVER 94 (26) 149 (33) 64 (22) 114 (28) NS RUNNY NOSE 221 (61) 287 (64) 179 (61) 235 (59) NS HEADACHE 177 (48) 232 (52) 146 (50) 198 (49) NS MUSCLE EACHE 119 (33) 168 (38) 86 (29) 122 (30) NS SOAR THROAT 227 (62) 242 (54) 173 (59) 214 (53) NS WHEEZING 61 (17) 89 (20) 52 (18) 81 (20) NS SHORT OF BREATH 98 (27) 134 (30) 79 (27) 110 (27) NS CHESTPAIN 108 (30) 159 (36) 92 (32) 138 (34) NS LOSS OF APPETITE 99 (27) 130 (29) 62 (21) 82 (20) d S LIMITED ACTIVITY 164 (45) 221 (50) 105 (36) 167 (42) NS Signs ALTERED CONSCIOUSNESS 3 (1) 8 (2) 0 (0) 2 (0) DK PULSE RATE > 125/' 4 (1) 8 (2) 0 (0) 2 (0) DK RESPIRATORY RATE > 30/' 3 (1) 11 (2) 0 (0) 5 (1) DK TEMPERATURE > 38°C 39 (11) 63 (14) 22 (8) 39 (10) NS SYSTOLIC BP<90mmHg 16 (4) 7 (2) 6 (2) 13 (3) NS LESS VESICULAR BREATHING

49 (13) 70 (16) 32 (11) 36 (9) NS

WHEEZING 68 (19) 78 (18) 49 (17) 63 (16) NS RONCHI 95 (26) 118 (27) 71 (24) 70 (17) d NS* CREPITATIONS 18 (5) 32 (7) 13 (4) 26 (6) NS PERCUSSION DULNESS 1 (0) 9 (2) 2 (1) 5 (1) NS


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Table 2 Continued.

PRE-TEST (2000) POST-TEST (2001)

Characteristics Intervention Control Intervention Control n=365 n=445 n=292 n=401 GEE

Investigations RADIOGRAPH 7 (2) 23 (5) 3 (1) 11 (3) NS SPUTUMANALYSIS 0 (0) 12 (3) 1 (0) 4 (1) a DK INFECTIONPARAMETERS 4 (1) 12 (3) 5 (2) 10 (2) NS SEROLOGY 1 (0) 7 (2) 2 (1) 9 (2) NS OTHER 0 (0) 26 (6) 6 (2) 9 (2) a DK Prescriptions REFERRAL 3 (1) 18 (4) 1 (0) 12 (3) b S SICK LEAVE 124 (34) 193 (43) 107 (37) 165 (41) NS FOLLOW UP CONTACT 25 (7) 57 (13) 29 (10) 33 (8) NS MEDICATION 318 (87) 388 (87) 285 (98) 377 (94) NS

PREDICTED MEAN AGE (95% CI)

41,9 (40,3-43,5) 40,9 (39,4-42,4) 40,2 (38,5-42,0) 41,7 (40,1-43,2) NS

PREDICTED MEAN DURATION

OF COUGH (95% CI) 5,6 (4,9-6,2) 6,5 (5,9-7,1) 5,2 (4,6-5,9) 5,7 (5,1-6,3) b,d S FINE a 142 (39) 175 (39) 98 (34) 147 (37) LUNG AUSCULTATION 139 (38) 165 (37) 102 (35) 119 (30) NS

a No estimation possible. To assess differences for these characteristics we

constructed a new variable derived from Fine et al.26, which equals one if the patient’s age > 50 or if the patient has congestive heartfailure, cerebrovascular disease, liver disease, kidney disease or neoplastic disease, or has altered consciousness, pulse rate>125/', respiratory rate>30/', temperature>38°C or systolic blood pressure>90 mmHg, and which equals zero otherwise.

b,c,d,e Significant differences between intervention and control in pre-test (b), or in post-test (c), between pre-test and post-test in control (d), or intervention group (e).

Lung auscultation is a constructed variable which equals one in the presence of less vesicular breathing, wheezing, ronchi or crepitations, and which equals zero otherwise

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Comparing the number of complaints on the day of the consultation patients in the control group suffer from less complaints in the pre-test compared to the post-test (estimated difference (95%CI)= 0.50 (0.04-0.95), and compared to the intervention group (0.52 (0.15-0.90)

Outcome

Outcome data were collected for 1503 consultations for acute cough. The ICC for the primary outcomes was highly significant, indicating that cluster specific analytical methods were appropriate.

Use of antibiotics. Table 4 shows the prescription rate of antibiotics and the percentage difference in change of prescription rates for patients in the intervention and the control group. In the pre-test period antibiotic prescribing rates were not significantly different between the intervention and control group (OR (95% CI) = 1.09 (0.68 - 1.76)); ORadj (95% CI) = 1.28 (0.76 - 2.16), adjusted for duration of cough and presence of sputum). Using the model forcing antibiotic prescribing rates to be equal in both study groups during the pre-test, an assumption which should hold with randomisation, patients in the intervention group were less likely to receive an antibiotic after our intervention compared to controls (ORadj = 0.56 (0.36-0.87)). Also comparing the antibiotic prescribing rate between the pre-test and the post-test, only patients in the intervention group were less likely to receive antibiotics after the intervention (ORadj = 0.56 (0.39-0.81), and not patients in the control group (ORadj = 1.01 (0.76-1.33)).

Kind of antibiotics used. In the pre-test period prescribing rates of recommended antibiotics were not significantly different between the intervention and control group (OR = ORadj = 1.05 (0.52-2.12)). Under the assumption of equal baseline rates, patients in the intervention group were more likely to receive amoxicillin or doxycyclin than patients in the control group (ORadj = 1.90 (0.96-3.75)) (Table 4). Also comparing the antibiotic prescribing rate between the pre-test and the post-test, only patients in the intervention group were more likely to receive the recommended antibiotics after the intervention (ORadj = 1.98 (1.19-3.29)), and not patients in the control group (ORadj = 1.03 (0.61-1.78)).


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Table 3 Characteristics of patients with acute cough: data from patient diaries. Figures are numbers (percentage).

PRE-TEST (2000) POST-TEST (2001) Intervention Control

Intervention Control

Complaints on day 1 n=243 n=278 n=208 n=280 COUGHING 239 (98) 275 (99) 205 (99) 273 (98) SPUTUM 149 (61) 177 (64) 112 (54) 170 (61) FEVER 62 (26) 98 (35) 56 (27) 71 (25) RUNNY NOSE 150 (62) 175 (63) 128 (62) 160 (57) a SOAR THROAT 139 (57) 160 (58) 111 (53) 148 (53) HEADACHE 117 (48) 151 (54) 126 (61) 159 (57) b MUSCLE ACHE 80 (33) 114 (41) 65 (31) 106 (38) LOSS OF APPETITE 89 (37) 110 (40) 74 (36) 97 (35) SHORT OF BREATH 84 (35) 113 (41) 75 (36) 94 (34) WHEEZING 49 (20) 72 (26) 45 (22) 62 (22) CHESTPAIN 87 (36) 108 (39) 65 (31) 95 (34) a,b Significant differences between pre-test and post-test in control (a), or intervention group (b).

Table 4 Rate of use and percentage difference in change of use of (recommended) antibiotics. Intervention Control Use of antibiotics (AB): Pre-Test 43.0 (157/365) 37.8 (168/445) Post-Test 27.4 ( 80/292) 28.7 (115/401) Percentage change -15.6 -9.1 Percentage difference -6.5 ORadj (95%CI)* 0.56 (0.36-0.87) Use of recommended AB: Pre-Test 40.1 (63/157) 37.5 (63/168) Post-Test 53.8 (43/ 80) 37.4 (43/115) Percentage change +13.6 -0.1 Percentage difference +13.7 ORadj (95%CI)* 1.90 (0.96-3.75) * Odds ratios are based on the model assuming equal antibiotic prescribing rates in intervention and control group

in the Pre-Test period, and are adjusted for patient characteristics (see box 2)

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Cost of antibiotics. Looking at the medication cost from the perspective of the NSIII means looking at the reimbursement cost of prescribed medication. Since for many prescribed drugs for acute cough no reimbursements are made, significance testing of the medication cost in all patients is hampered by distributional problems. We tested for differences in reimbursement cost in the subset of patients who were prescribed an antibiotic. Since antibiotics represent the only reimbursed group of prescribed medication in this subset of patients, we actually tested for differences in antibiotic cost. The antibiotic cost was lower in the intervention group after our intervention compared to the control group (Mean Difference (MD)adj (95%CI) = -6.89 (-11.77 - (-2.02) �), and compared to the pre-test (MDadj = -6.11 (-9.97 - (-2.24) �) (Table 5) .

Time to symptom resolution. Concerning the use of antibiotics and the kind of antibiotics used the same conclusions can be drawn form the subset of patients responding with patient diaries. Comparing the time to resolution of all symptoms and to return to the activity and to the health status of before the illness, no significant difference was found between the patients in the intervention group and those in the control group after our intervention (Figure 2).

Other analyses. Large variations occurred across the included GPs in the prescription of antibiotics and in the extent of change for this outcome measure (Figure 3). The change in antibiotic prescription rates was not different in the first month compared to the last two months of the post-test period.

Discussion We were able to show that a tailored intervention to implement a guideline for acute cough optimised GPs' antibiotic prescribing for adult patients with acute cough. Compared to controls patients in the intervention group were prescribed less antibiotics. If GPs in the intervention group prescribed antibiotics, these were more in line with the guideline. No significant differences were found in patients' symptom resolution.


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Table 5. Mean and difference in change of medication cost in the subset of patients with an antibiotic prescription from the perspective of the National Sickness and Invalidity Insurance Institute (NSIII) Intervention Control Medication cost Pre-Test 22.86 21.48 Post-Test 16.75 22.35 Change - 6.11 +0.87 Difference - 6.97 MDadj (95%CI)* - 6.89 (- 11.77 – (- 2.02)) * Mean difference is based on the model assuming equal medication cost in intervention and control group in

the Pre-Test period, and is adjusted for patient characteristics (see box 2)

Figure 2 Symptom resolution of patients with acute cough: graph of times to symptom resolution vs. cumulative proportion symptomatic patients (Kaplan-Meier).

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Figure 3 Rates of antibiotic use in consultations for acute cough before and after the tailored interventions from all practices with more than 10 consultations in each period

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These kind of trials should not only contribute to evidence of the effect, but also to understanding of the mechanism.

The evidence of effect

Study limitations. The results may be biased due to the recruitment, non-response and response quality of the GPs. The recruited GPs did not differ from the other 64 GPs approached for this study nor from the other 108 GPs responding in the questionnaire study,17 as we reported elsewhere.37 Only more male GPs agreed to participate (63/85 vs. 36/64: p=0.02, vs. 64/108:p=0.03 respectively). Furthermore, their age and gender distribution is similar to national averages. The GPs responding in the Pre-Test (n=72), those responding in the Post-Test (n=59) and those responding in one (n=74) or in both study periods (n=56) did not significantly differ from the respective not responding GPs. In all responding GPs subgroups GPs in the intervention group were similar to those in the control group. Response quality, assessed by means of testing for differences in the proportion of patients eligible for recruitment actually included in the study, in the proportion of the included patients eligible for analysis, and in the proportion of the latter patients responding with patient diaries, as well as by testing for differences in the median cluster size, was similar in both study groups and study periods. It was not feasible to increase the sample size in the post-test because GPs were unable to include more than 10 patients on average per study period. Patient characteristics also might influence the results of this study, and because of the nature of the interventions, participating practices knew the group to which they were assigned. The patients included and eligible for analysis were younger than those eligible for recruitment. Their characteristics however did not differ between the study groups nor between the study periods, except for risk for thrombo-embolic disease, duration of cough, presence of sputum, of ronchi, of loss of appetite, and of a referral.

The professional intervention. Adjusting the main outcome measure, the antibiotic prescribing rate, for these differences, patients in the intervention were less likely to receive an antibiotic prescription compared to controls after our intervention.

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We might have underestimated the rates for antibiotic prescriptions because the practitioners may not have registered this information correctly in some instances on the pre-printed forms we provided. We preferred this data collection method since we also aimed to collect information not available in the many different electronic medical record systems used in Belgium or in other sources of prescribing data linked to clinical information. This is unlikely to have differed between the groups and is therefore unlikely to have affected the results. It is possible that we underestimated the reduction in the prescription of antibiotics for acute cough. We do not know how often patients were told that antibiotics normally are not necessary but received an antibiotic prescription for use "if needed." However, we know from the patient diaries that patients in the intervention group did not purchase nor took the prescribed antibiotics less often than patients in the control group. Figure 2 shows the importance of using adequately sized cluster randomised controlled trials to evaluate interventions to support the implementation of guidelines. Large variation exists in practice and in the extent of change among practices.

The public campaign. A national campaign, which coincided with our professional intervention, provided health education of the general public. Though the study does not, and did not set out to, compare the effect of the coincidence of a national public campaign and a professional intervention, the design of our study also allowed to test for an effect of the national public campaign on the antibiotic prescription rates for acute cough. We agree with Flottorp et al. that uncontrolled or inadequately controlled before and after evaluations in selected practices are likely to have spurious results that are, at best, difficult to interpret.38 Nonetheless, the similarities of the effectiveness of our intervention when assessing differences between the intervention and control group after our intervention and when assessing pre-post differences in the intervention group, together with the absence of pre-post differences in the control group, when adjusting for differences in patient characteristics, suggests the national campaign had no effect on antibiotic prescribing after our intervention. In contrast to the public campaign our professional intervention not only resulted in a reduction of antibiotic consumption. It changed the kind of antibiotics prescribed form less desirable to more desirable antibiotics as well.

Price to pay. This trial on the implementation of a guideline to optimise antibiotic prescribing not only looked at prescribing as outcome, but took patient outcomes into account as well. Though antibiotics are not needed for


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most patients with acute cough, indiscriminately reducing antibiotic use will withhold some patient subgroups from the benefits of antibiotics. Less and other antibiotics prescribed by the GP did not affect the time to symptom resolution of the patients in the intervention group compared to the controls after our intervention. Another notable aspect of our study was the short duration of the educational intervention compared with some other studies that have used repeated education over several weeks; for example, to improve adolescent health care 39 Despite the responding GPs were visited more than fifteen times by medical representatives per month, a single outreach visit resulted in the desired changes during the follow up.

We reached 36 out of 42 GPs with our intervention at a total cost of � 8514.22, or an intervention cost of � 236.51 per GP. The intervention resulted in a significant reduction of the reimbursement cost for antibiotics from the perspective of the NSIII of nearly � 7.

Understanding the mechanism

Recently, Gross and Pujat40 concluded that for implementing guidelines for appropriate antimicrobial usage multifaceted implementation methods seem to be the most successful. Although more complex interventions to implement guidelines tend to be most effective, their effectiveness varies, they require more resources, and it is difficult to know which interventions to use. Identifying barriers to change and tailoring interventions to address these is a logical approach to selecting appropriate interventions. Still the effectiveness of tailored interventions remains uncertain.38 Two recent cRCTs reported the effect of interventions addressing either general practices38 or primary healthcare teams,41 not individual general practitioners. In contrast to the tailored interventions which only had little effect on the antibiotic prescribing rates for sore throat38 and in contrast to the educational outreach visits, which also coincided with a national campaign, and which did not improve the influenza vaccination rates,41 our intervention had a substantial effect on antibiotic prescribing.

