an international methodology to describe clinical nursing phenomena: a team approach

An international methodology to describe clinical nursingphenomena: a team approach

June Clarka,*, Martha Craft-Rosenbergb, Connie Delaneyb

aSchool of Health Sciences, University of Wales Swansea, Swansea, UKbThe University of Iowa, Iowa City, IO, USA

Received 4 November 1999; received in revised form 1 February 2000; accepted 14 February 2000

Abstract

The development of a structured and standardized clinical language for nursing is of major importance to theprofession for both practice and science. This paper describes a methodological approach which has been developedfor the re®nement and extension of the NANDA taxonomy in the Nursing Diagnosis Extension and Classi®cation

(NDEC) project. The paper proposes that this method could be used by nurses in all countries to facilitate theidenti®cation, development and validation of terms and labels which can be incorporated into each country's ownemerging data systems, translated and cross mapped between systems, and eventually incorporated into

international data sets. 7 2000 Elsevier Science Ltd. All rights reserved.

Keywords: Nursing diagnosis; Nursing language; Nursing classi®cation; Documentation; Instrument development

1. Introduction

The development of a structured and standardized

clinical language for nursing is of major importance to

the profession for both practice and science. Patients

and clients and their families need to be able to under-

stand ``what nurses do, relative to certain human

needs, to produce certain outcomes'' (ICN, 1996).

Managed health care delivery, whatever form it takes

in the various countries which are developing or

reforming their health care systems, requires access to

standardized, computerized data, including data about

nursing, for resource management and outcomes evalu-

ation. Standardized vocabularies are essential to the

implementation of an electronic patient record.

Describing the ``elements'' is also the ®rst step in the

development of a scienti®c discipline, for as Harmer

long ago pointed out:

If nursing is ever to make even a remote claim to

being a science or even to being conducted on a

scienti®c basis, it must be built up like all branches

of science; that is by the most careful and unbiased

observations and recording of often seemingly tri-

vial details from which, by organising, classifying,

analysing, selecting, inferring, drawing and testing

conclusions, a body of knowledge or principles are

®nally evolved (Harmer, 1926).

Werley and Lang (1988) have proposed a Nursing

Minimum Data Set which in addition to patient demo-

graphic and service elements, contains four nursing

care elements Ð nursing diagnosis, nursing interven-

International Journal of Nursing Studies 37 (2000) 541±553

0020-7489/00/$ - see front matter 7 2000 Elsevier Science Ltd. All rights reserved.

PII: S0020-7489(00 )00032-8

www.elsevier.com/locate/ijnurstu

* Corresponding author. Tel.: +44-1792-295809; fax: +44-

1792-295127.

E-mail address: [email protected] (J. Clark).

tions, nursing outcomes, and nursing intensity. Con-siderable work is being undertaken to develop vocabul-

aries and classi®cations for each of these elements, butbecause selection of appropriate diagnoses drives theselection of interventions, which in turn determine

intensity and provide the independent variables for thestudy of outcomes, the development of vocabulariesand classi®cations for diagnostic concepts is of particu-

lar importance.Increasing worldwide recognition of this need has

stimulated attempts in many countries to develop

classi®cations of the nursing phenomena which arevariously called ``patient problems'' (Martin andScheet, 1992), ``client status'' (Alberta Association ofRegistered Nurses, 1997), ``factors a�ecting health

care'' (WHO, 1992) or ``nursing diagnoses'' (NANDA,1999). E�orts include the Nursing Terms Project in theUnited Kingdom (Casey, 1995), the Standard Classi®-

cation of Diagnostic Terms for Nursing developed bythe Dutch Council of Public Health Project in theNetherlands, the Nursing Classi®cation Project in Den-

mark (Danish National Board of Health, 1992), severalprojects in the USA (Lang, 1996), and the Inter-national Council of Nurses' project to develop an In-

ternational Classi®cation for Nursing Practice (ICN,1996).The developers of all these systems have experienced

conceptual, methodological, and semantic di�culties

which must be resolved before the ICN's goal of estab-lishing a common nursing language for describing nur-sing practice can be realized. This paper describes a

