# How nursing staff skill mix, education and experience modify patient acuity-based estimates of required unit staffing

> **NIH VA I01** · VETERANS ADMIN PALO ALTO HEALTH CARE SYS · 2022 · —

## Abstract

A significant body of literature demonstrates that the amount of nurse staffing, as well as the mix, available to
provide care to patients has an effect on patient outcomes. This relationship is present across multiple health
care systems, and has been shown to correlate with a number of different medical outcomes. While these
findings have impacted practice and policy, most studies of the relationship between nurse staffing and patient
outcomes are still conducted at the level of the entire hospital, which averages patient outcomes across a wide
variety of staffing levels. Detail at the unit level is essential to understanding the impact of nurse staffing
variability, and to designing effective interventions. In one of the few studies assessing staffing at the unit and
shift level over time, and using the difference between staffing targets and actual staffing over time, the gap
was significantly associated with differences in patient mortality. Such a measure of nurse staffing allows
organizations to set staffing target based on patient, unit, and organizational context, and design appropriate
staffing interventions while still providing a comparable staffing metric.
Health care systems struggle to define recommended or targeted levels of staffing. In response to national
concerns about system practices that impact patient outcomes, the VA Office of Nursing Services (ONS)
promulgated a Staffing Methodology (SM) directive in 2010, requiring the use of unit and facility level review of
staffing and patient data to formulate custom recommendations for target staffing levels on each shift. The
proposed study fills a gap in our understanding of how levels of nurse staffing affect patient outcomes.
Variation in nurse staffing level persists at both the facility and unit level. It is not clear, however, how changes
in staffing hours and staff mix at the unit level within facilities affect outcomes for patients. Critical questions
about the type and quantity of nursing hours actually delivered to patients are not known, nor is the effect of
variability in the gap between target and actual known. This project will use regression models to extend the
current knowledge of how nurse staffing affects patient outcomes (mortality, failure to rescue, infections related
to catheters, and risk-adjusted length of stay) with two major objectives.
 Aim One: Use the extensive VA data systems to conduct the most rigorous study to date on how nurse
staffing levels and nurse affect patient outcomes. This will be the first large-scale examination of how shift-
level staffing affects patient outcomes, AND the first large-scale study to simultaneously use unit-level data
with controls for staffing levels, characteristics of the nurses, extensive patient risk-adjustment, and control
for use of other health care staff, including physicians. We will examine the gap between targeted and actual
nursing hours for each shift for the 66 VA facilities that use the AcuStaf nurse st...

## Key facts

- **NIH application ID:** 10209948
- **Project number:** 5I01HX002274-03
- **Recipient organization:** VETERANS ADMIN PALO ALTO HEALTH CARE SYS
- **Principal Investigator:** CIARAN S. PHIBBS
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2022
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2019-06-01 → 2022-09-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10209948

## Citation

> US National Institutes of Health, RePORTER application 10209948, How nursing staff skill mix, education and experience modify patient acuity-based estimates of required unit staffing (5I01HX002274-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10209948. Licensed CC0.

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