In stead of a ‘one size fits all’ approach, we really tailored the interventions to the needs of individual general practitioners. Tailoring the intervention at this level might have greater effect. After all individual approaches seem to have a greater impact on prescribing than group approaches.42 43 The individual

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approach of face to face meeting, academic detailing, to improve antibiotic prescribing proved to be successful in 8 studies in primary care.40 Furthermore, we actively supported the GPs with the outreach visits and we might have identified important barriers to change. Our educational program mainly addressed the barriers relating to the individual prescriber’ s barriers to change, focussing on non-medical reasons for prescribing. We did not provide individual feedback on prescribing or on decision criteria.44 Studies of scoring rules for sore throat have failed to show that they lower the rates for antibiotic prescription.45 46

We have not identified trials of the implementation of a guideline for acute cough similar to ours. The key messages of the pre-final version of the guideline used for this cRCT are the same as those of the final version.47 , also available now for all general practitioners at http://www.wvvh.be. Although our evidence base was rather poor, and uncertainty about the evidence may affect doctor's behaviour, identifying, understanding and modifying tacit expert knowledge and promoting the ownership of change amongst professionals appeared to be more important in altering behaviour in accordance with the guideline.48

If we also distinguish between an agenda for action and one for future research, the evidence of effectiveness supports this implementation strategy of the guideline to optimise antibiotic prescribing on a larger scale. Further research efforts should be devoted to understand the interaction between public campaigns and professional interventions and to cost-effectiveness studies. Whereas the public campaign transiently reduced antibiotic consumption and saved money,20 21 the involvement of the prescribers has the potential of influencing the prescribing decision as well, e.g. the kind of antibiotics prescribed.

Conclusions

The described strategy to support the implementation of the guideline, tailored to address identified barriers to optimise antibiotic prescribing for acute cough, achieved the goals of the public campaign:” Antibiotics: Use them less often, but better” .


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This trial is assigned the International Standard Randomised Controlled Trial Number (ISRCTN) ISRCTN09811591 by Current Controlled Trials Ltd.

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12. Perez-Cuevas R, Guiscafre H, Munoz O, Reyes H, Tome P, Libreros V, et al. Improving physician prescribing patterns to treat rhinopharyngitis. Intervention strategies in two health systems of Mexico. Soc Sci Med 1996:1185-94.


14. Deschepper R, Vander Stichele R, Haaijer-Ruskamp F. Cross-cultural differences in lay attitudes and utilisation of antibiotics in a Belgian and a Dutch city. Patient Educ Couns 2002;48:161-9.

15. Coenen S, Van Royen P, Denekens J. Diagnosis of acute bronchitis [letter; see reply]. J Fam Pract 1999;48:471-2.




19. Smucny J, Becker L, Glazier R, McIsaac W. Are Antibiotics Effective Treatment for Acute Bronchitis? A Meta-Analysis. J Fam Pract 1998;47:453-60.

20. A public campaign for a more rational use of antibiotics. 11th European Congress of Clinical Microbiology and Infectious Diseases (ECCMID); 2001; Istanbul, Turkey.

21. Watson R. Belgium cuts antibiotic use by 12%. BMJ 2001;323:710b-.


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22. Soumerai S, Avorn J. Principles of educational outreach ('academic detailing') to improve clinical decision making. JAMA 1990;263:549-6.

23. The AGREE Collaboration. AGREE Instrument. Available at: http://www.agreecollaboration.org. Accessibility verified February 7,2003.


25. Zaat J, Stalman W, Assendelft W. Hoort, wie klopt daar [Listen, who is knocking]? Huisarts en Wetenschap 1998;41:461-9.

26. Fine M, Auble T, Yealy D, Hanusa B, Weisfeld L, Singer D, et al. A prediction rule to identify low-risk patients with community-acquired pneumonia. NEJM 1997;336:243-50.

27. Wang E, Kellner J, Arnold S. Antibiotic-resistant Streptococcus pneumoniae. Implications for medical practice. Can Fam Physician 1998;44:1881-8.

28. Nava J, Bella F, Garau J, Lite J, Morera M, Marti C, et al. Predictive factors for invasive disease due to penicillin-resistant Streptococcus pneumoniae: a population-based study. Clin Infect Dis 1994;19:884-90.




32. Wears R. Advanced statistics: Statistical methods for analyzing cluster and cluster-randomized data. Acad Emerg Med 2002;9:330-41.

33. SAS System for Windows [program]. 8.02 version. Cary, NC: SAS Institute Inc., 2001.

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34. STATISTICA for Windows [program]. 6.0 version. Tulsa, OK: StatSoft, Inc., 2001.

35. Liang K, Zeger S. Longitudinal data analysis using generalized linear models. Biometrika 1986;73:13-22.

36. Ridout M, Demétrio C, Firht D. Estimating intraclass correlation for binary data. Biometrics 1999;55:137-48.

37. Coenen S, Michiels B, Renard D, Denekens J, Van Royen P. Antibiotics for coughing in family practice: physicians' perception of patients' requests determines prescription behavior. J Fam Pract 2002: Submitted.

38. Flottorp S, Oxman AD, Havelsrud K, Treweek S, Herrin J. Cluster randomised controlled trial of tailored interventions to improve the management of urinary tract infections in women and sore throat. BMJ 2002;325:367-70.

39. Sanci LA, Coffey CMM, Veit FCM, Carr-Gregg M, Patton GC, Day N, et al. Evaluation of the effectiveness of an educational intervention for general practitioners in adolescent health care: randomised controlled trial • Commentary: Applying the BMJ's guidelines on educational interventions. BMJ 2000;320:224-30.

40. Gross P, Pujat D. Implementing practice guidelines for appropriate antimicrobial usage: a systematic review. Med Care 2001;39:II55-69.

41. Siriwardena A, Rashid A, Johnson M, Dewey M. Cluster randomised controlled trial of an educational outreach visit to improve influenza and pneumococcal immunisation rates in primary care. Br J Gen Pract 2002;52:735-40.

42. van Eijk MEC, Avorn J, Porsius AJ, de Boer A. Reducing prescribing of highly anticholinergic antidepressants for elderly people: randomised trial of group versus individual academic. BMJ 2001;322:654-7.

43. Figueiras A, Sastre I, Tato F, Rodriguez C, Lado E, Caamano F, et al. One-to-one versus group sessions to improve prescription in primary care: a pragmatic randomized controlled trial. Med Care 2001;39:158-67.

44. Veninga C, Lagerlov P, Wahlstrom R, Muskova M, Denig P, Berkhof J, et al. Evaluating an educational intervention to improve the treatment of asthma


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in four European countries. Drug Education Project Group. Am J Respir Crit Care Med 1999;160:1254-62.

45. Poses R, Cebul R, Wigton R. You can lead a horse to water--improving physicians' knowledge of probabilities may not affect their decisions. Med Decis Making 1995;15:65-75.

46. McIsaac W, Goel V. Effect of an Explicit Decision-support Tool on Decisions to Prescribe Antibiotics for Sore Throat. Med Decis Making 1998;18:220-8.

47. Coenen S, Van Royen P, Michels J, al e. Aanbeveling voor goede medische praktijkvoering: Acute hoest [Good Clinical Practice Guideline: Acute Cough]. Huisarts Nu 2002;31:391-411.

48. Kelley MA, Tucci JM. Bridging the quality chasm [editorial]. BMJ 2001;323:61-2.

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VII

Patients’ views on respiratory symptoms and antibiotics

Introduction

In Europe there is a striking variation in outpatient antibiotic usage.1 In 1997, in Belgium 27 Defined Daily Dosages per 1000 inhabitants per day were consumed, compared to 18 for the UK and 9 for the Netherlands. And looking at 1998 data from the Alexander Project antimicrobial resistance of Streptococcus pneumoniae, especially macrolide resistance, is correlated with these figures.2

Cough is the most common reason for encounter (for respiratory tract infections) in general practice.3 4 Likewise patients frequently consult their GP for other respiratory symptoms, such as earache and sore throat. And though antibiotics have no or very limited effects,5-7 antibiotics are frequently prescribed for these respiratory symptoms.8-10 Moreover, especially in primary care and for respiratory tract infections antibiotics are overprescribed.11-13 This overprescribing wastes money, exposes patients unnecessarily to the risk of side effects, encourages reconsulting for similar problems and causes antimicrobial resistant bacteria.8

Non-medical determinants, either patient- or physician-related, appear to have a major influence on this overprescribing.14-17 Macfarlane showed non-medical determinants influenced nearly half the prescribing decisions for acute lower respiratory tract symptoms.18 Patient pressure was cited most frequently. Little

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showed non-medical factors influenced prescribing for upper respiratory tract infections. 19 We found that GPs' perception of patients' request for an antibiotic significantly influenced prescribing for acute cough.20 Furthermore, patients seem to overestimate the effectiveness of antibiotics.18 In a US study, 79% of respondents believed antibiotics are effective for a discoloured nasal discharge, and 31%- 61% believed antibiotics are effective against colds.21 22 Patients’ views on respiratory symptoms and antibiotics thus deserve consideration as possible determinants of antibiotic use.1 23

And since antibiotic resistance is an international problem, an awareness of possible similarities and differences in views between countries might be helpful in designing international interventions to optimise antibiotic usage, particularly in Europe. For a better understanding of patients' views on frequent respiratory symptoms, cough, earache and sore throat, we performed a postal questionnaire study with patients in Belgium, in the UK and in the Netherlands. This study was a collaboration between the Department of General Practice, Faculty of Medicine, of the University of Antwerp in Belgium, the Department of General Practice, College of Medicine, of the University of Wales in the UK and the Department of General Practice and Patient Oriented Research of the University Medical Center Utrecht in The Netherlands, the initiator of the study. For this thesis the emphasis will be laid on the results for Belgium.

Methods

Study sample

In Belgium, as well as in the UK and in the Netherlands, four general practices were recruited purposefully to represent a sample with a range of social and educational levels: two rural and two urban, each with one practice located in a deprived and one in a non-deprived area. In each practice one hundred patients (age between 18 and 65 years) were randomly selected. Those who were unable to read the questionnaire (because of a language problem or mental disorder) or were suffering from a serious disabling disease were excluded by GP’ s screening the selection lists.


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Data collection

All selected patients received a questionnaire. After ten days a first reminder was sent. Two weeks after the first reminder a second reminder with a new questionnaire was sent to patients from practices with a response rate lower than 50%.

Questionnaire

The questionnaire was based on a questionnaire previously piloted in the Netherlands24 and further developed in collaboration with the three centres. The questionnaire contained the following domains: seriousness (need to consult a general practitioner and perceived seriousness), self-limiting character, effectiveness of antibiotics (to speed up recovery and to prevent deterioration), adverse effects of antibiotics and aetiology. Patients were asked to rate their agreement to statement on five-point scale with categories ranging from 1 (strongly disagree) to 5 (strongly agree).

Data processing and statistical analysis

The data were entered with a 10% double-check. The analysis was performed in the Dutch centre. Extremely skewed, bipolar items or those, which were not completed by more than 20% of the responders were excluded from further analysis. The items were grouped into 6 clusters of views relating to respiratory tract symptoms: need to consult a general practitioner, perceived seriousness, perceived self limiting character, perceived effectiveness of antibiotics to speed up recovery, perceived effectiveness of antibiotics to prevent deterioration, with each cluster containing items relating to cough, sore throat and earache respectively, and side effects of antibiotics. This grouping of items was controlled by means of principal component factor analysis with Varimax rotation. The inter-correlation between the items in each cluster was calculated by means of Cronbach’ s alpha. Results were expressed as means. In addition, correlations between the views (Pearson correlation coefficient r) were described, with correlations � .25 being concerned as relevant (corresponding with R² � 0.05).

All analyses were performed with SPSS 10.0.

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Results

Respondents

In Belgium in total 243 evaluable questionnaires were returned (response rate 60.8%)(Table). Inter-practice variation was small. The respondents mean age was 41.3 years, 60.2% were women and they were highly qualified. Reported use of antibiotics during the past two years was very high (62.1%). This applied to antibiotics prescribed by a medical doctor as well as use of antibiotics not prescribed by a medical doctor for the illness for which they were taken. Forty-five percent of the respondents reported experiencing respiratory tract symptoms during the previous month.

Grouping of items

Principal component factor analysis with Varimax rotation endorsed the chosen clusters. The clusters need to consult a general practitioner and perceived seriousness both loaded on one factor, as did the clusters perceived effectiveness of antibiotics to speed up recovery and perceived effectiveness of antibiotics to prevent deterioration. However, for semantic reasons, they were analysed apart. The inter-correlation between the items within the six clusters of views was moderate to strong (Cronbach’ s α ranged from .57 to .88), which meant that the items reflect one concept underlying each cluster of items.

Views on respiratory tract symptoms and antibiotics

Belgian respondents reported a great need to consult a general practitioner with respiratory tract symptoms (mean = 4.5) and considered these symptoms as serious (mean = 4.2) and less as self-limiting (mean = 2.9). They reported similar perceptions of the effectiveness of antibiotics to speed recovery (mean = 3.1) and to prevent respiratory tract symptoms deteriorating (mean = 2.8). Belgian patients often endorsed concerns about adverse effects from antibiotics (mean = 4.3) and they also regarded a general practitioner as the best person to consult with respiratory tract symptoms. More than 75% of the respondents appeared to agree (strongly) with the statement that bacteria are an important cause for respiratory tract symptoms.


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Correlations between views

There was a moderate correlation between ‘need to consult a general practitioner’ and ‘perceived seriousness’ (r:.41) and a strong correlation between ‘perceived effectiveness of antibiotics to speed up recovery’ and ‘perceived effectiveness of antibiotics to prevent deterioration’ (r:.61), as could be expected from the factor analysis. The remaining correlations between these four views were weak. The view that a general practitioner is the best person to consult for respiratory tract symptoms was a core view being correlated with all views except the views concerning perceived seriousness and side effects. Perceiving of the self-limiting character of respiratory tract symptoms was negatively correlated with the general practitioner as the best person to consult and did not correlate with the remaining clusters (r:-.31). Perceiving bacteria as an important cause of respiratory tract symptoms was only correlated with the perceived effectiveness of antibiotics to prevent deterioration (r:.27).