methodological approach which was developed at theUniversity of Iowa, initially for the Nursing Interven-tion Classi®cation (McCloskey and Bulechek, 1996),

later for the Nursing Outcomes Classi®cation (Johnsonand Maas, 1997), and most recently for the re®nementand extension of the NANDA taxonomy in the Nur-sing Diagnosis Extension and Classi®cation (NDEC)

project. The paper proposes that this method could beused by nurses at all levels and in all countries to fa-cilitate the identi®cation and validation of terms and

labels which can be incorporated into each country'sown emerging data systems, translated and crossmapped between systems, and eventually incorporated

into the international data sets which are the long-termgoal of the ICN.

2. Conceptual, methodological and semantic problems

The problems, which the developers of all systemshave to resolve, are conceptual, methodological and

semantic. Conceptual problems include such questionsas:

. What is the nature of the concepts to be labelledand classi®ed? What exactly does the term ``nursingdiagnosis'' mean?

. Which concepts are clinically relevant and meaning-ful to nurses across di�erent countries and cultures?

. What level of abstraction would yield terms which

would be most clinically useful?. How can we capture those patient states or con-

ditions, which describe wellness states or risks rather

than actual problems or disorders?. How can we express those states or conditions

which relate to groups such as a family or a commu-

nity as a single unit rather than to individuals?. How can we incorporate those phenomena with

which nurses are concerned but which relate to theenvironment rather than to human beings?

Semantic questions include:

. How can these concepts be expressed in words?

. What form of words can be used to express complexconstructs which contain more than one concept butwhich have to be considered together to be clinicallymeaningful?

. How can these words be translated into di�erentlanguages in such a way that the words used trulyrepresent the common concept?

Methodological issues include:

. When terms and concepts have been identi®ed, howcan they be validated?

. Which approach to classi®cation is better Ð topdown or bottom up? or can we get the best of both?

. How should we evaluate the completeness and clini-

cal usefulness of the structured and unstructuredvocabulary, or classi®cation?

3. The NANDA taxonomy

The NANDA classi®cation was the ®rst systemdeveloped to represent the patient states or conditions

toward which nursing directs its work. It is widelyused in the United States and has also been translatedinto several other languages. The work consists of 150

diagnostic labels, de®nitions and a taxonomy, whichhave been approved for clinical use and testing, withfurther labels which have been received for review and

further development (NANDA, 1999). The diagnosticlabels are currently arranged in a taxonomy of nine

J. Clark et al. / International Journal of Nursing Studies 37 (2000) 541±553542

domains based on patterns of human response (Roy,

1984), but a revised taxonomy of twelve domains

based on health patterns, each of which contains at

least two classes, has been proposed and is under

review (NANDA, 1999). In addition to revision and

addition of terms, the proposed Taxonomy II is multi-

axial.

All of the systems developed to date are open to cri-

ticism. As nursing moves into to the twenty-®rst cen-

tury, problems with the existing NANDA taxonomy

are being discussed openly, both within the organiz-

ation and across the discipline. Kim and Camilleri

(1984) summarized the theoretical and implementation

criticisms for the NANDA taxonomy as:

1. inadequate scope, comprehensiveness, speci®city,

and clinical usefulness of the nursing diagnoses

classi®cation;

2. need for guidelines for improving conceptual clarity,

with concept meaning and parameters explicated;

3. need to clarify the characteristics of diagnosis con-

cepts;

4. lack of accepted means for di�erentiating among

diagnosis labels, de®ning characteristics, and related

factors;

5. need for development of de®nitions and decision

rules for component parts for diagnoses;

6. lack of a systematic approach for establishing re-

liability, validity, and external validity of the diag-

noses;

7. need for clinical testing of a revised taxonomy; and

8. need to re®ne language to increase clinical utility

and linkage to other classi®cations in nursing and

other disciplines.

