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PubMed · 11079868

Describing patient problems & nursing treatment patterns using nursing minimum data sets (NMDS & NMMDS) & UHDDS repositories.

C Delaney·D Reed·M Clarke
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Abstract

Dramatic changes in health care have intensified practitioners' efforts to access and use information to determine more efficacious approaches to patient outcomes. The overall goal of the study is to measure the influence of nursing informatics clinical reasoning decision support interventions on patient outcomes. This paper describes Phases I of the study: the methodology for establishing and testing the usefulness of large data repositories comprised of three minimum data sets, including the Nursing Minimum Data Set (NMDS), the Nursing Management Minimum Data Set (NMMDS), and the Uniform Hospital Discharge Data Set (UHDDS), and the American Nurses Association Quality Indicators to support effectiveness research. The use of generic data modeling to construct a clinical nursing repository of more than 477,000 electronic records is discussed. Patient problem and treatment profiles, patterns, and variations based on standardized analyzing classifications are described for inpatient adult samples, and nursing and medical diagnosis groups.

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Databases, FactualDecision Support TechniquesHumansMedical Records Systems, ComputerizedNursing DiagnosisNursing ProcessNursing ResearchPatient CareRetrospective StudiesJournal Article

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C Delaney, D Reed, M Clarke. 2000. Describing patient problems & nursing treatment patterns using nursing minimum data sets (NMDS & NMMDS) & UHDDS repositories.. https://pubmed.ncbi.nlm.nih.gov/11079868/

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