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Table Demographic characteristics (mean and SD) of respondents from the Netherlands, UK and Belgium and their views on respiratory tract symptoms and antibiotics (AB) (mean and SD; Cronbach’s alpha) (1)

Countries Netherlands UK Belgium All

(n=247) (n=188) (n=243) (n=678)

Resonse rate (%) 61.7 37.6 60.2 52.2

Age 40.1 (11.8) 44.9 (12.1) 41.3 (13.0) 41.9 (12.4)

Gender (% female) 64.0 55.6 65.8 62.3

Highest level of education

-low 10.7 17.9 7.2 11.4

-medium 58.1 46.2 51.7 52.6

-high 31.2 35.8 41.1 36.1

Antibiotics past 2 years

-prescribed (%) 31.8 54.0 62.1 48.8

- not prescribed (abs) 5 10 12 27

In case of respiratory tract symptoms

α α α α Need to consult a general practitioner 3.8 (1.0) 3.6 (0.7) 4.5 (0.6) 4.0 (0.9)

Cough and raised temperature >2 days 3.5 (1.4) 3.4 (1.0) 4.4 (1.0) 3.8 (1.3)

Sore throat and raised temperature >2 days

3.4 (1.4) 3.2 (1.0) 4.4 (0.9) 3.7 (1.3)

A child with earache >2 two days 4.5 (0.8)

.75

4.1 (0.7)

.66

4.8 (0.5)

.57

4.5 (0.7)

.74

Perceived seriousness 3.6 (1.0) .80 3.4 (0.7) .74 4.2 (0.8) .79 3.8 (0.9) .82

Cough and raised temperature 3.5 (1.2) 3.3 (1.0) 4.1 (1.0) 3.7 (1.1)

Sore throat and raised temperature 3.5 (1.1) 3.3 (0.9) 4.2 (0.9) 3.7 (1.1)

A child with earache and raised temperature

3.8 (1.0)

3.7 (0.8)

4.3 (0.8)

3.9 (1.0)

Perceived self-limiting character 3.6 (0.9) .67 3.4 (0.7) .67 2.9 (1.0) .67 3.3 (0.9) .70

Cough better without treatment < 2 weeks 3.7 (1.2) 3.5 (1.0) 2.9 (1.3) 3.4 (1.3)

Sore throat better without treatment < 1 week

4.0 (1.1) 3.7 (0.9) 3.2 (1.3) 3.6 (1.2)

Earache almost always gets better without treatment within two days

3.1 (1.2) 3.0 (0.9) 2.7 (1.2) 2.9 (1.1)


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Table continued.

In case of respiratory tract symptoms

α α α α Antibiotics speed up recovery 3.3 (1.1) .83 2.9 (0.7) ..69 3.1 (1..1) .84 3.1 (1.0) .82

Antibiotics speed recovery from coughs 3.1 (1.3) 2.7 (0.8) 2.9 (1.3) 2.9 (1.2)

Antibiotics speed recovery from sore throats

3.3 (1.2) 2.8 (1.0) 2.8 (1.3) 3.1 (1.2)

Antibiotics speed recovery from earache 3.4 (1.2) 3.1 (1.3) 2.9 (1.3) 3.3 (1.1)

AB stop deteriorating symptoms 2.9 (1.2) .86 2.8 (0.8) .77 2.8 (1.2) .88 2.8 (1.1) .85

Antibiotics stop cough deteriorating 2.6 (1.4) 2.6 (0.9) 2.6 (1.3) 2.6 (1.2)

Antibiotics stop sore throats deteriorating 2.8 (1.3) 2.8 (1.0) 2.8 (1.3) 2.8 (1.2)

Antibiotics stop earache deteriorating 3.1 (1.3)

3.1 (1.3)

2.9 (1.3)

3.0 (1.2)

Side effects of antibiotics(2) 4.0 (1.0) .66 3.8 (0.9) .74 4.3 (1.0) .77 4.0 (1.0) .74

Frequent use can cause problems for your health

4.1 (1.0) 3.9 (0.9) 4.5 (0.9) 4.2 (1.0)

Frequent use can cause problems for the community

3.7 (1.3) 3.6 (1.1) 4.2 (1.2) 3.9 (1.2)

A GP is the best person to go 3.6 (1.1) 3.4 (1.0) 4.2 (0.9) 3.8 (1.1)

Bacteria are an important cause 4.2 (1.0) 3.8 (0.8) 4.1 (0.9) 4.0 (0.9)

(1) The answers were ranged as follows: 1: totally disagree to 5: totally agree (2) This view is based on two items, so the Pearson correlation coefficient was used in stead of

Cronbach’s alpha

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Discussion

Because we sampled from only four practices, our results should be treated cautiously.

In the table, the results for Belgium are presented together with those for the Netherlands and the UK. Patient report of antibiotic use during the preceding two years was highest in Belgium and lowest in the Netherlands with the UK in between. Belgian respondents perceived a higher need to consult a general practitioner with respiratory symptoms and viewed these as more serious and less self-limiting compared to UK and Dutch respondents. This is congruent with respondents’ higher reported use of antibiotics, as well as higher national figures for antibiotic prescription in Belgium compared with the UK and the Netherlands.1 This congruence suggests validity of our data. The intercorrelation between the items with the six clusters was moderate to strong (Cronbach’ s α ranged from .70 to .85 for all respondents together).

There were smaller differences between the UK and Dutch respondents’ views as might be expected, given the differences in national antibiotic use. Countries’ health care delivery characteristics, such as having personal patients lists, and the degree of participation of GP's in peer review groups addressing prescribing behaviour, having national guidelines on management and patient education, and physician availability also may contribute to the international variance in views as well as in antibiotic use.23

Given the differences between the countries and the intercorrelation between the clusters, patient-directed interventions might fruitfully highlight the benign nature of the vast majority of respiratory tract symptoms, which makes consulting the general practitioner generally unnecessary. Stressing the danger of side effects of antibiotics might be less important. Further studies must be concentrated on the responsiveness to changes in views of this scale and the relevance of such changes in relation to reduction of antibiotic use.


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References


2. Schito GC, Debbia EA, Marchese A. The evolving threat of antibiotic resistance in Europe: new data from the Alexander Project. J Antimicrob Chemother 2000;46:3-9.

3. De Maeseneer J. Huisartsgeneeskunde: een verkenning [General practice: an exploration]. Proefschrift [Dissertation] Rijksuniversiteit Gent, 1989.


5. Smucny J, Fahey T, Becker L, Glazier R, McIsaac W. Antibiotics for acute bronchitis (Cochrane Review). In: The Cochrane Library, Issue 4, 2002. Oxford: Update Software.

6. Del Mar C, Glasziou P, Spinks A. Antibiotics for sore throat (Cochrane Review). In: The Cochrane Library, Issue 4, 2002. Oxford: Update Software.

7. Glasziou P, Del Mar C, Sanders S, Hayem M. Antibiotics for acute otitis media in children (Cochrane Review). In: The Cochrane Library, Issue 4, 2002. Oxford: Update Software.

8. Butler C, Rollnick S, Kinnersley P, Jones A, Stott N. Reducing antibiotics for respiratory tract symptoms in primary care: consolidating 'why' and considering 'how'. Br J Gen Prac 1998;48:1865-70.


10. Gonzales R, Bartlett J, Besser R, Cooper R, Hickner J, Hoffman J, et al. Principles of appropriate antibiotic use for treatment of acute respiratory tract infections in adults: background, specific aims, and methods. Ann Emerg Med 2001;37:690-7.

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12. Koninklijke Academie voor Geneeskunde van België [Belgian Royal Academy for Medicine]. Advies inzake het overgebruik van antibiotica [Advice concerning the overuse of antibiotics]. Tijdschr Geneeskd 1999;55:173-4.

13. Kuyvenhoven M, Verheij T, de Melker R, van der Velden J. Antimicrobial agents in lower respiratory tract infections in Dutch general practice. Br J Gen Pract 2000;50:133-4.

14. Britten N, Ukoumunne O. The influence of patients' hopes of receiving a prescription on doctors' perceptions and the decision to prescribe: a questionnaire survey. BMJ 1997;315:1506-10.





19. Little P, Williamson I, Warner G, Gould C, Gantley M, Kinmonth AL. Open randomised trial of prescribing strategies in managing sore throat. BMJ 1997;314:722-7.

20. Coenen S, Michiels B, Renard D, Denekens J, Van Royen P. Antibiotics for coughing in family practice: physicians' perception of patients' requests determines prescription behavior. J Fam Pract: Submitted.


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21. Braun B, Fowles J, Solberg L, Kind E, Healey M, Anderson R. Patient beliefs about the characteristics, causes, and care of the common cold: an update. J Fam Pract 2000;49:153-6.

22. Mainous Ar, Zoorob R, Oler M, Haynes D. Patient knowledge of upper respiratory infections: implications for antibiotic expectations and unnecessary utilization. J Fam Pract 1997;45:75-83.


24. van Duijn H, Kuyvenhoven M, Welschen I, den Ouden H, Slootweg A, Verheij T. Patients' and doctors' views on respiratory tract symptoms. Scand J Prim Health Care 2002;20:201-2.

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VIII


General discussion

Summary of the results

In this dissertation we aimed to describe the management of complaints about coughing in general practice, and to optimise this management, especially regarding the antibiotic prescribing decision. Patients’ views on the topic were addressed as well.

We described the management of patients with acute cough in Flemish general practice by means of qualitative and quantitative research methodologies. Focus group research enabled us to generate hypotheses on GPs’ decision making regarding complaints about coughing and the determinants underlying their decisions.1 GPs have to deal with diagnostic uncertainty when trying to distinguish between infectious and non-infectious causes of coughing. In suspected respiratory tract infections, GPs want to make a distinction between clinical syndromes such as bronchitis and pneumonia, viral and bacterial respiratory tract infections, and upper and lower respiratory tract infections. This also cannot be achieved with certainty on the basis of medical history and clinical examination. Dealing with diagnostic uncertainty, GPs’ decisions are directed at whether or not to prescribe antibiotics. For this therapeutic decision, patient- and doctor-related factors, such the patient’ s expectations and the GP’ s

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perceptions of these, also play a role. These non-medical reasons give rise to a shift in the action threshold in favour of antibiotics, a phenomenon explained by the ‘chagrin factor’ . A questionnaire study with adequate response enabled us to quantify and condense the focus group determinants and confirmed the focus group findings.2 The participating GPs (mean age:42.8 years; 65.9% men) considered all the items included in the questionnaire: always the items relating to the lung auscultation, often the items determining whether there is something unusual happening – both medical reasons – and to a lesser extent non-medical reasons. Non-medical as well as medical reasons supported antibiotic treatment. By means of multivariable analysis of medical and non-medical data registered by GPs about adult patients consulting at their practice with acute cough as one of the most prominent complaints, the findings of the previous studies were validated.3 The GPs’ perception of the patients' request for an antibiotic, a non-medical reason that was mentioned in the focus groups and scored high in the questionnaire study as a determinant for antibiotic prescribing, was significantly associated with antibiotic prescribing. Antibiotics were prescribed more often when a patient’ s request for an antibiotic was perceived and the lung auscultation was normal or revealed only one abnormal finding. Abnormal auscultatory findings were also associated with more prescribing.

Antibiotics are thus prescribed for medical reasons if these are available and, especially when GPs have to deal with diagnostic uncertainty, non-medical reasons favour antibiotic prescribing as well. Hence, clinical practice guidelines and interventions to optimise antibiotic prescribing have to take non-medical reasons for antibiotic prescribing into account.

To change the described management of acute cough, especially regarding the antibiotic prescribing decision, a clinical practice guideline was developed according to a standardised methodology defined by the Scientific College of Flemish General Practitioners and in line with the AGREE-criteria.4 A tailored professional intervention, including this guideline, one educational outreach visit and a written reminder, to implement the guideline, was successful in optimising antibiotic prescribing for patients with acute cough. In addition to a reduction in antibiotic prescriptions, prescribed antibiotics were more in line with the guideline recommendations and less expensive from the perspective of the National Sickness and Invalidity Insurance Institute (NSIII). The change in antibiotic prescribing did not affect the patients’ symptom resolution.5

General discussion

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For a better understanding of patients' views about frequent respiratory symptoms, cough, earache and sore throat, and antibiotic treatment, we performed a postal questionnaire study with patients in Belgium, in the UK and in the Netherlands. Belgian respondents perceived a higher need to consult a GP with respiratory symptoms and viewed these as more serious and less self-limiting compared to UK and Dutch respondents.

Limitations of the project

The internal and the external validity of the description of the management of patients with acute cough in Flemish general practice is limited by the measurement of the topic and the selection of the recruited and participating GPs. To understand this complex decision making process, especially the antibiotic prescribing decision, we triangulated three different research methodologies, starting with a qualitative study. Therefore, stating that in the prescribing decision non-medical reasons such as the patients’ request for antibiotics also play a role, seems a valid general conclusion. If there is diagnostic uncertainty this is almost unavoidable.6 In addition, we have shown that this irrational prescription behaviour can be explained by the so-called chagrin factor7: GPs consider it less appropriate not to prescribe antibiotics when this may prove to be necessary, than to prescribe antibiotics when not necessary. The latter caused less ‘chagrin’ to GPs. Furthermore, these finding are in line with Butler’ s qualitative research regarding the prescribing decision for sore throat.8 We confirmed our general conclusion by studying larger samples of GPs. And though these were not strictly representative samples, non-medical reasons have been shown to affect prescribing behaviour of GPs for respiratory tract infections in the work of Little9 and MacFarlane10, and it has been suggested that GPs’ perception of patient expectations may be the strongest determinants for antibiotic prescribing by others as well.11 12

The development of the clinical practice guideline for acute cough was hampered by the lack of good evidence for the management of acute cough. We chose to study the management of acute cough, and not the management of a respiratory syndrome like acute bronchitis, since most patients consult a GP with complaints about coughing,13 14 and the diagnosis of respiratory syndromes is not valid, nor reliable in general practice.15 Pooling the limited

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evidence concerning the effectiveness of antibiotics, the latter problem was also acknowledged,15 resulting in the use of acute (productive) cough as a synonym or in stead of acute bronchitis in the most recent meta-analysis.16

Currently there are no clinical criteria to identify subsets of patients who are most likely to benefit form antibiotic treatment, and the overall benefit from antibiotics for patients with acute (productive) cough is limited: antibiotics do not influence the (duration of) productive cough, nor the (duration of) the limitations in work or activities; and of every 10 patients with acute (productive) cough more than 8 will be clinically improved after 7-11 days regardless the use of antibiotics; less than one patient extra will be improved due to antibiotics, but as many patients will experience the side effects of treatment. The management recommended in the guideline not to treat immuno-competent adult patient with antibiotics after ruling out possibly life threatening conditions such as pneumonia (severity assessment), and considering other possible causes for acute cough than an uncomplicated respiratory infection is in line with the currently available evidence. The non-medical reasons for antibiotic prescribing were taken into account in the guideline as well. And probably a guideline for acute cough is fitting in better with daily practice than a guideline for acute bronchitis.

Writing and publishing guidelines however is not sufficient to change antibiotic prescribing practices in primary care. Our intervention to implement the guideline included dissemination of the guideline for acute cough, a short one-to-one conversations between a detailer and a practitioner, with the goal of persuading the practitioner to change behaviour in concordance with the guideline through tailored information and evidence, and a written reminder. We thus preferred the individual approach of academic detailing as implementation method, and actively supported the GPs with educational outreach visits. Furthermore, we tailored the intervention to identified barriers to change relating to the individual prescriber. To facilitate better implementation of guidelines on appropriate antibiotic management of respiratory infections(, excluding pneumonia,) multifaceted implementation methods are most useful, according to a systematic review by Gross and Pujat,17 but not all studies have shown a positive effect.18 Furthermore, it is difficult to determine which part or parts of complex methods are critical to successful implementation. Academic detailing however appears to be useful as an individual implementation method in primary care. Up to the start of our intervention all the evidence for the effectiveness of academic detailing to

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optimise antibiotic prescribing by general practitioners came from outside Europe. The success of implementation methods used in before-and-after studies19 20 however should not necessarily be viewed as definitive evidence for the utility of academic detailing. Selection bias can also occur in controlled studies if the control patients are not randomised.21-23 Randomised controlled trials typically compensate for such bias. But only one RCT showing a reduction in antibiotic prescription was performed,24 and two RCTs showed academic detailing had a significant impact on recommended drug usage and prescribing costs.25 26

We performed a cluster-randomised controlled before and after study in Flanders, Belgium, to assess the effectiveness of our implementation strategy. We measured the prescription rates of antibiotics and, if antibiotics were prescribed, prescription rates of the recommended antibiotics. In addition to the prescribing costs, we assessed the cost of the intervention as well. And we took patient outcome into account. Our results are in line with the assessments of other professional interventions in primary care. Yet the indicators we used to assess success did not allow to distinguish the effectiveness of the guideline from the effectiveness of the implementation methods.

