© mapi 2014, all rights reserved 1 lessons learned from a multi-diseases study using a patient...

© Mapi 2014, All rights reserved 1

Lessons learned from a multi-diseases study using a patient online community

Measuring and Understanding Patient Acceptance Of Treatment Across Different

Indications As Triggers in Targeting Adherence Support Programs

Benoit Arnould and Hélène Gilet, Mapi Michael Chekroun, Carenity

ACO SummitPhiladelphia, 2nd June 2015


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Key words from ACO Summit day 1

Adherence, compliance & persistenceWe will (briefly) discuss why it is so difficult to measure, understand, and improve!

Patient EngagementWe would very much like to have patients engaged in the solution we think are good for them,

BUT…

Should we not first engage ourselves in solution that work for them?

Quality MetricsMeasuring quality is essential for our systems.

The challenge is to conduct appraisal in a way that favours actual improvement in quality, and not just improvement in metrics…


Co-authors

MICHAEL CHEKROUNFounder & CEO, [email protected] : +33 (0)1 84 17 42 71 M : +33 (0)6 85 61 75 55WWW.CARENITY.COM

BENOIT ARNOULDSenior Director – GlobalPatient-Centered OutcomesHEOR & Strategic Market Access, Mapi [email protected] : +33 (0)4 72 13 69 53M : +33 (0)6 80 45 55 28WWW.MAPIGROUP.COM

HÉLÈNE GILETSenior Research ManagerHEOR & Strategic Market Access, [email protected] : +33 (0)4 72 13 59 78WWW.MAPIGROUP.COM

FOLLOW US ON LINKEDIN:W W W . L I N K E D I N . C O M /C O M P A N Y / M A P I G R O U P


Non-Adherence is a REAL problem!

"Medication non-adherence rates typically range from 30% to 60%.“

"Half of the patients for whom appropriate medication is prescribed fail to receive the full benefits because of inadequate adherence to treatment."

"Poor adherence to treatment of chronic disease is a worldwide problem of striking magnitude.“

"Adherence to long-term therapy for chronic illnesses in developed countries averages 50%. In developing countries, the rates are even lower. It is undeniable that many patients experience difficulty in following treatment recommendations."

* "Medication Nonadherence: Finding Solutions to a Costly Medical Problem," Gottlieb, Drug Benefit Trends 12(6)** Adherence to Long-Term Therapies: Evidence for Action, World Health Organization, 2003


Many different reasons of non-adherence

IntentionalBeliefs

DiseaseTreatmentIndustry

Response to actual treatment

Side effectsRegimenFormulationPerceived efficacy

Financial

UnintentionalPatient characteristics

ForgetPoor eyesight/literacyDon’t understand instructions

Lack of knowledge Treatment issues

Device or container difficultiesFormulation problemsTablets of similar colourRegimen too complex

Can’t get rx or drugs

© Mapi 2014, All rights reserved 701/06/2011

7

Adherence a major concern but…

No unique simple solution to improve adherence

A huge amount of resources is allocated to make patients more adherent

Health care system need to work on:

Priorities– Do we target the right patients?– Do we address their actual needs?

Solutions– Do we take the right actions?– Are the results of our actions lasting and their effects maintained?

Effectiveness– What is the best program?– How can we generalise an experiment?

Cost-effectiveness– What is the value?– Who will pay for it?


Adherence studies face important limitations

Validity of measurementWhat is really measured?

Reliability of measurementHow far can we consider results are close to reality?

Social desirability bias Do study participants tell the truth?

Recruitement biasWhere can non-adherent patients be found, through which channel can they be enrolled in studies?


Concept and measurementof Acceptance


Socio-demographics (age, sex, social category, etc.)

Individual psychosocial

characteristics (personality, cognitive,

characteristics, etc.)

Perceived susceptibility

Perceived severity

Health value

Perceived benefice

Perceived barriers

BehaviorAcceptance

Acceptance in Health Beliefs Model Rosenstock (1966,1974), Becker & Mainman (1975), Becker & Rosenstock (1984), Marant (2011)


APTEO study: methodology


APTEO study objective

APTEO = French acronym for « l’Acceptance des Patients vis-à-vis de leur Traitement : Etude Online » (or "patient acceptance of their treatment: online survey")

Objective: to evaluate, for a variety of chronic diseases, the level of patients’ acceptance of their medication in real life using a patient online community


Carenity: 60,000 patients and 1,000 conditions

Top 20 conditions on Carenity


APTEO study design

Observational, cross-sectional study

Data collected (completed by patients):Demographic characteristics (age, gender, occupational status, geographic location)

Clinical characteristics (chronic disease, date of diagnosis, current treatment, comorbidities)

