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Nursing minimum data sets: Findings from an umbrella review.

Francesca Freguia1, Matteo Danielis1, Renzo Moreale1

  • 1School of Nursing, Department of Medical Sciences, 9316University of Udine, Udine, Italy.

Health Informatics Journal
|May 31, 2022
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Summary

This umbrella review summarizes existing research on Nursing Minimum Data Sets (NMDSs). It highlights the need for a standardized NMDS with core elements and common language to support health digitalization.

Keywords:
data evaluationdigital healthinformationliterature reviewnursing carenursing minimum data setumbrella review

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Area of Science:

  • Nursing Informatics
  • Health Services Research
  • Data Standards

Background:

  • Nursing documentation practices are largely localized and paper-based.
  • The increasing digitalization of healthcare necessitates standardized data collection.
  • Nursing Minimum Data Sets (NMDSs) offer a potential framework for consistent nursing data.

Purpose of the Study:

  • To synthesize evidence on the methodological and reporting features of reviews concerning NMDSs.
  • To identify recommendations for NMDS development from existing literature.
  • To summarize proposed categories and items for inclusion in NMDSs.

Main Methods:

  • An umbrella review methodology was employed.
  • Searches were conducted in MEDLINE, CINAHL, and Scopus for secondary studies up to November 2021.
  • Included reviews were critically appraised using the Checklist for Systematic Review and Research Syntheses.

Main Results:

  • Eight reviews published between 1995 and 2018 were included, exhibiting variable methodological quality.
  • Recommendations spanned overall, clinical, research, and management levels.
  • Seven distinct NMDSs were identified, differing in purpose, elements, populations, and taxonomies.

Conclusions:

  • A common NMDS is needed to provide a reference point for nursing documentation in the digital age.
  • Developing a standardized NMDS requires establishing core elements, a common language, and linkages with other datasets.
  • Improving the quality of reviews in this field is also recommended.