Although the participating GPs, the proportion of patients eligible for recruitment included in the study and in the analysis, and the characteristics of the latter patients were similar for both study groups in both study periods, a selection of GPs and patients might have influenced the results. Cross-contamination of the study groups was unlikely, as was a Hawthorne effect because the control group knew that a study was being done to improve antibiotic usage for acute cough. The concurrent control group controlled for unknown factors, such as changes in the microbial patterns, in the medical delivery system and in provider knowledge and practices that occurred over time. Such changes between the two study periods limit the ability to draw definitive conclusions on the merits of an intervention assessed in before-and-after studies.

Implementing evidence-based guidelines is one of the most known, and best studied examples of professional interventions. Although more complex interventions to implement guidelines tend to be most effective, their effectiveness varies – and should not be exaggerated – they require more resources, and it is difficult to know which intervention to use. Furthermore, the issue seems to be one that takes time. But, although the participating

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physicians were frequently visited by advocates for the use of antibiotics, a single visit by advocates for improved communication with their patients optimised their antibiotic prescribing significantly.

We did not provide individual feedback on their prescribing, nor did we use patient education or media support. In the context of a national public campaign, which coincided with our professional intervention patient information leaflets and booklets were distributed among all GPs and pharmacies. This campaign also included TV spots and radio messages informing the public on over consumption and misuse of antibiotics, the resulting resistance problem and the self-limiting character of most frequent infections in the community. Although this campaign was no longer effective at the time of our assessment, the effect of our professional intervention may include a significant interaction of the public campaign with our professional intervention. Still a patient information leaflet describing the uncertain value of antibiotics reduced antibiotic use in patients presenting with lower respiratory tract infections.27 However this approach is appealing, it is clearly not the final answer. Half of the patients took the antibiotics that their physician felt unnecessary

Each year the NSIII provides GPs with individual feedback on their prescribing of reimbursed pharmaceutical specialities, e.g. the gross amount for and the volume in Daily Defined Dosage (DDD) of antimicrobials for systemic use (Anatomic Therapeutic Chemical class J (ATC J). There was a delay of about two years between the prescribing and the prescribing feedback before the start of our intervention study in 1999. Before the randomisation of the GPs willing to participate received feedback on ATC J prescribing for 1997. Before our intervention they received the data for 1998. On the other hand an intervention of repeated mailings containing confidential profiles of the prescribing habits of an individual provider compared with those of his or her local groups and peers and accompanying educational materials however can be successful, even without the use of direct personal contact by academic detailers, opinion leaders, or nurse or pharmacist implementers.28 Computerised decision-support programs that make recommendations as orders are typed into the computer appear to be an excellent, real-time method of guideline implementation. But all studies are hospital based.17

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As pointed out by Schaffner and his colleagues two decades ago, the challenge to the medical profession is whether to develop and implement effective programs to correct excess in medical practice or whether to leave this responsibility to others, such as the government and managed care organisations.19 We have now provided more evidence for the effectiveness of implementing guidelines on the appropriate use of antibiotics by means of academic detailing.

Concerning the assessment of patients’ views on respiratory symptoms and antibiotics a postal questionnaire study was performed with patients in Belgium, in the UK and in the Netherlands. The questionnaire was based on a questionnaire previously piloted in the Netherlands29 and further developed in collaboration with the three centres. Though internal consistency is good, the validity of the identified domains and the questionnaire items and the questionnaire’ s responsiveness to change needs further study.

Opportunities for further research

To preserve the effectiveness of antibiotics for the management of respiratory tract infections, the focus of future research activities should be in line with the description of the topic:” Management of respiratory tract infections,” for the first call for the Sixth Framework Programme (FP6) published December 2002 by the European Commission in the work programme of the thematic priority area 1:” Life Sciences, Genomics and Biotechnology for Health” under the headings “ Combating major diseases,” “ Applications-orientated genomic approaches to medical knowledge and technologies,” and “ Combating resistance to antibiotics and other drugs.” Consequently, the focus should be to address current fragmentation by integrating microbial and human genomics with clinical research and cost-benefit/cost-effectiveness studies towards a common understanding of an improved evidence-based management of community acquired RTIs with the aim of reducing antibiotic resistance. The activities should take into account validation and implementation of novel treatment, prevention and diagnostic approaches for various bacterial and viral respiratory pathogens.

Research activities on microbial genomics could comprise the development, standardisation and validation of innovative molecular methods to establish the aetiology of RTIs, to elucidate the relative importance of various pathogens

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with regard to morbidity and to determine the presence of genetic elements conferring antimicrobial resistance. Identification of new antibiotic resistance determinants and description of new resistance profiles are necessary to predict future trends in bacterial resistance and to ensure optimal therapy for patients as well.

Activities on human DNA could identify genetic risk factors for RTIs with worse prognosis, e.g. community-acquired pneumonia.

By using qualitative as well as quantitative research methods clinical research could provide a deeper and setting specific understanding of antibiotic prescribing and antibiotic use on a macro- and micro-level, both for primary care and secondary care. In addition, these data could also be used to identify domains and questions (item generation) for an evaluative instrument to measure change in patients’ attitude, knowledge and beliefs about common infections and their management. At the present time, no validated, responsive instrument is available for measuring the effect of interventions aimed at changing peoples attitudes, beliefs and knowledge about common infections, despite the fact that high profile public campaigns and other interventions are being undertaken with this aim. Observational studies could contribute to gaining insight into the incidence, aetiology, optimal diagnostic strategies, individual risks for severe outcome and infection with resistant micro-organisms. Furthermore, intervention studies are needed to solve the ongoing debate on the overall benefit from antibiotics, to identify subgroups who will (not ) benefit from antibiotic, and to improve the management of RTIs, especially antibiotic prescribing. Evidence on the effectiveness of symptomatic treatment of RTIs could also contribute to improve antibiotic prescribing. For primary care these clinical research activities requires operational networks of GPs, which for Belgium need to be established and/or supported.

This dissertation is line with the empirical evidence base for changing behaviour, suggesting that academic detailing (outreach visits to practices) supplemented by other interventions is likely to be the most effective way to implement guidelines to change doctors prescribing behaviour. More evidence on the effectiveness of computerised decision support programmes in primary care is needed, as is research to determine which individual part of complex methods is most successful.

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Finally economic evaluations of diagnostics, therapeutics, outreach visits and other interventions to improve antibiotic prescribing could be performed in cost-benefit/cost effectiveness studies.

References 1. Coenen S, Van Royen P, Vermeire E, Hermann I, Denekens J. Antibiotics for coughing in general practice: a qualitative decision analysis. Fam Pract 2000;17:380-5.

2. Coenen S, Michiels B, Van Royen P, Van der Auwera J-C, Denekens J. Antibiotics for coughing in general practice: a questionnaire study to quantify and condense the reasons for prescribing. BMC Fam Pract 2002;3:16.

3. Coenen S, Michiels B, Renard D, Denekens J, Van Royen P. Antibiotics for coughing in general practice: GPs' perception of patients' request determines prescribing. Submitted.

4. Coenen S, Van Royen P, K VP, Michels J, Dieleman P, Lemoyne S, et al. Aanbeveling voor goede medische praktijkvoering: Acute hoest [Good Clinical Practice Guideline: Acute Cough]. Huisarts Nu 2002;31:391-411.


6. Fahey T. Antibiotics for respiratory tract symptoms in general practice. British Journal of General Practice 1998;48:1815-6.




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13. Okkes I, Oskam S, Lamberts H. Van klacht naar diagnose. Episodegegevens uit de huisartspraktijk. Bussum: Coutinho, 1998.

14. De Maeseneer J. Huisartsgeneeskunde: een verkenning [General practice: an exploration]. Proefschrift Rijksuniversiteit Gent, 1989.

15. Arroll B, Kenealy T. Antibiotics for acute bronchitis. BMJ 2001;322:939-940.

16. Becker L, Glazier R, McIsaac W, Smucny J. Antibiotics for Acute Bronchitis (Cochrane Review). In: Software U, editor. The Cochrane Library, Issue 4. Oxford, 2002.

17. Gross P, Pujat D. Implementing practice guidelines for appropriate antimicrobial usage: a systematic review. Med Care 2001;39:II55-69.

18. O'Connor P, Amundson G, Christianson J. Performance Failure of an Evidence-Based Upper Respiratory Infection Clinical Guideline. J Fam Pract 1999;48:690-7.

19. Schaffner W, Ray W, Federspiel C, Miller W. Improving antibiotic prescribing in office practice: a controlled trial of three educational methods. JAMA 1983;250:1728-1732.

20. Stewart J, Pilla J, Dunn L. Pilot study for appropriate anti-infective community therapy. Canadian Family Physician 2000;46:851-859.

21. Perez-Cuevas R, Guiscafre H, Munoz O, Reyes H, Tome P, Libreros V, et al. Improving physician prescribing patterns to treat rhinopharyngitis. Intervention strategies in two health systems of Mexico. Soc Sci Med 1996:1185-1194.

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22. Zwar N, Wolk J, Gordon J, Sanson-Fisher R, Kehoe L. Influencing antibiotic prescribing in general practice: a trial of prescriber feedback and management guidelines. Family Practice 1999;16:495-500.

23. Gonzales R, Steiner J, Lum A, Barrett PJ. Decreasing antibiotic use in ambulatory practice: impact of a multidimensional intervention on the treatment of uncomplicated acute bronchitis in adults. JAMA 1999;281:1512-1519.

24. DeSantis G, Harvey K, Howard D. Improving the quality of antibiotic prescription patterns in general practice. The role of educational intervention. Med J Aust 1994;160:502-505.

25. Avorn J, Soumerai S. Improving drug-therapy decisions through educational outreach. A randomized controlled trial of academically based "detailing". N Engl J Med 1983;308:1457-1463.

26. Ilett K, Johnson S, Greenhill G, Mullen L, Brockis J, Golledge C, et al. Modification of general practitioner prescribing of antibiotics by use of a therapeutics adviser (academic detailer). Br J Clin Pharmacol 2000;49:168-173.

27. Macfarlane J, Holmes W, Macfarlane R. Reducing reconsultations for acute lower respiratory tract illness with an information leaflet: a randomized controlled study of patients in primary care. British Journal of General Practice 1997;47:719-22.

28. Hux JE, Melady MP, DeBoer D. Confidential prescriber feedback and education to improve antibiotic use in primary care: a controlled trial. CMAJ 1999;161:388-392.

29. van Duijn H, Kuyvenhoven M, Welschen I, den Ouden H, Slootweg A, Verheij T. Patients' and doctors' views on respiratory tract symptoms. Scand J Prim Health Care 2002;20:201-2.

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Summary

Introduction

The discovery of antibiotics (penicillin) by Alexander Fleming in 1928 triggered enormous progress in the field of medicine. However, as early as 1944 Fleming observed that some bacteria were able to destroy penicillin, and he warned that the misuse of antibiotics could lead to selection of resistant bacteria. This warning was lost in the first flush of the discovery of increasing numbers of antibiotics and the success of these medicines.

At the beginning of the 21st century, infectious diseases again cause more deaths as antibiotics lose their effectiveness. Over the last decade, the causative agent of the most frequent life-threatening bacterial infections, Streptococcus pneumoniae - or pneumococcus for short -, has become less sensitive to penicillin and other antibiotics. More than 30% of pneumococci isolated in Belgium are resistant to erytromycine and tetracycline, whereas more than 5% show full penicillin resistance.

This increase in bacterial resistance is associated with the increased use of antibiotics, both in animals and in humans. In the case of humans, 80% of antibiotics are prescribed by primary healthcare providers, that is outside the hospital, especially by general practitioners (GPs). The best way of preserving

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the effectiveness of antibiotics is to use them more appropriately, i.e. in cases where patients will actually benefit. The alternative of continuing to develop new antibiotics will only solve the problem of antibiotic resistance if the principles of judicious use of antibiotics are implemented at the same time. The growth in resistance is progressing faster than the development of newer antibiotics.

This dissertation aims to develop a management model enabling GPs to reduce the prescription of antibiotics without harming their patients. At the same time, our research addresses the very core of primary care, the screening function of general practice, with the missing of diagnoses as Scylla, and the excessive treatment of everyday complaints as Charybdis (Chapter I).

The filter function of general practice

General practice has an important role to play in the organization of quality health care. Its main characteristic is to screen various health problems in, on the one hand, self-limiting conditions or conditions to be dealt with in primary care, and, on the other, disorders that require a more specialist approach. For many, even well-known, complaints this function still needs an evidence base.

Missing diagnoses

The fact of working at low cost and with few technological means in order to deal with a wide array of health problems is an inherent feature in general practice. As a result, there is a limited diagnostic certainty. This also applies to the most common complaint, i.e. coughing. Respiratory tract infections (RTIs) are not easy to distinguish from other conditions such as asthma since patients complain about coughing in both cases. Furthermore, there is a low degree of certainty when differentiating between acute bronchitis and pneumonia, and between viral and bacterial infections. A bacterial pneumonia, however, can be a life-threatening condition, requiring antibiotics, and even admission into hospital.

As a result, the quest for evidence enabling GPs to exclude life-threatening conditions with more certainty should not centre on diagnoses that are difficult to make, such as acute bronchitis, but on symptoms like coughing, for which patients seek help.

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Excessive treatment of everyday complaints

For most conditions for which antibiotics are being used, there is no scientific evidence to support their actual benefit. For most patients, the use of an antibiotic in case of an acute cough has no benefit when compared with a placebo. Nevertheless, especially for this condition, (too) many and ever more expensive antibiotics are being prescribed. Apart form the high financial cost and the medicalising effect, this overuse results in an increase in anti-microbial resistance to the antibiotics available.

This dissertation aims to contribute to the development of effective strategies for a more appropriate use of antibiotics. Since coughing is one of the most common complaints in general practice, the appropriate use of antibiotics to treat coughs is a key area of action in order to tackle the resistance problem. Consequently, by describing, exploring and optimising the prescription of antibiotics for coughing we can safeguard a major development in the field of medicine, i.e. the use of antibiotics in the treatment of life-threatening infections. Examining how GPs can identify patients with coughing complaints who will (not) benefit from antibiotics, is another relevant element in this regard.

Part 1: Exploration and description

In the first part of the dissertation we explored the way GPs currently manage patients who consult them with complaints about coughing.