ACCEPT questionnaire (25 items)


ACCEPT questionnaire:6 treatment-attribute specific dimensions …

treatment-attribute specific dimension

Number of items

E.g. item labelResponse

choice (same for all items)

Acceptance/Medication Inconvenience

5 Q1: Do you find it inconvenient to prepare your medication?

• "Yes, and I don’t find this easy to accept"

• "Yes, but I find this easy to accept"

• "No"

Acceptance/Long-term Treatment

3 Q5: Will you have to take your medication for a long time?

Acceptance/Regimen Constraints

5 Q6: Do you find that having to remember to take your medication is inconvenient?

Acceptance/Numerous Medications

1 Q11: Do you find that you have a lot of medications to take?

Acceptance/Side Effects

5 Q16: Are these side effects unpleasant?

Acceptance/Effectiveness

3 Q20: Do you find that your medication is effective for you?


… + 1 general acceptance dimension

General Acceptancedimension

Number of items

Item labelsResponse

choice (Likert-type scales)

Acceptance/ General

3

Q23: Do you agree with the following statement: "My medication has more advantages than disadvantages"?

"Totally disagree""Somewhat disagree""Somewhat agree""Totally agree""I don’t know"

Q24: Given the advantages and disadvantages of your medication, do you consider it to be an acceptable solution?

"Not at all acceptable""Not very acceptable""Somewhat acceptable""Totally acceptable""I don’t know"

Q25: Are you convinced that in the long term, it is worth taking your medication?

"Not at all convinced""Not really convinced""Somewhat convinced""Totally convinced""I don’t know"


ACCEPT is available in 16 languages

English for CanadaEnglish for the UKEnglish for the USAFrench for CanadaFrench for SwitzerlandGerman for GermanyGerman for SwitzerlandItalian for Italy

Portuguese for BrazilRussian for RussiaSlovakSpanish for ArgentinaSpanish for ColombiaSpanish for MexicoSpanish for SpainSpanish for the USA


References ACCEPT

Gilet H, Chekroun M, Arnould B. Patients’ acceptance of their medication: Results from a French multidiseases study with patient online community using the ACCEptance by the Patients of their Treatment (ACCEPT©) questionnaire. 2014. ISPOR 17th Annual European Congress, Amsterdam, The Netherlands, 8-11 November 2014.Gilet H, Chekroun M, Arnould B. How can patient online communities inform industry about barriers to medication acceptance and unmet needs? Lessons learned from a French multi-diseases study using a patient online community. 2014. ISPOR 17th Annual European Congress, Amsterdam, The Netherlands, 8-11 November 2014.Arnould B, Gauchoux R, Meunier J, Gilet H, Regnault A. Validation of ACCEPT, a new generic measure to assess how patients with chronic diseases balance between the advantages and disadvantages of following the recommended treatment regimen in real-life. 2013. ISPOR 16 th Annual European Congress, Dublin, Ireland, 2-6 November 2013.Marant C, Longin J, Gauchoux R, Arnould B, Spizak C, Marrel A, et al. Long-term treatment acceptance: what is it, and how can it be assessed? Patient. 2012;5:239-249.Gauchoux R. Acceptability studies: a new way of assessing adherence and understanding its determinants in real life. PRM Newsletter. 2011;8:1-2,14.Chretin S, Viala-Danten M, van Ganse E, Patrick DL, Arnould B, Longin J. The missing piece between treatment experience and intention to persist: testing the internal consistency reliability and predictive validity of acceptability. 2010. ISPOR 13th Annual European Congress, Prague, Czech Republic, 6-9 November 2010.Marant C, Spizak C, Longin J et al. Development of the ACCEPT© questionnaire to assess acceptability of long-term treatments: qualitative steps. 2009. ISPOR 12 th Annual European Congress, Paris, France, 24-27 October 2009.Marant C, Longin J, Spizak C et al. What does acceptability mean for patients and how should it be measured? Qualitative steps for the development of a new measurement instrument for pharmacies: the "ACCEPT©" questionnaire. 2008. ISPOR 11th Annual European Congress, Athens, Greece, 8-11 November 2008.Saussier C, van Ganse E, Auge-Caumon MJ et al. Measuring the contribution of treatment acceptability to the understanding of patient adherence to long-term treatments. Results from a pilot study conducted with In fine PHARMA®: a pharmacies network dedicated to pharmacoepidemiological surveys. 2008. ISPOR 11 th Annual European Congress, Athens, Greece, 8-11 November 2008.


