# Nursing Resources and Health Care-Associated Infections: Measures of Hospital Performance

> **NIH AHRQ R01** · EMORY UNIVERSITY · 2020 · $399,999

## Abstract

PROJECT SUMMARY
Healthcare-associated infections (HAIs) remain common, risking patient lives, adding to health care costs, and
contributing to the major public health problem of antibiotic-resistant infections. Clinical interventions have
been found effective in preventing HAIs under controlled conditions but not under usual care conditions.
Infection prevention interventions have not focused on improving hospital-wide nurse work environments as
recommended by the Institute of Medicine. The primary aim of this study is to determine whether nursing
resources such as work environments and other modifiable features of nursing, including nurse staffing, skill
mix, workforce stability, and education are associated with HAIs, with a goal of identifying promising hospital
level strategies to facilitate infection reduction. Measures of these modifiable features of nursing will be derived
by aggregating, to the hospital level, unique survey data collected in 2015-2016 from 27,319 nurses employed
in 583 hospitals in four large states: California, Florida, New Jersey, and Pennsylvania. The hospitals in these
large states account for close to a quarter of hospital discharges nationally. These hospital-level measures,
together with measures of hospital size, teaching status, and technology derived from American Hospital
Association Annual Survey data, will then be merged, separately, with infection data from two different
sources; 1) patient-level data that combine information from the Medicare Provider and Analysis Review files
(MEDPAR), the Medicare Outpatient Standard Analytic File, and the Medicare Carrier File (Provider Part B)
and includes information essential for risk adjustment and enhanced measures of infections, and 2) hospital-
level standardized infection ratios (SIR) using data from the Centers for Disease Control and Prevention (CDC)
that are publicly reported on the Centers for Medicare and Medicaid Services (CMS) Hospital Compare
website. Multilevel logit models and hierarchical linear models (for the patient level data) will be used to
estimate the effects of the different nursing resource measures on the likelihoods of different groups of medical
and surgical patients acquiring different infections, before and after adjusting for other hospital and patient
characteristics. Ordinary least squares regression models (for the hospital level data) will be used to estimate
these same nursing effects on the risk-adjusted standardized infection ratios, before and after controlling for
other hospital characteristics. The large sample of representative (rather than volunteer) hospitals, the use of
the Medicare Part B data to uncover infections in patients discharged to their home or a care facility that were
not recognized during their hospital stay, and the use of unique data on work environments and other nursing
characteristics will make it possible to capture significant effects of nursing which prior investigations have
been unable to explore. T...

## Key facts

- **NIH application ID:** 9963182
- **Project number:** 5R01HS026232-02
- **Recipient organization:** EMORY UNIVERSITY
- **Principal Investigator:** EDMUND R BECKER
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** AHRQ
- **Fiscal year:** 2020
- **Award amount:** $399,999
- **Award type:** 5
- **Project period:** 2019-07-01 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9963182

## Citation

> US National Institutes of Health, RePORTER application 9963182, Nursing Resources and Health Care-Associated Infections: Measures of Hospital Performance (5R01HS026232-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9963182. Licensed CC0.

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