Other criticisms about the NANDA taxonomy include:

1. lack of a correlation between the NANDA and ICD

classi®cations;

2. limitations of mono-axial systems to re¯ect the mul-

tidimensionality of nursing;

3. inadequacy of the existing conceptual framework

which most nurses do not see as an accurate re¯ec-

tion of reality;

4. duplication of diagnostic terms which relate both to

individuals and to groups;

5. absence of health (wellness) diagnoses; and

6. lack of ®t between the Human Responses Patterns

and ``physiological'' nursing diagnoses that require

both interdependent and independent nursing inter-

ventions to reach desired outcomes (Kim and

Camilleri, 1984).

These criticisms concern the problems of internal and

external validity with individual diagnoses and with

the entire taxonomy. Kim (1989) noted major weak-nesses in nursing diagnosis validation research, includ-

ing lack of established inter-rater reliability, littleattention given to construct validity, and lack of repli-cation studies for external validity. It is no surprise

that these criticisms have limited the adoption of theNANDA taxonomy, especially in countries outside theUSA where these di�culties are compounded by di�er-

ences in language and culture. Leaders even withinNANDA have acknowledged these criticisms. Theremay be some basis for the view held by some nurses

that the current taxonomy is a poor classi®cation ofnursing diagnoses. However, questioning the validityof the nursing diagnoses as well as the organizingstructure opens the horizon for growth and develop-

ment (Kerr et al., 1993).According to Fleishman and Quaintance (1984), the

criteria for evaluating classi®cation systems are:

1. internal validity (the extent to which the system islogical and parsimonious within itself);

2. external validity (whether the system is capable of

accomplishing its intended purpose of predicting abehavioral e�ect); and

3. use rate (whether the system is actually used by

scientists and technologists in the ®elds of interest).

The current NANDA taxonomy does not appear tomeet the criteria for internal validity and external val-

idity. In spite of these limitations, it is used widely ininformation systems, books, care maps, and curricula.Thus, the need for a valid taxonomy of diagnoses ismost urgent. As noted by Brewer and Warren (1994),

the biggest barrier to validation has been money andthe resources to do the research.

4. The Nursing Diagnosis Extension Classi®cation

(NDEC) project

The NDEC project is a collaboration betweenNANDA and a research team based at The University

of Iowa. The collaborative agreement recognizes thatNANDA is responsible for policy formulation whileNDEC's role focuses on conducting the research tore®ne and extend the taxonomy.

Planning for the project began in 1992 when thethen president of NANDA, Lois Hoskins, who hap-pened to be visiting the College of Nursing for another

purpose, noted that the interventions and outcomeswork at The University of Iowa o�ered an ideal cli-mate to continue and extend the work of diagnoses

classi®cation. The Nursing Interventions Classi®cation(NIC) and the Nursing-sensitive Patient Outcomes

J. Clark et al. / International Journal of Nursing Studies 37 (2000) 541±553 543

Classi®cation (NOC) projects were already increasingthe awareness of the need for a comprehensive and

validated taxonomy of nursing diagnoses. The depen-dency of the selection of nursing interventions andidenti®cation of appropriate nursing sensitive outcomes

on the nursing diagnosis is unequivocal. The nursingdiagnosis is a core patient related data element crucialto determining the most e�ective nursing interventions

to meet the most appropriate nursing sensitive out-comes.Following consultation with colleagues, dialogue

with the NANDA President and numerous Boardmembers, and extensive literature review, the need foradditional work in the speci®cation, validation, andclassi®cation of nursing diagnoses was con®rmed, and

a collaborative agreement was signed. The ®rst teammeeting was held in November 1993.The research team currently consists of Co-PIs M.

Craft-Rosenberg, C. Delaney and J. Denehy workingwith more than 60 investigators, members, advisoryboard, and consultants. Clinicians, academicians, and

researchers representing all major clinical practiceareas are included. The majority are doctorally pre-pared. Several have conducted research on nursing

diagnosis. All faculty team members teach nursingdiagnoses, interventions, and outcomes at the under-graduate and graduate levels. All team members areexpected to be members of NANDA, and several team

members have held or currently hold NANDA o�ces(e.g. Meridean Maas, Orpha Glick, and the late PegMehmert). Several participants possess informatics

and/or classi®cation development expertise, includingCo-PIs Martha Craft-Rosenberg, Connie Delaney, andJanice Denehy, Investigators Orpha Glick, Mary

Clarke, and Meridean Maas, and Advisory BoardMembers Gloria Bulechek, Christopher Chute, NormaLang, Joanne McCloskey and Judy Warren.

