# Learning from Hospital Preparedness during COVID: Chronically Under-Resourced Nurses and Patient Safety

> **NIH AHRQ R01** · UNIVERSITY OF PENNSYLVANIA · 2022 · $399,292

## Abstract

Learning from Hospital Preparedness during COVID:
Chronically Under-Resourced Nurses and Patient Safety
This study will evaluate how hospital nurses weathered the COVID-19 public health emergency, whether and
to what extent hospital nurse resources (staffing, work environment, Magnet designation) buffered nurses from
poor outcomes (such as burnout) during the pandemic and facilitated recovery 3 years after the onset of the
COVID emergency, and the extent to which patient outcomes, safety, quality, and value of care indicators
paralleled changes in nurse outcomes and hospital nurse resources over the study period. We will accomplish
these objectives by leveraging already existing data from over 33,000 hospital nurses in 244 hospitals in New
York and Illinois, [Wave 1 data collected just before COVID (Dec 2019-Feb 2020); Wave 2 collected 1 year
after COVID onset] and by conducting primary data collection of repeat measures [Wave 3 to be collected 3
years after COVID onset (Oct 2022-Dec 2022)]. Each Wave includes repeated measures of nurse outcomes
(e.g., burnout, job dissatisfaction, intent to leave job), hospital nurse resources (staffing, work environment,
Magnet), measures of patient safety and quality of care, including items from the AHRQ Patient Safety Culture
survey. These cross-sections of data will be linked with contemporaneous (1) patient-level data from CMS
MedPAR Medicare to study risk-adjusted patient outcomes among patients hospitalized for common medical,
surgical, and COVID diagnoses; (2) Hospital Compare data to evaluate hospital-level measures of patient
satisfaction and healthcare value (Medicare spending per beneficiary), (3) American Hospital Association data
for considering organizational features of hospitals, and (4) publicly available COVID hospitalization data to
account for variation in COVID burden across hospitals. In combination, we will have 3 cross-sections of data
from 244 hospitals (with fluctuating nurse and patient populations) just before, 1 year and 3 years after the
onset of the COVID emergency. Our analytic approach uses multi-level nested (hierarchically-related) linear
and logistic regression models (with interaction terms). The COVID emergency offers a unique opportunity to
make a major advance in our scientific understanding of the potentially causal relationships between nurse
outcomes and patient outcomes, which have until now largely only been rigorously evaluated in the cross-
section. The tremendous shock imposed by the COVID emergency, combined with our propitiously timed data,
enable us to evaluate how the pandemic impacted hospital nurses and what hospital factors contribute to a
more favorable recovery in the years following the COVID emergency. Together, this evidence will inform high-
impact actionable policy and organizational solutions for building and sustaining safe, high value healthcare
systems that can endure future public health emergencies and thrive during ordinary times.

## Key facts

- **NIH application ID:** 10498363
- **Project number:** 1R01HS028978-01
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Karen Blanchette Lasater
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** AHRQ
- **Fiscal year:** 2022
- **Award amount:** $399,292
- **Award type:** 1
- **Project period:** 2022-09-06 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10498363

## Citation

> US National Institutes of Health, RePORTER application 10498363, Learning from Hospital Preparedness during COVID: Chronically Under-Resourced Nurses and Patient Safety (1R01HS028978-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10498363. Licensed CC0.

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