Exploring the Nursing Minimum Data Set for The Netherlands using multidimensional scaling techniques

Exploring the Nursing Minimum Data Set for The Netherlands using multidimensional scaling techniquesRationale.  To fulfil the need for a systematic collection of nursing data that give insight in nursing care and its benefits and costs, a nursing minimum data set (NMDS) has been developed and validated for Dutch general hospitals. A NMDS provides data describing the diversity in patient populations and variability in nursing activities that can be analysed in various ways. Aim of the study.  To explore and compare the fundamental underlying dimensions describing patient problems and nursing interventions in Dutch general hospital wards. Methods.  Data of predominantly nominal and ordinal measurement level that were collected with the NMDS for The Netherlands on 15 Dutch hospital wards underwent two consecutive steps: first, they were transformed into metric data by means of RIDIT (relative to an identified distribution) analysis; secondly, they were analysed by means of multidimensional scaling. Results.  Multidimensional scaling techniques yielded a fairly good three‐dimensional solution of the NMDS data. Hospital wards could be distinguished from each other on the basis of patient problems and nursing interventions most common on some wards but not on others. The core aspects underlying patient problems concerned dependency problems, life threatening problems and endogenous–exogenous problems, while discriminating nursing interventions were cure–care activities, internally–externally oriented activities and psychosocial–physical interventions. Limitations.  Not all types of hospital wards were represented, which limits the representativity of the results for Dutch general hospitals. Furthermore, the patient sample size over the 15 wards was relatively small. Conclusion.  The constructs are consistent with NMDS findings in Belgium and findings from practice, which contributes to their content validity.