5. Methods for the re®nement and development of

diagnostic labels

Several methods have been developed for identifyingand re®ning diagnostic labels. Most draw on the work

of Fehring (Fehring, 1986). The International Councilof Nurses is encouraging nurses from around theworld to submit new labels and to re®ne the labels

which are included in the International Classi®cationfor Nursing Practice (ICN, 1996) and has providedguidelines for retrospective and prospective methods

(Clark, 1996). The North American Nursing DiagnosisAssociation has a systematic process of four stages for

reviewing nursing diagnoses submitted by members(NANDA, 1999).

Validating nursing diagnoses is a complex task. Aninvitational conference on Research Methods for Vali-dating Nursing Diagnoses held in 1989 considered a

variety of qualitative, quantitative and integratedapproaches (NANDA, 1989). The NDEC project isconcerned primarily with construct validity and con-

tent validity. Construct validity, which Polit and Hun-gler (1997) acknowledge as one of the most di�cultand challenging tasks that the researcher faces,

involves assessing the theory and assumptions behindthe nursing diagnosis and its relationship with othervariables. The content validity of a nursing diagnosis isdetermined by the evaluation of the adequacy of its

de®ning characteristics (Kerr et al., 1993).The NDEC process incorporates ®ve steps:

1. concept analysis, using a standard protocol;

2. validation in small groups called Diagnosis WorkGroups (DWGs);

3. testing for conformity to rules for the development

of standardized language;4. validation by experts; and5. validation in clinical practice.

These steps are linked into NANDA's own stages oflabel development and approval Table 1.The NDEC project has used the concept analysis

process to re®ne and develop more than 99 diagnosisconcepts. Thirty seven of these re®ned and new diag-noses are included in the most recent (1999) NANDAmanual. NDEC has been unable to undertake expert

validation because of lack of funding. However, clini-cal testing continues in two di�erent sites. Alongsidethe clinical testing, work continues on the development

of additional candidate concepts.

5.1. Concept analysis

The purposes of concept analysis are:

1. to evaluate the completeness of the diagnosis con-

cepts and develop labels for any missing concepts;2. to develop a de®nition for each diagnosis concept;3. to evaluate and re®ne the signs and symptoms and

related factors based on the literature and the exper-tise of diagnosis work group members; and

4. to advance these diagnoses to NANDA Staging Cri-

teria 2.1. (see Table 1).

The approach used to explicate the content ofapproved NANDA diagnoses and to identify more

speci®c and clinically useful candidate diagnoses hasbeen mainly inductive, built on and derived from


empirical work. Sources were speci®ed to include: Wes-

tern Journal of Nursing Research, Advances in Nursing

Science, Nursing Research, Image-Journal of Nursing

Scholarship, Annual Review of Nursing Research, Nur-

sing Diagnosis; Proceedings from NANDA Confer-

ences dating back to 1974. Other sources, including

sources from other disciplines were used as appropri-

ate. Reports of empirical studies were given priority.

All resources are rated according the extent to which

the reports provide signs and symptoms (de®ning

characteristics) and related factors (Appendix D). The

dimensions of care addressed in the articles (unit of

care, developmental stage, health±illness continuum,

population, and setting) are also recorded on a matrix

to document the extent to which the data used rep-

resent the entire patient/client phenomena. The diag-

nostic label, conceptual de®nition, signs and

symptoms, related/risk factors/etiologies, synonyms,

and related concepts were extracted from each article

using a structured form (Appendix A). For empirical

studies the problem statement, variables, method,

sample, instruments, and ®ndings were identi®ed and

critiqued (Appendix B).