Definition of the analysis population

Patients included in the analysis population:Patients suffering from any chronic diseases

Patients currently receiving a treatment for this disease

Patients who had completed at least one item of the ACCEPT questionnaire

Adults

Patients living in France


APTEO study: results


Patient population

A unique population of patients:Population size: data on more than 4,000 patients analysed

Variety of diseases: more than 270 chronic diseases, among which 19 including more than 30 patients

30,000 patients registered on Carenity.com

4,880 participants

4,193 patients included in analysis

population

19 diseases with more than 30 patients:- Type 2 diabetes (N=669)- Multiple sclerosis (N=426)- Type 1 diabetes (N=251)- Ankylosing spondylitis (N=297)- Fibromyalgia (N=248)- Rheumatoid arthritis (N=215)- Arthrosis (N=163)- Bipolar disorder (N=143)- Breast cancer (N=137)- Depression (N=104)- Lupus (N=100)- Crohn’s disease/Ulcerative colitis (UC) (N=98)- Chronic obstructive pulmonary disease (COPD) (N=74)- Psoriasis (N=68)- Parkinson’s disease (N=65)- Hypertension (N=64)- Asthma (N=51)- Epilepsy (N=45)- Myocardial infarction (N=33)

942 patients with other diseases

+


How do patients accept their treatment?Score "Acceptance/General"

Box = interquartile range (Q3-Q1); + = mean; — = median; upper and lower bars = observed max and min values. Boxplots are ranked based on mean Acceptance/General score.


Type 1 diabetes – Mean Acceptance/General score = 61.2

Dimension (Min – Max all diseases)

Mean score1 Item

% response "Not easy to accept"2

Type 1 diabetes

Min – Max all diseases

Acceptance/Treatment Inconvenience(59.9 – 96.3)

59.9 Preparation 18 2 – 18Mode of administration 32 0 – 32Form 26 0 – 26Storage conditions for journeys 39 1 – 39Taking discreetly 19 0 – 24

Acceptance/Long-Term Treatment(46.3 – 61.3)

48.2 Long time in the past 36 11 – 49Long time in the future 49 23 – 58Routine 15 6 – 19

Acceptance/Regimen Constraints(52.9 – 76.7)

52.9 Remember to take 37 17 – 39Find time to collect 24 8 – 25Remember to take with oneself 37 7 – 37Always having on oneself 38 7 – 38Frequency 33 9 – 39


Numerous medications 31 12 – 55

Acceptance/Side Effects(35.4 – 81.4)

68.5 Side effects 37 22 – 76Unpleasant side effects 39 22 – 74Disabling side effects 32 16 – 66Medication due to side effects 7 2 – 37Risk of serious side effects 23 8 – 58

Acceptance/Effectiveness(37.7 – 79.8)

67.0 Effective 8 4 – 29Protecting enough 8 3 – 25Rapid effect 16 11 - 49

20-39% 40-59% 60-79%0-19%1 Higher score is better; 2 Higher percentage is worse




Mean score1 Item


Type 1 diabetes
















Breast cancer – Mean Acceptance/General score = 38.6


Mean score1 Item


Breast cancer












Acceptance /Effectiveness(37.7 – 79.8)




Fibromyalgia – Mean Acceptance/General score = 33.7


Mean score1 Item


Fibromyalgia












Acceptance /Effectiveness(37.7 – 79.8)




Discussion, conclusionsand next steps


Conclusions

ACCEPT profiles are easy to interpret.Confirmation and quantification of « well-known » facts

Acceptance scores show clear contrasts between diseases

Unmet needsPatients priorities

Contrasts give guidance for interpretationAcross diseases:

On which diseases is innovation most needed?

Within disease: Do subgroups of patients face more issues than others?

Priorities: What are the most prevalent and impactful barriers to treatment acceptance?

– Efficacy, Safety, Duration, Number of drugs, Convenience, Constraints…– Specific features (item level)


Applications for Health Care Providers: addressing strategic and tactic questions

Prioritization: What sort of innovation/solution is likely to match market unmet needs?

Segmentation: Which subgroup of patients could benefit most?

Personalized solutions: Through finely granulated identification of barriers, efficiently spend resource on adequate solutions:

Give potential risks meaningfulness and reality (eg monitoring blood glucose in Type 1 diabetes patients)Give potential benefits a reality! (eg chemotherapy in breast cancer)Adapt solution to patient values (remember the invention of therapeutic window for AIDS patients – it was past century!)Overcome practical barriers (eg eye-drop devices for elderly, or prescribe combos)Address their needs! (eg switch to more active drugs in Rhumatoïd Arthritis)


Ultimately, the patient experience is the key to adherence

Patient experience in real life

PROs help to assess and communicate that experience

Patient experience inhealth care environment

© mapi 2014, all rights reserved 1 lessons learned from a multi-diseases study using a patient...

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