Qualitative part

In a qualitative study (Chapter II), we explored the diagnostic and therapeutic decisions by Flemish general practitioners regarding adult patients who consult them complaining about a cough as well as the determinants of their decisions by means of focus groups. Twenty-four GPs participated in four semi-structured group discussions centred on the following questions:

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1.You are consulted by one of your adult patients who complains about coughing. Which diagnoses come to mind?


3. You suspect an infection of the respiratory tract. Do you differentiate in any way? Which distinctions do you make?


The recordings of these focus groups were transcribed and subsequently analysed in accordance with the principles of “ qualitative content analysis” . All texts were coded according to the research questions. Interpretation of the coded texts allowed a classification of the codes and the establishment of relationships between the various codes or categories.

In the focus groups, GPs stated that they try to differentiate between infectious and non-infectious causes of coughing, and between various types of RTIs. The most important decision, however, is whether or not to prescribe antibiotics for patients in case of suspected RTI. In terms of the latter decision, we made a distinction between two kinds of determinants after analysis of all codes. Medical determinants, such as signs and symptoms, determine the probability of disease but offer little diagnostic certainty for the patients involved. Non-medical determinants, such as defensive medicine by the GP (doctor-related) and patient expectations (patient-related), help determine the threshold at which to prescribe an antibiotic as well.

Following the analysis of the different codes, hypotheses were set up regarding decisions made by GPs when faced with complaints about coughing and the determinants underlying their decisions:

• The first diagnosis to present itself to a GP is RTI. This diagnosis is reached independently of the patient. Other hypotheses emerge only if they are considered plausible as a result of knowledge of patient history.

• GPs ask routine questions to confirm only the most likely diagnoses. Explicitly ruling out other diagnoses is less often used in decision-making.

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• In suspected RTI, GPs want to make a distinction between clinical syndromes such as bronchitis and pneumonia, viral and bacterial RTI and upper and lower RTI. This cannot be achieved with certainty on the basis of medical history and clinical examination. Dealing with diagnostic uncertainty, GPs’ decisions are directed at whether or not to prescribe antibiotics.

• For this (therapeutic) decision, doctor- and patient-related factors also come into play. These factors give rise to a shift in the action thresholds in favour of antibiotics, a phenomenon explained by the “ Chagrin factor” . GPS regret less having unnecessarily prescribed antibiotics than not having prescribed any if afterwards it appears that they were necessary. In this context, ‘necessary’ does not only mean necessary for curing the patient, but also, for instance, to meet patient expectations and thus retain patient loyalty. The decision to prescribe antibiotics is better explained by both types of determinants than by the conventional diagnostic groups of RTIs.

Quantitative part

A questionnaire (Chapter III) was used to quantify and condense the determinants generated in the focus group study. More specifically, we assessed the extent to which GPs consider those determinants when making decisions in the case of suspected RTI in a coughing patient and how strongly the determinants act in favour of or against antibiotic treatment.

Of the 316 Flemish GPs who were sent the questionnaire, 200 replied, with 188 responses being eligible for analysis (59.5 % of overall response rate). Our sample, which included 65.9 % men and an average age of about 43, was typical of the Flemish GP population.

GPs seem to consider all the determinants included in the questionnaire. They nearly always consider 'lung auscultation', but also whether the patient has a fever, is coughing up (coloured) sputum, looks ill and whether s/he has a medical history of COPD or smoking. Moreover, they often watch out for ‘anything out of the ordinary’ . GPs pay less attention to 'non-medical reasons', whether they be patient- or doctor related.

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GPs felt that the deterioration of the general condition of the patient favoured treatment with antibiotics most . There were no items that argued strongly in favour or against treatment with antibiotics. Non-medical reasons support the prescription of antibiotic treatment, albeit to a lesser extent than medical factors.

Validation of qualitative and quantitative studies

In order to validate the focus group and questionnaire findings we recorded GP management of acute cough (Chapter IV).

Of the 85 GPs willing to participate in our intervention study (see Part II: Optimisation), 72 included an average of 10 consecutive adult patients who consulted them with acute cough between February and April of 2000 and 2001. They recorded medical as well as non-medical data, including the prescription of antibiotics and the GP's perception of requests for antibiotic treatment on the part of the patients.

These data also revealed that non-medical determinants may have a considerable effect on the decision whether or not to prescribe an antibiotic. After all, the fact that patients requested antibiotics proved to be an equally important, statistically significant, independent predictor of an antibiotic prescription, as were medical determinants, such as for example the presence of sputum. Good clinical practice guidelines and interventions to optimise the prescription of antibiotics have to take into account non-medical reasons such as the patient's request for antibiotics. In order to implement the recommended management approach, this has to fit in with the described, i.e. current, common practice.

Part 2. Optimisation

The second part of this dissertation provides recommendations for changing current practices and specifically for optimising the use of antibiotics for coughing in general practice. We conducted a prospective, cluster-randomised, controlled, ‘before-and-after’ study. The intervention was based upon a clinical practice guideline.

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Recommended management

A group of GPs drafted a guideline for the diagnostic and therapeutic management of acute cough. This text was based upon the available evidence, our own descriptive research, and on a consensus within the author group if evidence was lacking. The text was peer-reviewed by a multidisciplinary panel of experts and subsequently revised.

The revised guideline for acute cough includes the following key points:

• The guideline applies to patients, aged 12 years or older, whose most prominent complaint is acute cough with or without purulent sputum, not patients with recurrent or chronic cough, chronic obstructive pulmonary disease or patients that received antibiotic treatment in the preceding week.

• First, pneumonia, pulmonary embolism, left ventricular failure (pulmonary oedema), pneumothorax, aspiration and irritation by toxic agents should be ruled out by history and clinical examination. Although these are not frequent conditions and acute cough may not be the most prominent complaint, these potentially life-threatening conditions are treatable. They should not be missed.

• If a cause other than a respiratory infection is present (for example asthma, gastro-oesophageal reflux disease, ACE-inhibitors) management needs to be adjusted accordingly. Even though such conditions may not be obvious in a first encounter, they should not be ruled out.

• If eventually a respiratory infection seems to be the most likely cause, it is not feasible to distinguish between viral and bacterial infections. Nevertheless, the decision whether to prescribe antibiotics has to be made. Antibiotics are only needed for patients whose immunity has been compromised.

• Besides the scientific arguments, we also recommend integrating the GP’ s own agenda as well as that of the patient in the final therapeutic decision.

An educational package was developed in accordance with the guideline. In addition, this text was further elaborated according to a standardized

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methodology defined by the Scientific College of Flemish General Practitioners (WVVH) to become the guideline for good clinical practice: acute cough (Chapter V).

Implementation

Participants in the questionnaire study were asked whether they were willing to join an intervention study including pre- and post-assessment of the diagnostic and therapeutic management of coughing (Chapter VI). The pre-test of the planned intervention study consisted of the previously mentioned registration of the management of acute cough in the period February-April 2000. Before the intervention, all 85 GPs who agreed to participate were divided at random into two study groups.

Our intervention was preceded by a nation-wide public awareness campaign, "Antibiotics: Use them less often, but better." The campaign included TV and radio announcements, booklets and leaflets raising public awareness about the overconsumption and misuse of antibiotics, the resulting resistance problem and the self-limiting character of the most frequent infections.

In January 2001, all GPs in the intervention group received the guideline by mail and were contacted by a facilitator to arrange an outreach visit at their practice. They were asked to read through the guideline in advance of that visit. During the 10-20 minute visit, the educational package was presented. This presentation was adjusted to the needs or observations expressed by the GP. Once all GPs had been visited, each received a written reminder of the key recommendations by post.

Immediately after the intervention period, GPs started the post-test. This consisted of recording data regarding consecutive patients with acute cough in the period February-April 2001. After the first consultation at the GP's practice, the patients involved each day recorded the presence of coughing, sputum, fever, sore throat, headache, muscle ache, runny nose, loss of appetite, shortness of breath, thoracic pain, as well as information about their health status and level of activity. When assessing the intervention, we took into account the amount and cost of the antibiotics prescribed and the time it took for patient symptoms to disappear (symptom resolution).

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Results

Of the 42 GPs in the intervention group, 36 received the entire intervention. Fifty-six GPs, 27 in the intervention group, 29 in the control group, participated in both pre- and post-tests. They included 1503 patients eligible for analysis. Patient diaries of 1009 patients eligible for analysis were available. Taking into account clustering of patients (Generalised Estimating Equations analysis), we arrived at the following findings:

Use of antibiotics. The antibiotic prescription rates for acute cough in the intervention group and the control group were 157/365 (43.0%) and 168/445 (37.8%) in the pre-test and 80/292 (27,4%) and 115/401 (28.7%) in the post-test, respectively. When antibiotics were prescribed, these were macrolides, cephalosporines or combinations of penicillins and beta-lactamase inhibitors, i.e. the non-recommended antibiotics, in 94/157 (59.9%) and 105/168 (62.5%), and 37/80 (46.3%) and 72/115 (62.6%), respectively. Without adjustment for the other registered variables, these prescription rates did not differ between the intervention and the control groups, neither in the pre-test nor in the post-test.

Although by March 2001 the public awareness campaign no longer had an effect on the use of antibiotics, there was a significant difference between pre- and post-test prescriptions (P=0.005 and P=0.03) in both groups. In cases where antibiotics were prescribed, only the GPs in the intervention group prescribed 14% less of the non-recommended antibiotics (P=0.06 vs. P=0.84).

Unlike the pre- and post-test comparison (cf. the public awareness campaign), the comparison of the intervention and control groups allows a convincing adjustment for the substantial differences in the incidence of acute respiratory infections between 2000 and 2001. If, in addition, we adjust for differences in the other registered variables between patients in both groups and assume the antibiotic prescription rates to be equal in both study groups in the pre-test phase, only GPs in the intervention group prescribed significantly fewer antibiotics in the post-test than those in the control group (ORadj = 0.55 (0.36-0.85)), and compared with their own prescriptions in the pre-test period (ORadj = 0.55 (0.38-0.80)).

The intervention not only influenced the number of antibiotic prescriptions, but also resulted in a better choice of antibiotics for acute cough patients. Since

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there was a significant pre- and post-test difference only in the intervention group, the public awareness campaign no longer appears to have had an effect on post-test antibiotic prescription.

Cost of antibiotics. During the pre-test, the mean medication cost from the point of view of the National Sickness and Invalidity Insurance Institute (NSIII) was � 12 in the intervention group and � 11 in the control group. In the post-test this dropped to � 8 in the intervention group, and � 9 in the control group.

By limiting the analysis to the subset of patients who were prescribed an antibiotic, the mean medication cost increased to � 22 in the intervention group and � 21 in the control group. This dropped significantly in the intervention group in the post-test, i.e. � 16, in comparison with the control group’ s � 21 (Mean Difference (MD)adj (95%CI) = -6.89 (-11.77 - (-2.02) �) and with the pre-test figure of � 22 (MDadj = -6.11 (-9.97 - (-2.24) �)

Time to symptom resolution. As far as the use and type of antibiotics are concerned, the same conclusions can be drawn from the subset of patients who completed diaries. Since we are especially interested in public health, the outcome for the patient is of paramount importance. This is why we investigated whether fewer and different antibiotics influenced the time to symptom resolution. However, we found no significant difference between the intervention and control groups in terms of the time to resolution of all symptoms.

Part 3. The patients

In the decision to prescribe antibiotics, patient-related determinants also play a role. International differences in outpatient antibiotic consumption might correlate with differences in patient attitudes. Moreover, the problem of antibiotic overuse is an international problem, which requires international interventions and provides opportunities for international research.

By means of an international postal questionnaire study, in collaboration with Utrecht (the Netherlands), Cardiff (UK), and Barcelona (Spain), 400 patients in

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each country were asked about their views on respiratory complaints and antibiotic use (Chapter VII). Belgian patients reported a higher need for consulting a general practitioner when faced with respiratory symptoms and considered these disorders to be more serious and less self-limiting than did their Dutch and UK counterparts. These results might partially explain the differences in antibiotic use between respondents. Patient counselling should specifically highlight the benign and self-limiting nature of the vast majority of respiratory tract complaints.

Conclusion

This dissertation clearly shows that the prescription of antibiotics for the most frequent (RTI) complaint in general practice, i.e. coughing, requires optimisation (Chapter VIII). This can be achieved by means of a guideline for good clinical practice, provided the guideline fits in with current common practice and is implemented by means of academic detailing.

In doing so, we can achieve the goals of the public awareness campaign: ” Antibiotics: Use them less often, but better” . GPs not only prescribed less, but also better because of our intervention. Furthermore, this did not happen at the expense of patient recovery.

There is significant interaction between doctor and patient in the decision to prescribe antibiotics. So, in order to develop effective strategies aimed at a more appropriate use of antibiotics, we need to focus on both the doctor and the patient and, in particular, on doctor-patient communication. More specifically, the discussion of patient expectations about antibiotic prescription and the (in)appropriateness of it, supported by relevant and evidence-based recommendations is the key to success for the GP. Likewise, interventions should focus on both the prescribers and the consumers. Therefore we advise a combination of interventions such as a national public awareness campaign and an intervention like ours, which directly addressed GPs.

Finally, interventions to change behaviour - in this case the prescription behaviour - cannot claim to have a lasting effect. They need to be repeated to preserve the effectiveness of antibiotics in future health care.

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Antibiotica voor hoesten in de huisartspraktijk:

Samenvatting

Inleiding

De ontdekking van antibiotica (penicilline) door Alexander Fleming in 1928 betekende een enorme vooruitgang op het gebied van de geneeskunde. Maar reeds in 1944 noteerde Fleming dat sommige bacteriën in staat waren penicilline te vernietigen, en hij waarschuwde dat misbruik van antibiotica kon leiden tot selectie van resistente bacteriën. Deze waarschuwing ging verloren in de roes van de ontdekking van steeds maar nieuwe soorten antibiotica en het succes van deze geneesmiddelen.

Aan het begin van de 21e eeuw zijn we echter zover dat infectieziekten opnieuw een hogere tol aan mensenlevens eisen omdat antibiotica hun doeltreffendheid verliezen. Zo is de verwekker van de meest frequente levensbedreigende bacteriële infecties, de Streptococcus pneumoniae of kortweg de pneumococ, gedurende het laatste decennium steeds minder gevoelig geworden voor penicilline en andere antibiotica. Meer dan 30% van de in België geïsoleerde pneumococcen zijn resistent tegen erythromycine en tetracycline, meer dan 5% vertoont volledige penicilline-resistentie.

Deze toename van de bacteriële resistentie hangt samen met het toegenomen antibioticumgebruik, zowel bij dieren als bij mensen. Bij mensen worden 80%

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van de gebruikte antibiotica voorgeschreven in de ambulante praktijk, d.w.z. buiten het ziekenhuis, voornamelijk door huisartsen. De beste optie om de doeltreffendheid van antibiotica te bewaren, is ze doelmatiger te gebruiken, d.w.z. daar waar ze patiënten voordelen bieden. Het alternatief, om steeds nieuwere antibiotica te ontwikkelen, zal het probleem van antibioticaresistentie ook enkel oplossen, als tegelijkertijd gewerkt wordt aan een doelmatiger gebruik. Resistentie ontwikkelt zich namelijk sneller dan de ontwikkeling van nieuwere antibiotica.

