PURPOSE: To map the problem or diagnosis terms from three nomenclatures, term to term, to determine commonalities and differences; and to determine whether it is possible to develop a single vocabulary that contains the best features of all. When different nomenclatures are used in different settings, continuity of care is hampered by the need to re-state problems and interventions. DESIGN: The sample for this descriptive analysis was 396 terms from three nursing diagnosis and problem nomenclatures recognized by the American Nurses Association: the North American Nursing Diagnosis Association (NANDA) Approved List, the Home Health Care Classification (HHCC), and the Omaha System. METHOD: Terms from each of the three nomenclatures were mapped to terms in each of the others. Consensus methods were used to resolve differences in mapping decisions. Terms were characterized as "Same," "Similar," "Broader," "Narrower," and "No Match." Validation of consistency and accuracy was done by reverse mapping, use of syllogisms, use of taxonomic groupings, and expert review. RESULTS: Of 396 terms, 21 concepts accounting for 63 terms were found to be the same or similar in all three nomenclatures; 91 terms were unique to the nomenclature in which they were found ("No Match"). The remaining 242 terms had a narrower or broader relationship to at least one term in another nomenclature. In all three nomenclatures, inconsistencies existed in level of abstractness of the diagnosis or problem terms, and in definition and placement of terms within their own taxonomic structure. CONCLUSION: Because of differences in structure and incompatible taxonomic arrangements, a master list of "preferred terms" taken from the three nomenclatures is not feasible. However, the mappings are useful for determining commonalities and the unique contributions of each nomenclature, which can facilitate the development of a uniform language for nursing diagnoses. The mapping can also form the basis for automatic translation of computer-stored nursing diagnoses from one setting to another when different nomenclatures are used.
PURPOSE: To map the problem or diagnosis terms from three nomenclatures, term to term, to determine commonalities and differences; and to determine whether it is possible to develop a single vocabulary that contains the best features of all. When different nomenclatures are used in different settings, continuity of care is hampered by the need to re-state problems and interventions. DESIGN: The sample for this descriptive analysis was 396 terms from three nursing diagnosis and problem nomenclatures recognized by the American Nurses Association: the North American Nursing Diagnosis Association (NANDA) Approved List, the Home Health Care Classification (HHCC), and the Omaha System. METHOD: Terms from each of the three nomenclatures were mapped to terms in each of the others. Consensus methods were used to resolve differences in mapping decisions. Terms were characterized as "Same," "Similar," "Broader," "Narrower," and "No Match." Validation of consistency and accuracy was done by reverse mapping, use of syllogisms, use of taxonomic groupings, and expert review. RESULTS: Of 396 terms, 21 concepts accounting for 63 terms were found to be the same or similar in all three nomenclatures; 91 terms were unique to the nomenclature in which they were found ("No Match"). The remaining 242 terms had a narrower or broader relationship to at least one term in another nomenclature. In all three nomenclatures, inconsistencies existed in level of abstractness of the diagnosis or problem terms, and in definition and placement of terms within their own taxonomic structure. CONCLUSION: Because of differences in structure and incompatible taxonomic arrangements, a master list of "preferred terms" taken from the three nomenclatures is not feasible. However, the mappings are useful for determining commonalities and the unique contributions of each nomenclature, which can facilitate the development of a uniform language for nursing diagnoses. The mapping can also form the basis for automatic translation of computer-stored nursing diagnoses from one setting to another when different nomenclatures are used.
Authors: Patricia C Dykes; Hyeon-eui Kim; Denise M Goldsmith; Jeeyae Choi; Kumiko Esumi; Howard S Goldberg Journal: J Am Med Inform Assoc Date: 2008-12-11 Impact factor: 4.497
Authors: Vanessa Cristina Alves; Weslen Carlos Junior de Freitas; Jeferson Silva Ramos; Samantha Rodrigues Garbis Chagas; Cissa Azevedo; Luciana Regina Ferreira da Mata Journal: Rev Lat Am Enfermagem Date: 2017-12-21