Findings from all articles were compared and syn-

thesized using a structured form. If the concept or

label seemed too complex, additional concepts were

identi®ed. One concept analysis summary was com-

pleted for each label (Appendix C). This summary

includes the recommended diagnostic label, conceptual

de®nition, signs/symptoms, related/risk factors/etiolo-

gies, and any additional concepts. The conceptual de®-

nition must describe the complete meaning of the

concept, be internally consistent, clear, simple, and

refer to all signs/symptoms. The related/risk factors/

etiologies must be precise. The di�erentiations between

the diagnosis and the related/risk factors/etiologies,

and between these and the signs and symptoms must

be adequate. All terms must be used in a consistent

manner, measurable, sensitive and useful for nursing,and include all dimensions of the diagnosis. The ad-

ditional concepts form the foundation for developmentof new diagnostic labels. The summary is then for-warded to the DWG, among other experts, for revali-

dation.

5.2. Validation by Diagnosis Work Groups

The diagnoses have been examined by the clinicalexperts who were assigned to Diagnosis Work Groups

(DWGs) using the processes given in Table 2. DWGsconsist of 6±10 nurses with expertise in the diagnosesto be analyzed, and wherever possible are chaired by

doctorally prepared nurses. The DWGs have acted as``think tanks'' for evaluation, discussion, deliberation,and debate. The evaluation of the concept analysis by

other clinical experts has also provided a test of faceand content validity.For the re®nement of the NANDA approved nur-

sing diagnoses, nine DWGs (a total of 65 members)

were formed:(a) parenting and infant behavior; (b)altered thought processes and confusion; (c) homeo-static imbalances; (d) elimination; (e) mental and spiri-

tual health; (f) hypoxia/¯uid & electrolytes/acid±base;(g) self-care/skin integrity; (h) family; and (i) commu-nity.

The DWG chair assigned diagnoses to individualgroup members based on their expertise and interest.Some group members requested that the analysis

assigned to them be shared with another member. Thisarrangement has been shown to provide opportunityfor shared learning and di�ering perspectives. Forexample, when the concept analysis began on the

NANDA label, ``Ine�ective Management of Thera-peutic Regimen: Families'', one individual advocatedfor the word ``non-compliance'', while the second indi-

vidual felt strongly that the word to be used was ``non-

Table 1

NANDA Staging Criteria (NANDA 1999)

1.0 Received for Development (Consultation from Diagnosis Review Committee)

1.1 Label only

1.2 Label and de®nition

1.3 Label and de®ning characteristics or risk factors

1.4 Label, de®nition, de®ning characteristics or risk factors, references

2.0 Accepted for Clinical Development: Authentication/Substantiation

2.1 Label, de®nition, de®ning characteristics or risk factors, and literature review;

2.2 Case study

2.3 Clinical studies

3.0 Clinically supported: Validation and Testing (criteria under development)

4.0 Revision: Re®nement (criteria under development)


Table 2

Procedure for concept analysis and synthesis

1. Identify literature related to the concept.A. Select 5±10 key sources that represent conceptual and research bases.2. Review each literature source for de®nitions, signs and symptoms, related factors, linkages with nursing interventions andnursing outcomes, and patient population.A. Complete the Diagnosis Resource Rating Tool.B. Complete the NDEC Concept Analysis Form.3. Compare signs and symptoms and related factors derived from the literature with signs and symptoms and related factors fromthe NANDA taxonomy.4. Generate or revise a diagnosis label, proposed de®nition for the diagnosis label, and a list of signs and symptoms and relatedfactors that re¯ect all dimensions of the diagnosis using information from the literature review and signs and symptoms and relatedfactors from the NANDA taxonomy.A. Development of conceptual de®nition.(1) Process (Rogers and Kan¯, 1993; Waltz et al., 1991).

(a) Develop a preliminary de®nition Ð NANDA or your own de®nition of the concept.(b) Literature review Ð critical analysis of the de®nitions and use of the concept in the literature. List all de®nitions of the

concept, synonyms, and their de®nitions.(c) Select the critical dimensions of the concept (i.e., the key elements consistently present).(d) Construct an outline, table, or diagram to represent key dimensions (Waltz et al., 1991).(e) Determine if the label is too complex (i.e., needs to be divided) or if labels are missing and need to be added.(f) State the conceptual de®nition (you may need to revise the de®nition as you develop signs and symptoms and related

factors).(2) Rules for de®nitions.