Dit proefschrift wil een beleidsmodel opstellen dat de huisarts toelaat het voorschrijven van antibiotica te reduceren zonder dat dit ten koste gaat van zijn of haar patiënten. Tegelijkertijd raakt het aan het wezen van de huisartsgeneeskunde, de filterfunctie van de huisartsgeneeskunde, met het missen van diagnoses als Scylla en het overbehandelen van alledaagse klachten als Charybdis (Hoofdstuk I).

De filterfunctie van de huisartsgeneeskunde

De huisartsgeneeskunde speelt een belangrijke rol bij de organisatie van een kwaliteitsvolle gezondheidszorg. Haar voornaamste eigenschap is het filteren van allerlei gezondheidsklachten in zelflimiterende of in eigen beheer op te lossen problemen en in aandoeningen die een meer gespecialiseerde aanpak vereisen. Voor veel, zelfs goed gekende aandoeningen dient deze functie echter nog met wetenschappelijke evidentie onderbouwd te worden.

Het missen van diagnoses

Het is eigen aan de huisartsgeneeskunde dat veel klachten worden uitgewerkt aan lage kostprijs en met weinig technologie. De zekerheid waarmee diagnosen worden gesteld is derhalve beperkt. Ook voor de meest voorkomende klacht: hoesten, is dit het geval. Het is niet eenvoudig luchtweginfecties te onderscheiden van andere aandoeningen die zich zoals bijvoorbeeld astma ook presenteren met hoestklachten. Bovendien is er onvoldoende zekerheid om te zeggen dat het om een acute bronchitis gaat en niet om een pneumonie, laat staan dat een virus en niet een bacterie de oorzaak is van de klachten. Een bacteriële pneumonie is nochtans levensbedreigend en vereist vooralsnog een behandeling met een antibioticum, eventueel zelfs hospitalisatie.

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Zoeken naar wetenschappelijke evidentie die huisartsen toelaat met meer zekerheid een levensbedreigende aandoening uit te sluiten, dient dan ook niet te vertrekken vanuit voor huisartsen moeilijk te stellen diagnoses, zoals bijvoorbeeld acute bronchitis, maar vanuit de klachten waarmee deze zich presenteren, zoals bijvoorbeeld hoestklachten.

Het overbehandelen van alledaagse klachten

Wetenschappelijke onderbouwing van de voordelen van een antibioticum ontbreekt bij het merendeel van de aandoeningen waarvoor antibiotica worden gebruikt. Wat hoestklachten betreft, is er evidentie dat antibiotica meestal geen voordelen bieden t.o.v. placebo. Toch worden vooral voor deze klachten (te) veel en steeds duurdere antibiotica voorgeschreven. En 80 % van die voorschriften levert de huisarts af. Naast de enorme kostprijs hiervan en de medicalisering van hoestklachten heeft dit overgebruik vooral een toename van de bacteriële resistentie voor de beschikbare antibiotica tot gevolg.

Dit proefschrift draagt bij tot de ontwikkeling van doeltreffende strategieën die een doelmatiger gebruik van antibiotica beogen. Aangezien hoesten tot de frequentste klachten in de huisartspraktijk behoort, is het nastreven van een doelmatiger gebruik van antibiotica bij hoestklachten een belangrijk aangrijpingspunt om het resistentie probleem het hoofd te bieden. Aldus kan een belangrijke vooruitgang op geneeskundig gebied, met name de behandeling van levensbedreigende infecties met antibiotica gevrijwaard worden. Onderzoeken hoe huisartsen patiënten met hoestklachten kunnen identificeren die (geen) baat hebben bij een antibioticum speelt daarin eveneens een belangrijke rol.

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Deel 1: Beschrijven en exploreren

In het eerste deel van dit proefschrift exploreerden we het huidige beleid van huisartsen bij patiënten die met hoestklachten consulteren.

Kwalitatief deel

In een kwalitatief onderzoek met focusgroepen (Hoofdstuk II) hebben we de diagnostische en therapeutische beslissingen van huisartsen bij patiënten met hoestklachten geëxpliciteerd en de determinanten van deze beslissingen nagegaan. Vierentwintig huisartsen namen deel aan vier groepsdiscussies, gestructureerd rond de volgende sleutelvragen: 1. Voor u staat een volwassen patiënt uit uw praktijk met als

contactreden/klacht “ hoesten” . Welke diagnoses komen in jullie op? 2. Hoe maakt u het onderscheid tussen de verschillende mogelijke diagnoses? 3. U vermoedt dat uw patiënt een luchtweginfectie heeft. Maakt u daarin een

onderscheid? Welk onderscheid? 4. Hoe maakt u het onderscheid tussen de verschillende mogelijkheden bij uw

patiënt?

De bandopnames van deze focusgroepen werden uitgeschreven en geanalyseerd volgens de methode van ‘qualitative content analysis’ . Alle tekstfragmenten werden gecodeerd in functie van de onderzoeksvragen. De interpretatie van de gecodeerde tekstfragmenten liet toe de codes te categoriseren en verbanden te leggen tussen verschillende codes of categorieën.

De huisartsen verwoordden in de focusgroepen dat ze beslissen of hoestklachten al dan niet een infectieuze oorzaak hebben en dat ze trachten verschillende luchtweginfecties te onderscheiden. De belangrijkste beslissing is echter het al dan niet voorschrijven van antibiotica bij de patiënten waarbij ze een luchtweginfectie vermoeden. Voor deze laatste beslissing onderscheidden we na de analyse van alle codes twee soorten determinanten. Medische determinanten, zoals klinische tekens en symptomen, bepalen de kans op ziekte, maar bieden bij deze patiënten weinig diagnostische zekerheid. Niet-medische determinanten zoals defensief handelen door de huisarts (artsgebonden) en de verwachtingen van patiënten (patiëntgebonden) bepalen mee de drempel om een antibioticum voor te schrijven, vaak ten voordele van antibiotica.

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Na de analyse van de verschillende codes werden hypothesen gegenereerd over de beslissingen die huisartsen nemen bij patiënten met hoestklachten en de determinanten die deze beslissingen bepalen: 1. Huisartsen denken in eerste instantie en onafhankelijk van de patiënt aan

een luchtweginfectie. Andere hypothesen komen slechts aan bod als die aannemelijk zijn vanuit de voorkennis over de patiënt.

2. Huisartsen stellen routinevragen enkel om de meest waarschijnlijke diagnosen aan te tonen. Het expliciet uitsluiten van andere diagnosen wordt minder vaak gehanteerd in het besliskundig proces.

3. Bij vermoeden van een luchtweginfectie willen huisartsen een onderscheid maken tussen klinische entiteiten zoals bronchitis en pneumonie, virale en bacteriële luchtweginfecties en infecties van de bovenste en onderste luchtwegen. Met argumenten uit de anamnese en het klinisch onderzoek kan dat niet met zekerheid. Huisartsen dienen om te gaan met diagnostische onzekerheid en hun beslissing spitst zich dan ook toe op het al dan niet voorschrijven van antibiotica.

4. Bij deze (therapeutische) beslissing spelen artsen patiëntgebonden factoren ook een rol. Deze factoren bepalen een verschuiving van de actiedrempels ten voordele van antibiotica. De ‘Chagrin factor’ verklaart dit fenomeen. Huisartsen ervaren minder spijt als ze onnodig antibiotica hebben voorgeschreven, dan wanneer ze geen antibiotica hebben voorgeschreven, terwijl nadien zou kunnen blijken dat het nodig was. ‘Nodig’ betekent hier niet alleen nodig om de patiënt te genezen, maar ook om bijvoorbeeld geen patiënten te verliezen aan niet-ingeloste verwachtingen. De beslissing om antibiotica voor te schrijven wordt beter verklaard door beide soorten determinanten dan door de conventionele diagnostische groepen luchtweginfecties.

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Kwantitatief deel

Met een enquête (Hoofdstuk III) hebben we vervolgens de bevindingen van het focusgroepen onderzoek gekwantificeerd en met behulp van factoranalyse gecondenseerd. We gingen meer bepaald na in welke mate huisartsen bij patiënten met hoestklachten en het vermoeden van een luchtweginfectie letten op een selectie van de determinanten uit het focusgroepen onderzoek. Daar naast werd aan huisartsen gevraagd hoe sterk deze determinanten volgens hen pleiten ‘voor’ of ‘tegen’ het behandelen met een antibioticum. Van de 316 aangeschreven Vlaamse huisartsen hebben er 200 geantwoord, en van 188 (59.5 %) was de respons bruikbaar. Met bijna twee derde mannen (65.9 %) en een gemiddelde leeftijd van bijna 43 jaar was onze steekproef vergelijkbaar met de Vlaamse huisartsenpopulatie.

De huisartsen letten op alle determinanten geïncludeerd in de vragenlijst. Bijna altijd hielden ze rekening met het resultaat van ‘de longauscultatie’ - maar ook of er (gekleurd) sputum wordt opgehoest, of er koorts is, de patiënt bekend is met COPD of rookt, er ziek uitziet of kortademig is. Ze letten vaak op ‘gegevens om het onderscheid te maken tussen pluis en niet-pluis situaties’ , beiden zijn medische determinanten, en in mindere mate op ‘niet-medische determinanten’ , hetzij arts- hetzij patiëntgebonden.

De achteruitgang van de algemene toestand van de patiënt pleitte volgens de huisartsen sterk voor een behandeling met een antibioticum. Voor het overige vonden ze dat niets sterk voor of tegen een behandeling met een antibioticum pleitte. Zoals ‘medische determinanten’ pleitten ook ‘niet-medische determinanten’ voor het behandelen met een antibioticum, maar in mindere mate.

Validatie kwalitatief en kwantitatief onderzoek

Met een registratie van praktijkgegevens (Hoofdstuk IV) hebben we vervolgens gevalideerd wat de huisartsen in het focusgroepen onderzoek zegden en wat ze antwoordden in het vragenlijsten onderzoek. Van de 85 huisartsen bereid tot deelname aan het interventie onderzoek (zie Deel 2. Optimaliseren) hebben 72 huisartsen gemiddeld 10 opeenvolgende volwassen patiënten geïncludeerd die hen consulteerden met acute hoestklachten in de periode februari-april 2000. Zij registreerden zowel medische als niet-medische gegevens, waaronder respectievelijk het voorschrijven van antibiotica en de

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inschatting door de huisarts van de vraag van de patiënt om een behandeling met een antibioticum.

Ook uit deze gegevens bleek dat niet-medische determinanten van belang kunnen zijn bij de beslissing al dan niet een antibioticum voor te schrijven. Zo was de vraag van de patiënt om antibiotica een even belangrijke, statistisch significante en onafhankelijke voorspeller van een antibioticumvoorschrift, als medische determinanten zoals bijvoorbeeld de aanwezigheid van sputum.

Aanbevelingen en interventies om het voorschrijven van antibiotica te optimaliseren dienen ook rekening te houden met niet-medische factoren, zoals de vraag van de patiënt. Om het aanbevolen beleid te implementeren sluit dit immers best aan bij de beschreven, c.q. gangbare praktijk.

Deel 2. Optimaliseren

In een tweede deel van dit proefschrift wilden we het beschreven beleid trachten te beïnvloeden, meer bepaald het gebruik van antibiotica bij de klacht ‘hoesten’ in de huisartspraktijk optimaliseren. Hier was het opzet een gecontroleerd cluster gerandomiseerd interventie onderzoek met voor- en nameting. De interventie was gebaseerd op een aanbeveling.

Het aanbevolen beleid

Voor de diagnostische en therapeutische aanpak van acute hoestklachten werd een eerste aanbevelingstekst ontwikkeld door een auteursgroep van huisartsen. Deze aanbevelingstekst was gebaseerd op de beschikbare onderzoeksliteratuur, eigen onderzoek en op consensus binnen de auteursgroep indien onderzoeksbewijs ontbrak. De aanbevelingstekst werd ter beoordeling voorgelegd aan experten huisartsen, pneumologen en microbiologen en vervolgens aangepast.

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In de aangepaste aanbevelingstekst ‘acute hoest’ werden volgende sleutelboodschappen geformuleerd: �� Deze aanbeveling betreft patiënten van 12 jaar of ouder met als

voornaamste klacht acute hoest al dan niet met purulent sputum; patiënten met chronisch obstructief longlijder, patiënten met recidiverende of chronische hoestklachten of patiënten die in de voorafgaande week met antibiotica zijn behandeld, worden in deze aanbeveling buiten beschouwing gelaten.

�� In een eerste stap dienen met anamnese en klinisch onderzoek behandelbare aandoeningen, waarbij onmiddellijk levensgevaar bestaat, uitgesloten te worden, ook al zijn ze weinig waarschijnlijk: longembolie, congestief hartfalen (longoedeem), pneumothorax, aspiratie en pneumonie.

�� Is in een tweede stap een niet levensbedreigende en niet-infectieuze oorzaak duidelijk, dient het beleid hieraan aangepast. Meestal echter zijn deze diagnosen niet duidelijk bij een eerste contact. Ze dienen niet expliciet aangetoond of uitgesloten in dat eerste consult.

�� Is tenslotte een luchtweginfectie de meest waarschijnlijke diagnose, dan is het niet haalbaar virale van bacteriële luchtweginfecties te onderscheiden. Er dient wel beslist of antibiotica nodig zijn. Deze zijn enkel nodig bij patiënten met gecomprommiteerde immuniteit: bv. oncologische patiënten, patiënten met diabetes mellitus

�� In de uiteindelijke therapeutische beslissing dienen bovendien de ideeën van de patiënt en die van de huisarts geïntegreerd te worden.

Op basis van deze aanbevelingstekst werd dan een deskundigheidsbevorder-ingspakket (pakket DKB) ontwikkeld. Bovendien is deze aanbevelingstekst volgens een door de Wetenschappelijke Vereniging van Vlaamse Huisartsen (WVVH) vastgelegde procedure verder uitgewerkt tot de aanbeveling voor goede medische praktijkvoering: Acute Hoest (Hoofdstuk V).

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De implementatie

De deelnemers aan het vragenlijsten onderzoek werd gevraagd of ze bereid waren deel te nemen aan een interventie onderzoek met voor- en nameting i.v.m. het diagnostisch en therapeutisch beleid bij hoestklachten (Hoofdstuk VI). De voormeting van het geplande interventie onderzoek bestond uit het hoger vermeld registratie onderzoek in de periode februari-april 2000. De 85 huisartsen die deelname toezegden werden vóór de interventie ‘at random’ verdeeld in twee groepen.

Juist voor onze interventie, in december 2000, startte de federale overheid een nationale mediacampagne “ Antibiotica, minder vaak en beter” . Met spots op radio en televisie, affiches en folders richtte deze campagne zich tot de bevolking met informatie over het overmatig en ondoelmatig gebruik van antibiotica, de gevolgen hiervan voor de ontwikkeling van resistentie, en het zelf limiterend karakter van de meest frequente infecties.

Alle huisartsen in de interventiegroep ontvingen in januari 2001 de aanbevelingstekst ‘acute hoest’ per post en werden door een artsenbezoeker gecontacteerd om een praktijkbezoek te plannen. De artsen werd gevraagd de aanbevelingstekst vooraf door te nemen. Tijdens het bezoek presenteerde de daartoe getrainde artsenbezoeker gedurende 10 tot 20 minuten het pakket DKB, aangepast aan de noden en opmerkingen welke de arts te kennen gaf (academic detailing). Wanneer alle huisartsen bezocht waren, ontvingen ze een herinneringsbrief met de sleutelboodschappen per post.

