Nursing management minimum data set: Cost-effective tool to demonstrate the value of nurse staffing in the big data science era

Lisiane Pruinelli, Connie W. Delaney, Amy Garcia, Barbara Caspers, Bonnie L. Westra

Research output: Contribution to journalArticle

14 Scopus citations

Abstract

There is a growing body of evidence of the relationship of nurse staffing to patient, nurse, and financial outcomes. With the advent of big data science and developing big data analytics in nursing, data science with the reuse of big data is emerging as a timely and cost-effective approach to demonstrate nursing value. The Nursing Management Minimum Date Set (NMMDS) provides standard administrative data elements, definitions, and codes to measure the context where care is delivered and, consequently, the value of nursing. The integration of the NMMDS elements in the current health system provides evidence for nursing leaders to measure and manage decisions, leading to better patient, staffing, and financial outcomes. It also enables the reuse of data for clinical scholarship and research.

Original languageEnglish (US)
Pages (from-to)66-71 and 89
JournalNursing Economics
Volume34
Issue number2
StatePublished - Mar 1 2016

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