Nursing classification systems: necessary but not sufficient for representing "what nurses do" for inclusion in computer-based patient record systems.
Our premise is that from the perspective of maximum flexibility of data usage by computer-based record (CPR) systems, existing nursing classification systems are necessary, but not sufficient, for representing important aspects of "what nurses do." In particular, we have focused our attention on those classification systems that represent nurses' clinical activities through the abstraction of activities into categories of nursing interventions. In this theoretical paper, we argue that taxonomic, combinatorial vocabularies capable of coding atomic-level nursing activities are required to effectively capture in a reproducible and reversible manner the clinical decisions and actions of nurses, and that, without such vocabularies and associated grammars, potentially important clinical process data is lost during the encoding process. Existing nursing intervention classification systems do not fulfill these criteria. As background to our argument, we first present an overview of the content, methods, and evaluation criteria used in previous studies whose focus has been to evaluate the effectiveness of existing coding and classification systems. Next, using the Ingenerf typology of taxonomic vocabularies, we categorize the formal type and structure of three existing nursing intervention classification system--Nursing Interventions Classification, Omaha System, and Home Health Care Classification. Third, we use records from home care patients to show examples of lossy data transformation, the loss of potentially significant atomic data, resulting from encoding using each of the three systems. Last, we provide an example of the application of a formal representation methodology (conceptual graphs) which we believe could be used as a model to build the required combinatorial, taxonomic vocabulary for representing nursing interventions.
Henry
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Department of Community Health Systems, School of Nursing, University of California, San Francisco 94143-0608, USA. nursing%sue_henry@ccmail.ucsf.edu
Mead
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D000043:Abstracting and Indexing; D003625:Data Collection; D003627:Data Interpretation, Statistical; D006801:Humans; D007587:Job Description; D016347:Medical Records Systems, Computerized; D009732:Nursing Care / Q000145:classification* / Q000379:methods; D009737:Nursing Records; D015203:Reproducibility of Results; D018875:Vocabulary, Controlled