(a) The de®nition describes the complete meaning of the nursing diagnosis concept.(b) The de®nition as a whole is internally consistent with the nursing diagnosis concept.(c) The de®nition is clear and simple (Waltz et al., 1991).(d) The de®nition refers to all signs and symptoms included with the concept (describes the dimensions of the concept (Waltz

et al., 1991).B. Development of related factors and signs and symptoms.1. Process.

(a) Combine the lists of related factors generated from the NANDA taxonomy and from the literature review.(b) Combine the lists of signs and symptoms generated from the NANDA taxonomy and from the literature review.(c) Remove redundancy from the lists.(d) Cluster the list of related factors if too long or numerous.(e) Cluster the list of signs and symptoms if too long or too numerous.(f) Obtain additional sources if list is too short to determine if complete.(g) Review conceptual de®nition as needed.(h) Create distinct labels by associating each related factor to the diagnosis label.(i) Associate the signs and symptoms or clusters of signs and symptoms to each label created in the preceding step.

2. Rules for related factors and signs and symptoms (from Waltz et al., 1991).(a) Precision (explicit and speci®c terms are used).(b) Meaning adequacy exists between nursing diagnosis and related factors and between nursing diagnoses and signs and

symptoms; congruence exists between the nursing diagnosis with related factors and signs and symptoms).(c) Consistency (terms are used in a consistent manner).(d) Inclusiveness (all dimensions of the diagnosis are represented).(e) Measurability (empirical measures can be developed).(f) Utility (sensitive and useful for nursing).

C. Determine the appropriateness of the diagnosis label (this will be ongoing as the de®nition is developed).1. Recommend a new diagnosis label (label name), if needed, that is speci®c and understandable.2. Add new diagnosis labels as needed.3. Review diagnosis for consistency with the Rules outlined in Table 3.4. Provide all recommendation and supporting documentation to Co-PIs for review before presenting to the research team,including a copy of all articles used in the review.5. Submit the following to the research team:

(a) Diagnosis label.(b) Conceptual de®nition for diagnosis label.(c) A list of related factors.(d) A list of speci®c signs and symptoms for each diagnosis with a related factor.(e) All concept analysis forms.


adherence''. During their reading and discussions theyreversed their positions completely. However, they

eventually came to consensus on the word ``non-com-pliance'' after validation by the NDEC research team.A proforma (Appendix C) was developed for presen-

tation of the concept analyses by the individual to theDWG for discussion and critique. During and afterthe presentation suggestions are made for re®nement.

If the concerns raised by the group are numerous and/or substantive, another presentation for further discus-sion is scheduled. Normally the group's suggestions are

incorporated into a revised report, and the analysiswith accompanying references is forwarded to theRules Review Committee for review.

5.3. Conformity to Rules for the Development ofStandardized Languages

The Rules for the Development of StandardizedLanguages (Table 3) were developed by NDEC basedupon criteria from NANDA (NANDA, 1996), prin-ciples for development of computerized databases

(Evans et al., 1994; Gillenson, 1985; Loucopoulos andZicari, 1992), and the ANA Steering Committee onDatabases to Support Clinical Practice criteria for uni-

form nursing languages. The rules review processincludes the person(s) who conducted the original con-cept analysis so that questions can be answered

directly. Suggestions are given to the individual DWGmember, who re®nes the work and returns it to one ofthe principal investigators. The analysis is then for-

warded to the NDEC research team for evaluation andvalidation.