Onmiddellijk na de interventieperiode startten de huisartsen de nameting. Deze bestond uit het registreren van gegevens bij opeenvolgende patiënten met acute hoestklachten in de periode februari-april 2001. De geïncludeerde patiënten registreerden elke dag vanaf het eerste consult bij de huisarts gegevens over hoesten, slijmen, koorts, keelpijn, hoofdpijn, spierpijn, neusloop, verminderde eetlust, kortademigheid, pijn op de borst, alsook over hun algemene gezondheidstoestand en graad van activiteit. Voor het beoordelen van de interventie hanteerden we het volume en de kost van de voorgeschreven antibiotica, alsook de duur tot het verdwijnen van de symptomen bij patiënten (symptoomresolutie) als uitkomstmaten.

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De resultaten

Van de 42 huisartsen in de interventiegroep ontvingen er 36 de volledige interventie. 56 huisartsen, 27 in de interventie en 29 in de controle groep, namen deel aan de voor- en de nameting. De huisartsen includeerden 1503 patiënten geschikt voor analyse. Van 1009 patiënten (67%) beschikken we over hun registratieformulieren. Deze patiënten verschilden niet van de andere patiënten, zonder patiënten-registratieformulier, wat betreft de door de huisartsen geregistreerde gegevens. Rekening houdend met de clustering van de patiënten (Generalised Estimating Equations analyse) kwamen we tot volgende uitkomsten:

Volume antibioticavoorschriften. De proporties antibioticavoorschriften bij acute hoest patiënten in de interventie en controle groep tijdens de voor-, respectievelijk tijdens de nameting zijn 157/365 (43.0%) en 168/445 (37.8%), respectievelijk 80/292 (27,4%) en 115/401 (28.7%). Als er antibiotica werden voorgeschreven, gingen het in respectievelijk 94 (59.9%), 105 (62.5%), 37 (46.3%) en 72 (62.6%) om macroliden, cephalosporinen of combinaties van amoxicilline en clavulaanzuur, c.q. de niet aanbevolen antibiotica. Zonder correctie voor de andere geregistreerde variabelen zijn er geen verschillen tussen de interventie en de controle groep, noch tijdens de voor-, noch tijdens de nameting.

Ondanks het feit dat ook de nationale mediacampagne in België in maart 2001 geen effect meer had op het antibioticagebruik is er in beide groepen wel een significant verschil tussen de voor- en de nameting wat het aantal voorschriften betreft (P=0.005 vs. P=0.03). Als er antibiotica werden voorgeschreven, schreven enkel de huisartsen van de interventie groep 14% minder de niet aanbevolen antibiotica (P=0.06 vs. P=0.84).

In tegenstelling tot de vergelijking tussen voor- en nameting, cf. de nationale campagne, laat de vergelijking met een controle groep toe overtuigend te corrigeren voor de aanzienlijke verschillen in incidentie van acute luchtweginfecties tussen 2000 en 2001. Corrigeren we bovendien voor verschillen tussen de patiënten in de respectievelijke groepen betreffende de andere geregistreerde variabelen en gaan we uit van gelijke proporties antibioticavoorschriften en gelijke antibiotica keuze tussen interventie en controle groep tijdens de voormeting, dan schrijven enkel de huisartsen in de interventiegroep significant minder antibiotica voor tijdens de nameting

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vergeleken met de controle groep (OR (95% BI): 0.55 (0.36-0.85)), en vergeleken met hun voormeting (0.55 (0.38-0.80)). En als ze antibiotica voorschrijven zijn dit ook meer de in de aanbeveling voorgestelde antibiotica vergeleken met de controle groep (1.87 (0.93–3.76), en significant meer vergeleken met hun voormeting (1.99 (1.16-3.42)).

De interventie beïnvloedde niet alleen het aantal antibioticum voorschriften, maar resulteerde even goed in een betere keuze van het antibioticum voor acute hoest patiënten. Aangezien er enkel voor de interventie groep een significant verschil is tussen voor- en nameting en niet in de controle groep, lijkt de nationale campagne ook geen effect meer gehad te hebben op het voorschrijven van antibiotica voor acute hoest tijdens de nameting.

Kost antibioticavoorschriften. Tijdens de voormeting bedroeg de gemiddelde medicatiekost vanuit het perspectief van het Rijksinstituut voor Ziekte- en Invaliditeitsverzekering (RIZIV) � 12 in de interventie groep en � 11 in de controle groep. Tijdens de nameting was dit minder, � 8 in de interventiegroep en � 9 in de controle groep. Beperken we de analyse tot de patiënten die antibiotica voorgeschreven kregen, dan bedroeg tijdens de voormeting de gemiddelde medicatiekost � 22 in de interventiegroep en � 21 in de controle groep. Tijdens de nameting was dit significant minder in de interventie groep, � 16 , vergeleken met de controle groep (� 21) en met de voormeting (22).

Duur tot symptoomresolutie. Aangezien ons vooral de volksgezondheid interesseert zijn de uitkomsten van de patiënten ook een belangrijke, zoniet de belangrijkste, uitkomstmaat. We gingen daarom na of minder en andere antibioticavoorschriften bij acute hoest patiënten de duur tot symptoomresolutie beïnvloedden, maar vonden geen significant verschil tussen controle- en interventie groep wat betreft de resolutie van alle symptomen samen.

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Deel 3. De patiënten.

Bij de beslissing antibiotica voor te schrijven spelen ook patiëntgebonden determinanten een rol. Zo houden internationale verschillen in antibiotica-gebruik mogelijk verband met verschillen in opvattingen van patiënten. Bovendien is het overgebruik van antibiotica een internationaal probleem, dat internationale interventies noodzakelijk maakt en zich leent tot internationaal onderzoek.

Met een internationale post-enquête, in samenwerking met Utrecht (Nederland), Cardiff (Verenigd Koninkrijk) en Barcelona (Spanje), zijn per land 400 patiënten gevraagd naar hun opvattingen over luchtwegklachten en antibioticagebruik (Hoofdstuk VII). Belgische patiënten ervaren LWIs als ernstiger, eerder als een reden om een arts te raadplegen en minder als zelflimiterend dan Nederlandse patiënten en patiënten uit het Verenigd Koninkrijk. Deze resultaten verklaren de verschillen in antibioticagebruik tussen de respondenten ten dele. Voorlichting van patiënten dient zich voornamelijk te richten op het over het algemeen banale en zelflimiterende karakter van luchtwegklachten.

Tot besluit

Dit proefschrift heeft aangetoond dat het voorschrijven van antibiotica bij de meeste frequente klacht (voor luchtweginfecties) in de huisartspraktijk, hoesten, geoptimaliseerd dient te worden (Hoofdstuk VIII). Dit kan op basis van een aanbeveling voor goede medische praktijkvoering als deze aansluit bij de gangbare praktijk en wordt geïmplementeerd door middel van individuele artsenbezoeken (academic detailing).

Doelstellingen zoals geformuleerd voor de nationale campagne “ Antibiotica, minder vaak en beter” werden op die manier bereikt. Huisartsen schreven niet alleen minder, maar ook beter voor ten gevolge van onze interventie. Bovendien ging dit niet ten koste van de genezing van de patiënten.

Bij de beslissing al dan niet antibiotica voor te schrijven is er een belangrijke interactie tussen arts en patiënt. Om doeltreffende strategieën te ontwikkelen

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die een doelmatiger gebruik van antibiotica beogen, dienen we dus zowel aandacht te hebben voor de arts als voor de patiënt, en in het bijzonder voor de arts-patiënt communicatie. Meer bepaald het bespreken van de verwachtingen van de patiënt inzake een antibioticum voorschrift en het (on)nut hiervan, ondersteund door relevante en onderbouwde aanbevelingen, is voor de huisarts de sleutel tot succes. Ook de interventies zelf richten zich wellicht bij voorkeur op de voorschrijvers en op de gebruikers. Het lijkt ons daarom erg raadzaam interventies zoals de nationale campagne naar het publiek en onze interventie naar de huisartsen te combineren.

Tenslotte kunnen interventies om gedrag, hier het voorschrijfgedrag, te veranderen geen blijvend effect claimen. Ze dienen dus ook regelmatig herhaald te worden, om de doeltreffendheid van antibiotica voor de toekomstige gezondheidszorg te behouden.

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Curriculum Vitae

Samuel Jules Adeline Coenen was born in Antwerp, Belgium, May 21 1972. In secondary school he studied Latin and Greek (St. Xaverius College 1990: cum Laude). He graduated as a Candidate in Medical Sciences from the University of Antwerp (RUCA 1993: Summa cum Laude; a 3-year study programme), and as Medical Doctor (UIA 1997: Summa cum Laude; a 4-year study programme). His Master’ s thesis was on the diagnostic value of history and clinical examination for the diagnosis of respiratory tract infections. In stead of continuing his professional training as a general practitioner, he choose to focus on research in general practice for which he was granted a Fellowship as Research-assistant of the Fund for Scientific Research-Flanders (1997-1999, and renewed 1999-2002). His research focused on the exploration, description and optimisation of antibiotic prescribing for acute cough in the context of increasing antimicrobial resistance. In the mean time he supervised thesis students and occasionally lectured at the University of Antwerp. In the Doctoral Study Programme for Ph.D. students in Medical Science he made himself familiar with subjects ranging from statistics over evidence based medicine and (qualitative) research in general practice to the philosophy of science, from scientific reporting in English and French over Powerpoint to webauthoring, and, even more universalist, from the monetary union over the financial world crisis to investments, emotional intelligence and the Socratic conversation… To date, he (co-)authored over 20 contributions in (inter)national peer-reviewed journals (a detailed list is included in this book) and gave about 20 oral presentations at (inter)national conferences. He received the Specia-prize for Excellence during Medical Studies (1997), the ADVISA-prize for Young Researcher in General Practice (2000), the Pharmacia Award for Flemish Research in General Practice (2001), and was nominated for the Special Equip Quality Improvement Prize (2002) and the Pharmacia Corporation-prize UA Antwerp (2002). He was granted funding by the Small Project Fund of the Research Council of the University of Antwerp (1998), the Scientific College for Flemish General Practitioners (WVVH) (2000) and the Special Projects Fund of the European Society of General Practice/Family Medicine (2001). He is currently working at the Department of General Practice as a research assistant of the University of Antwerp, co-authoring the Five-Year Plan of the Belgian Antibiotic Policy Coordination Committee (BAPCOC), member of the steering committee guideline development of the WVVH, and member of the editorial staff of the journal of

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the WVVH, Huisarts Nu. He occasionally reviews manuscripts for international peer-reviewed journals and is (co-)author of WVVH guideline for acute cough and the BAPCOC guideline for lower respiratory tract infections.

He is married to Sylvie Van Bylen and the father of Seppe (°1998) and Lieselotte (°1999).

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List of Publications

In national peer reviewed journals - Coenen S. Antibiotica voor acute hoest bij volwassenen? Bespreking van

Fahey T et al. Quantitative systematic review of randomised controlled trials comparing antibiotic with placebo for acute cough in adults. BMJ 1998;316:906-10, in Huisarts Nu (MINERVA) 1999;2:174-6 (Rechtzetting Huisarts Nu (MINERVA) 1999;2:220).

- Coenen S. Steroïden voor nachtelijke hoest bij kinderen. Bespreking van Davies MJ et al. Persistent nocturnal cough: randomised controlled trial of high dose inhaled corticosteroid. Arch Child Dis 1999;81:38-44, in Huisarts Nu (MINERVA) 2000;8:376-7.

- Coenen S, Van Royen P, Vermeire E, Hermann I, Denekens J. Antibiotica bij hoestklachten in de huisartsenpraktijk: een kwalitatief besliskundig onderzoek.Huisarts nu 2001;30:390-7.

- Coenen S. Antibiotica voor acute hoest: tijd voor actie [Editoriaal]? Huisarts Nu 2002;31:388-9.

- Coenen S, Van Royen P, Van Poeck K, Michels J, Dieleman P, Lemoyne S, Denekens J. Aanbeveling voor goede medische praktijkvoering: Acute Hoest. Huisarts Nu 2002;31:391-411.

- Coenen S, Michiels B, Van Royen P, Van der Auwera JC, Denekens J. Antibiotica voor hoestklachten in de huisartspraktijk: determinanten van het voorschrijfgedrag. Huisarts Nu 2003;32: 180-9��

- Coenen S. Azithromycine en acute bronchitis. Bespreking van Evans A et al. Azithromycin for acute bronchitis: a randomised, double-blind, controlled trial. Lancet 2002;359:1648-54, in Minerva 2003;2:45-6.

In international peer reviewed journals

As first author - Coenen S, Avonts D, Van Royen P, Denekens J. Chronic obstructive

pulmonary disease: don’ t forget the gatekeeper [Letter]. The Lancet 1998;352:649.

- Coenen S, Van Puymbroeck H, Debaene L, Denekens J, Van Royen P. Irrational prescribing because of shifting therapeutic thresholds for sore throats and for coughing [eLetter]. eBMJ.

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- Coenen S, Van Royen P, Denekens J. Reducing antibiotics for respiratory tract symptoms in primary care: 'why' only sore throat, 'how' about coughing?[Letter]. Br J Gen Pract 1999;49:400-1.

- Coenen S, Van Royen P, Denekens J. Diagnosis of Acute Bronchitis [Letter]. J Fam Pract 1999;48:741-2.

- Coenen S, Van Royen P, Vermeire E, Hermann I, Denekens J. Correspondence [Letter]. Fam Pract 2000;17:209.

- Coenen S, Van Royen P, Vermeire E, Hermann I, Denekens J. Antibiotics for coughing in general practice: a qualitative decision analysis. Fam Pract 2000;17:380-5.

- Coenen S, Van Royen P, Avonts D, Denekens J. The GP forgotten again [eLetter]. EBMJ.

- Coenen S, Kuyvenhoven MM, Butler CC, Van Royen P, Verheij TJM. Variation in European antibiotic use [Letter]. Lancet 2001;358:1272.

- Coenen S, Michiels B, Van Royen P, Van der Auwera J-C, Denekens J. Antibiotics for coughing in general practice: a questionnaire study to quantify and condense the reasons for prescribing. BMC Family Practice 2002, 3:16. (10 pages; URL: http://www.biomedcentral.com/1471-2296/3/16)

- Coenen S, Van Royen P, Michiels B, Denekens J. Promotion of rational antibiotic use in Flemish general practice: implementation of a guideline for acute cough [Abstract]. Prim Care Respir J 2002;11:56.

- Coenen S, Van Royen P, Michiels B, Van der Auwera J-C, Denekens J. A mytical diagnosis or a practicable symptom? [eLetter]. eBMJ.

As co-author - Vermeire E, Van Royen P, Coenen S, Denekens J. The compliance of type 2

diabetes patients [Letter]. Aust Fam Phys 1999;28:720. - Remmen R, Van Royen P, Coenen S, Denekens J. Diagnosis and general

practice [Letter]. Br J Gen Pract 2001;51:232. - B. Michiels, S. Coenen, D. Avonts, P. Van Royen, J. Denekens. Who benefits

from an influenza vaccination of GPs [Letter]? Vaccine 2001;20:1-2. - Vermeire E, Van Royen P, Griffiths Fr, Coenen S, Peremans L, Hendrickx K.

