The effect of data aggregation on estimations of nurse staffing and patient outcomes

Health Serv Res. 2021 Dec;56(6):1262-1270. doi: 10.1111/1475-6773.13866. Epub 2021 Sep 2.


Objective: To examine how estimates of the association between nurse staffing and patient length of stay (LOS) change with data aggregation over varying time periods and settings, and statistical controls for unobserved heterogeneity.

Data sources/study setting: Longitudinal secondary data from October 2002 to September 2006 for 215 intensive care units and 438 general acute care units at 143 facilities in the Veterans Affairs (VA) health care system.

Research design: This retrospective observational study used unit-level panel data to analyze the association between nurse staffing and LOS. This association was measured over both a month-long and a year-long period, with and without fixed effects.

Data collection: We used VA administrative data to obtain patient data on the severity of illness and LOS, as well as labor hours and wages for each unit by month.

Principal findings: Overall, shorter LOS was associated with higher nurse staffing hours and lower proportions of hours provided by licensed professional nurses (LPNs), unlicensed personnel, and contract staff. Estimates of the association between nurse staffing and LOS changed in magnitude when aggregating data over years instead of months, in different settings, and when controlling for unobserved heterogeneity.

Conclusions: Estimating the association between nurse staffing and LOS is contingent on the time period of analysis and specific methodology. In future studies, researchers should be aware of these differences when exploring nurse staffing and patient outcomes.

Keywords: length of stay; methods; nurse staffing; nursing workforce; skill mix.

Publication types

  • Observational Study
  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Administrative Claims, Healthcare / statistics & numerical data
  • Aged
  • Data Aggregation*
  • Female
  • Humans
  • Length of Stay / statistics & numerical data*
  • Longitudinal Studies
  • Male
  • Nursing Staff, Hospital / statistics & numerical data*
  • Personnel Staffing and Scheduling / statistics & numerical data*
  • Retrospective Studies
  • Severity of Illness Index
  • Time Factors
  • United States
  • United States Department of Veterans Affairs