Using the nursing minimum data set for the Netherlands (NMDSN) to illustrate differences in patient populations and variations in nursing activities

WTF Goossen*, PJMM Epping, T Feuth, WJA van den Heuvel, A Hasman, TWN Dassen

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    27 Citations (Scopus)

    Abstract

    Rationale: A nursing minimum data set (NMDS) provides data that are useful to legitimate nurses' contribution to healthcare. In Belgium and the US, such NMDS are operational, other countries are developing it, among which is the Netherlands.

    Objective: To evaluate whether the nursing minimum data set for the Netherlands (NMDSN) is suitable to describe the diversity of patient populations and the variability of nursing care.

    Methodology: Using the NMDSN data collection forms, patient data were collected from 15 different hospital wards. During one week, nurses manually completed the NMDSN list for every patient. The data analysis methodology from the Belgian MVG was used, including ridit analysis and graphs.

    Results: The NMDSN includes items related to hospital, patient demographics, medical condition, nursing process, nursing phenomena, nursing interventions, outcomes of nursing care, and complexity of care. There were 686 individual patients in the study, while for the data analysis their 2090 patient days in the hospital were used. Frequencies of nursing phenomena, nursing activities and results of care were calculated, transformed into ridit scores, and presented graphically as 'fingerprints'.

    Conclusion: The set of NMDSN items allows illustrating the diversity of patient populations, and variation in nursing care by means of 'fingerprints'. (C) 2001 Elsevier Science Ltd. All rights reserved.

    Original languageEnglish
    Pages (from-to)243-257
    Number of pages15
    JournalInternational Journal of Nursing Studies
    Volume38
    Issue number3
    Publication statusPublished - Jun-2001

    Keywords

    • nursing minimum data set
    • diversity and variability in hospital care
    • nursing diagnoses
    • nursing interventions
    • ridit analysis
    • RIDIT ANALYSIS
    • ORDINAL DATA

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