5.4. Validation by NDEC research team

The NDEC research team is composed of investi-

gators with clinical expertise in care of infants, chil-dren, adults, and older adults in the community,ambulatory care settings, and acute care facilities. Themembers' experience includes both qualitative and

quantitative research and a variety of theoretical per-spectives. Team recommendations are incorporated asappropriate. The re®ned diagnoses, all of which by this

point meet NANDA staging criteria 2.1, are thenready to be placed in a database and prepared for vali-dation by external experts, and are forwarded to the

NANDA o�ce. NANDA then submits them to itsnormal diagnosis review process.It is essential that the diagnoses, together with the

signs/symptoms and related/risk factors, be furthervalidated by nurses who practice in di�erent parts ofthe country and di�erent parts of the world to test andre®ne their applicability in other cultures. This requires

participation by nurses worldwide. One purpose of thispublication is to invite such participation. Already onegroup of nurses at the University of Wales Swansea is

working on selected diagnoses to check their validityfor use in the United Kingdom.The NDEC de®nition of ``expert'' includes nurses

who provide direct care in all specialty areas as well asnurses who have advanced education. The teambelieves that clinical expertise is as important as aca-

Table 3

Rules for the Development of Standardized Languages

Rule 1: A nursing diagnosis label is a noun phrase which describes a client health related state, behavior, or response.

Rule 2: A diagnosis label may or may not contain a qualifying terms which expresses:

a. Place of the diagnosis label on the health±illness continuum, such as At Risk, Actual, Potential for Enhanced.

b. Deviation from benchmark (change from baseline, norm, expectation): from the NANDA list of quali®ers.

c. A time dimension, such as acute, chronic, or intermittent.

Rule 3: Each nursing diagnosis label will be contain between two and four words. It will meet the following criteria for:

a. precision: exact, accurate

b. concision: compact, succinct

c. clarity: clearness in meaning, lacking ambiguity

d. non-synonymity: dissimilar and distinct from other diagnoses

Rule 4: Diagnosis labels which are at one or more levels are clinically useful.

Rule 5: The format for presentation of a nursing diagnosis shall be: (a) Label (1±4 words); (b) De®nition; (3) Associated

factors (i.e. risk factors, etiologic factors; factors associated or related to diagnosis label); (4) Signs and Symptoms;

(5) possible synonyms (i.e. UMLS); (6) References; and (7) related diagnoses (approved or candidate).

Rule 6: Each diagnosis label must have at least one related factor.

Rule 7: For each label and its associated related factor there must be at least one speci®c sign or symptom which

distinguish this diagnosis from other diagnoses.


demic education and credentials. The survey methodsand copies of the instruments to be used are available

from the authors upon request.

5.5. Clinical testing

Clinical testing across all settings can be accom-plished through several methods. Methods which can

be used in settings without a computerized clinical in-formation system include:

5.5.1. Chart or client record auditCharts or client records can be examined to deter-

mine the extent to which the phenomena representedin the records are captured by the labels, signs/symp-

toms, and related factors/etiologies as described byNDEC.

5.5.2. Applying the NDEC labels, signs/symptoms, andrelated factors/etiologies to actual patient/clients:Individual nurses can incorporate this process into

their daily clinical practice and normal documentation.

5.5.3. Case reviews

Case conferences and other forms of case review bya group(s) of clinicians can be used as an opportunityto examine the extent to which the diagnoses to be

validated capture and represent the patient phenomenaseen.

These methods complement and extend, and can beused in association with, the non-clinical methodsdescribed by the developers of ICNP (Clark, 1996).

Where a computerized clinical information system isavailable, clinical validation can be achieved throughdata retrieval and analysis using traditional statistical

or knowledge discovery/data mining methods.

6. Conclusion: an invitation

The work is exciting, and the methods we havedeveloped are already being used in other places to

identify and study the nursing concepts which are thebuilding blocks of our science. The content of our ter-minology and classi®cation systems must grow and

change as nursing itself develops and changes. How-ever, progress depends as much on the sharing of ideasas on technical developments. The greater the contri-

bution of nurses in all countries and all ®elds of prac-tice, the more con®dent we can be of the validity,reliability and sensitivity to cultural variations both of

the concepts and of the language we use to expressthem. This article is therefore an invitation to nursesworldwide to participate in the continuing work.


Appendix A

NDEC Concept Analysis Worksheet


Appendix B

NDEC Concept Analysis Worksheet for Empirical Studies


Appendix C

NDEC Completed Concept Analysis Form


Appendix D

DEC Diagnosis Work Group Source Rating Tool


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