The critical appraisal of focus group research articles. Eur J Gen Pract 2002; 8 104-108

- Vermeire E, Van Royen P, Coenen S, Wens J, Denekens J. The adherence of type 2 diabetes patients to their therapeutic regimens: patients' perspective; a qualitative study. Practical Diabetes International. Accepted for publication.

List of publications

163

Abstracts

National Conferences - Coenen S, Van Royen P, Vermeire E, Hermann I, Denekens J. Met welke

argumenten voert de huisarts zijn diagnostisch beleid bij de contactreden "hoesten". VHI 16de referatendag 1998, Gent.

- Vermeire E, Van Royen P, Coenen S, Denekens J. Opvattingen van apothekers over compliance van hun cliënten in het algemeen en type 2-diabetespatiënten in het bijzonder [Poster]. VHI 16de referatendag 1998, Gent.

- Van Heerde M, Stuer H, Coenen S, Denekens J, Van Royen P. Risico’ s van hypolipemiërende behandelingen [Poster]. 16e VHI Referatendag 1998, Gent.

- Vermeire E, Van Royen P, Coenen S, Patteet R, Denekens J. De compliance van type 2 diabetes patiënten met hun behandeling: focusgroepen onderzoek. 17e VHI Referatendag 1999, Antwerpen.

- Sepers G, Coenen S, Denekens J, Van Royen P. De niet-bacteriologische determinanten voor het gebruik van antibiotica bij luchtweginfecties in de huisartsgeneeskunde [Poster]. 17e VHI Referatendag 1999, Antwerpen.

- Coenen S. De implementatie van Evidence-Based Medicine in de dagelijkse praktijk. ADVISA Workshop Evidence-Based Medicine 2000, Antwerp.

- Coenen S, Van Royen P, Van der Auwera J, Denekens J. Antibiotica voor hoestklachten: hoe beslissen huisartsen? Eerste Eerstelijnssymposium 2000, Brussel.

- Coenen S. Gecontroleerd interventieonderzoek naar het effect van een deskundigheidsbevorderingspakket op het gebruik van antibiotica bij de klacht ‘hoesten’ in de huisartspraktijk. Belgian Drug Utilization Research Group 2000, Brussel.

- Coenen S, Van Royen P, Michiels B, Van der Auwera JC, Denekens J. Doelmatig antibioticagebruik in de huisartspraktijk: implementatie van een aanbeveling voor acute hoest. Tweede Eerstelijnssymposium 2001, Leuven.

- Meewe M, Coenen S, De Backer W, Van Royen P, Denekens J. De behandeling van acute hoest: Zijn betamimetica nuttiger dan antibiotica ter behandeling van luchtweginfecties met acute hoest [Poster]. Tweede Eerstelijnssymposium 2001, Leuven.

- Coenen S. Antibiotica voor hoesten: hoe beslissen huisartsen. Research Club UZA 2001, Antwerpen.

- Coenen S, van Duijn HJ, Van Royen P, Kuyvenhoven MM, Tudor Jones R, Butler CC. Opvattingen van patiënten over luchtwegklachten en antibiotica:

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een vergelijking tussen België, Groot-Brittannië en Nederland. Derde Eerstelijnssymposium 2002, Antwerpen.

- Coenen S, Michiels B, Renard D, Denekens J, Van Royen P. Het effect van de inschatting door de huisarts van de vraag van de patiënt op het voorschrijven van antibiotica voor acute hoest. Derde Eerstelijnssymposium 2002, Antwerpen.

International Conferences - Coenen S, Van Royen P, Vermeire E, Hermann I and Denekens J. What

determines medical decision-making in patients with coughing as the reason for encounter? Focus group research with general practitioners. First European Network Organisations Open Conference-WONCA 1999, Palma de Mallorca

- Vermeire E, Van Royen P, Coenen S, Denekens J. Compliance of type 2 diabetes patients with their therapeutic regimen [Poster]. First European Network Organisations Open Conference-WONCA 1999, Palma de Mallorca.

- Vermeire E, Van Royen P, Coenen S, Wens J, Denekens J. Compliance of type 2 diabetes patients with their therapeutic regimen: Focus groups. European General Practitioners’ Research Workshop 2000, Maastricht.

- Vermeire E, Van Royen P, Peremans L, Hendrickx K, Coenen S, Griffiths F. Critical appraisal of focus group research articles [Poster]. Cochrane Colloqium 2000, Cape Town.

- Coenen S. A Flemish Recommendation for the Management of Acute Cough in General Practice. Second General Practice Respiratory Infection Network Symposium 2000, Gent

- Van Royen P, Coenen S, Denekens J, Dieleman P, Michels J. From practice guidelines to implementation of good clinical practice. A Flemish guideline for acute cough and rational antibiotic use in general practice. WONCA 2001, Tampere.

- Coenen S. Antibiotica voor hoestklachten: hoe beslissen huisartsen [Poster]? NHG-Wetenschapsdag, Amsterdam 2001, Nederland.

- Coenen S, Van Royen P, Van der Auwera JC, Denekens J. Promotion of rational antibiotic use in Flemish general practice: implementation of a guideline for acute cough. EURODURG 2001, Praag.

- Coenen S, Van Royen P, Michiels B, Van der Auwera JC, Denekens J. Promotion of rational antibiotic use in Flemish general practice: implementation of a guideline for acute cough. Third General Practice Respiratory Infection Network Symposium 2001, Helsinki.

List of publications

165

- Coenen S. Promotion of rational antibiotic use in Flemish general practice: implementation of a guideline for acute cough. European Conference on Antibiotic Use in Europe 2001, Brussel.

- Coenen S. Indications for antibiotic treatment of lower respiratory tract infections. World IPCRG Conference, Amsterdam 2002.

- Coenen S, Van Royen P, Michiels B, Van der Auwera JC, Denekens J. Promotion of rational antibiotic use in Flemish general practice: implementation of a guideline for acute cough. World IPCRG Conference 2002, Amsterdam (Abstract: Prim Care Respir J 2002;11(2):56).

- Coenen S, Van Royen P, Michiels B, Van der Auwera JC, Denekens J. Promotion of rational antibiotic use in Flemish general practice: implementation of a guideline for acute cough. WONCA Europe 2002, London.

- Coenen S, Van Royen P, Michiels B, Van der Auwera JC, Denekens J. Optimaliseren van het voorschrijven van antibiotica in de Vlaamse huisartspraktijk: de implementatie van een aanbeveling voor acute hoest. NHG-Wetenschapsdag 2002, Nijmegen.

- Coenen S, Michiels B, Renard D, Denekens J, Van Royen P. Antibiotics for coughing in general practice: GPs’ perception of patients’ demand determines prescribing. Fourth General Practice Respiratory Infections Network Symposium 2002, Winchester.

- Coenen S, Michiels B, Denekens J, Van Royen P. Optimising antibiotic prescribing for acute cough: a quality improvement report from Belgium. EquiP 2002, Lissabon.

Master’s Thesis

As first author - Coenen S, Wens J, Denekens J, Van Royen P. Diagnostiek van

luchtweginfecties: een literatuurstudie naar de kracht van medisch besliskundige argumenten binnen het bereik van de huisarts. 1997.

As supervisor - De Wever V: Welke kans is er op de diagnose van psych(iatr)ische

aandoeningen bij patiënten die zich in de huisartspraktijk presenteren met de klacht hoesten, en met welke argumenten kan de huisarts deze diagnose aantonen dan wel uitsluiten, 1998.

- Martens V: De plaats van hoestremmers bij luchtweginfecties, 1998.

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- De Leeck A: Allergie voor huisdieren bij astmatische kinderen, 1999. - De Smedt P: Electrocardiografie en risico op het ontwikkelen van uitgebreid

myocardinfarct en/of plotse dood, 1999. - Devos M: Argumenten om bij de klacht hoesten antibiotica voor te schrijven,

1999. - Sepers G: De niet-bacteriologische determinanten voor het gebruik van

antibiotica bij luchtweginfecties in de huisartsgeneeskunde, 1999. - Van Den Branden A: Aantonen van een bovenste luchtweginfectie vanuit de

klacht hoest, 1999. - Van Dessel E: Behandeling van Pelvic Inflammatory Disease, 2000. - Moret J: Beleid bij prikaccidenten. Effecten en toxiciteit van

chemoprofylaxis, 2000. - Palit Y: Alcohol en vaatlijden, 2000. - Jacobs S: Depressie bij ouderlinge, 2000. - Sahbaz H: De gezondheidstoestand van de bejaarde migranten, 2000. - Kraak J: Acute bronchitis: het juiste antibioticum, 2001. - Marichal P: COPD: anticholinergica en/of betamimetica, 2001. - Meewe M: De behandeling van acute hoest, 2001. - Janssen E: Langwerkende betamimetica bij chronisch astma, 2001.

Other publications - Coenen S, Denekens J, Van Royen P. Patiënt en arts hebben baat bij minder

antibiotica. De Standaard 1999 19 februari:10. - Coenen S, Michiels B, Denekens J, Van Royen P. Optimising Antibiotic

Prescribing for Acute Cough: a Quality Improvement Report from Belgium, submitted for the Equip Quality Improvement Prize 2002.

- Coenen S. Antibiotica voor hoestklachten: beslissen in de huisartsgeneeskunde. Onderzoeksverslag voor de Wetenschappelijke Prijs Pharmacia Corporation – 2002.

- Coenen S. Antibiotica voor hoestklachten in de huisartspraktijk: exploreren, beschrijven en optimaliseren van het voorschrijven. Onderzoeksverslag voor de Wetenschappelijk Prijs 2003 McKinsey&Co voor Doctoraatswerken – 2003.

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Dankwoord

Bedankt … , dat is een dankwoord. Al wat daarna komt is knap lastig als je zo dankbaar bent voor de zovele dingen die zoveel mensen in de voorbije jaren voor je gedaan hebben en je al deze mensen daarvoor willen danken. Ik zal niet nalaten te proberen iedereen te bedanken voor wat hij of zij betekent heeft voor dit proefschrift, maar vooral wil ik het volgende zeggen. Het heeft me steeds ontzettend deugd gedaan dat de hieronder vermelde mensen, maar ook zo vele anderen, mij zo welgezind zijn geweest.

In min of meer chronologische volgorde bedankt ik mijn ouders, zij gaven me alle kansen, ook die om te studeren en arts te worden; Johan Wens, omdat hij, Annick en hun kinderen me hebben laten zien wat huisartsgeneeskunde in de praktijk betekent; met hem allen die meewerkten aan het onderzoeksprotocol voor de aanvraag van een Aspirant-mandaat van het Fonds voor Wetenschappelijk Onderzoek – Vlaanderen (FWO); Jan Heyrman, die als referent optrad; Frank Buntinx, voor zijn bijdrage aan de herziening van het protocol ter gelegenheid van de hernieuwing van mijn FWO-mandaat; het FWO, omdat ze vertrouwen hadden in dit huisartsgeneeskunde onderzoek, de Universiteit Antwerpen, om haar gastvrijheid en financiële steun; Eric Mathieu, die zijn hulp en een ontzettend boeiend programma aanbood in de doctoraatsopleiding; alle medewerkers van de Vakgroep Huisartsgeneeskunde: Lydie Van Laerhoven, Louise Gentils en Veerle Jordant, voor het secretariaatswerk; Ingeborg Hermann, Ria Patteet en, in het bijzonder, Etienne Vermeire, voor de assistentie bij de kwalitatieve start van dit project; Barbara Michiels, voor haar aanzienlijk aandeel in het kwantitatieve vervolg, Jean-Claude Vander Auwera, voor zijn statistisch advies en andere inzichten; Jo Goedhuys, voor zijn feedback betreffende de factor analyse; Didier Renard en Geert Molenbergs, die me toelieten uiteindelijk zelf de geclusterde data te analyseren; Lieven Annemans, Bob Vander Stichele, Monique Elsevier en Jan Van Campen, omdat ze me introduceerden in de gezondheidseconomie en het onderzoek van geneesmiddelen gebruik; An de Sutter en Jan Matthys, voor hun boeiend gezelschap tijdens de Opleiding Huisart-Onderzoek; Rogier Hopstaken, Jean Muris en Willy Graffelman, omdat ze hun ideeën en expertise deelden; de Wetenschappelijke Vereniging voor Vlaamse Huisartsen (WVVH), voor de financiële steun bij de ontwikkeling van de WVVH-aanbeveling voor acute hoest; auteurs en experts betrokken bij deze aanbeveling, o.a. Peter Dieleman, Sabine Lemoyne, Jan Michels, respectievelijk Jef Boecks, Veerle

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De Bock en Hugo Van Bever voor hun bijdrage; Isabelle Kloeck, Goedele Truyen, Karel Van Poeck, Isabelle Janssens, Bart Blyweert en Guillaume van Melckebeke en alle anderen die van ver of nabij hebben geholpen bij het interventie onderzoek; ADVISA vzw in de persoon van Jean Colin, voor de financiële steun; Ineke Welschen, Marijke Kuyvenhoven, Huug van Duijn en Theo Verheij, voor het plezier van samenwerking; Herman Goossens en Marc De Meyere, voor de unieke kansen om mijn werk te presenteren; de ander leden van het General Practice Respiratory Infection Network (GRIN), onder andere Ian Williamson en Alastair Hay voor hun feedback; Jo Verhoeven en Daniel Newman, die hebben geholpen met het Engels, en Veronique Verhoeven, Luc Debaene en de andere medewerkers die voor een leuke werksfeer zorgden.

Uiteraard dank ik ook al de huisartsen, en hun patiënten, die bereid waren om deel te nemen aan de verschillende onderzoeken, zonder hen was dit proefschrift er gewoonweg niet gekomen; Marc Debroe, Wilfried De Backer en André Meheus, voor hun vakkundige adviezen tijdens de jaarlijkse evaluatie van dit doctoraat; Geert-Jan Dinant and Paul Little, for your very valuable review of this dissertation.

Maar, ik ben vooral erg tevreden dat ik met velen onder jullie waarschijnlijk nog vaak zal kunnen samenwerken. Daarvoor ben ik nu reeds naast de eerder genomineerden Mark Haggard, Erwin Offeciers en Chris Butler dankbaar.

Ik hoop dat ik jullie allemaal als vrienden mag beschouwen, en dat doe ik zeker voor twee bijzondere mensen: Joke Denekens en Paul Van Royen, wiens bijdrage aan deze universiteit, zowel wat betreft de onderwijskundige onderbouw als de wetenschappelijke invulling van de basisopleiding, zeker voor mij niet ongemerkt is gebleven. Joke bedankt voor het vertrouwen dat je me geeft. Paul bedankt voor je betrokkenheid en immer accurate reflectie bij alle mijn ondernemingen.

En tot slot - over mijn waardevolste onderneming – Sylvie Van Bylen, Seppe en Lieselotte, het doet me goed te weten dat jullie trots op me zijn. Dit werk draag ik aan jullie op.

phd thesis samuel coenen.pdf

Documents

general practice gps

introduction chapter

e d i c i n e d e p

c t i c e antibiotics

general introduction

chapter v

e n t o f g e n e r

general discussion