# Leveraging pandemic practice changes to optimize evidence-based pneumonia care

> **NIH VA I01** · VA SALT LAKE CITY HEALTHCARE SYSTEM · 2024 · —

## Abstract

Background: The COVID-19 pandemic exposed critical failures in the management of pneumonia.
Pneumonia is the leading cause of death from infectious diseases, resulting in over 20,000 hospitalizations
and thousands of deaths across the VA system each year. For the past thirty years, the mainstays of
treatment have been antibiotics and supportive care, with little recognition of viral pathogens and the host
immune response. Our reliance on antibiotics has led not only to overuse and resistance, but also to a
stagnation in diagnostic and therapeutic research that left us ill-equipped for the viral pandemic.
Significance: The devastation of COVID19 has made it clear that our old models of disease are inadequate
for the optimal management of respiratory infection. Existing evidence surrounding empiric treatment in
pneumonia is poor, fraught with previous research that has been challenged by heterogeneity and a failure
to characterize patients with enough detail to identify beneficial treatment approaches. It is unlikely that
more of the same approach will advance care. This proposal contributes to a direction of clinical approach
toward a more complex causal model of infection that requires complex solutions.
Innovation and Impact: We will use state-of-the-art exploratory mixed methods that integrate EHR data
with survey and qualitative data to examine practice change. National analyses will allow for more inclusive
and feasible implementation solutions in diverse VA settings. This proposal breaks scientific ground in VA
informatics by leveraging variation with state-of-the-art causal inference methods. If we take the opportunity
to study new treatment approaches based on more complex clinical assessments, we will take an important
step toward developing better treatments in pneumonia and being better prepared for future pandemics.
Specific Aims: Aim 1. Describe emerging changes in the empiric use of antibiotic and steroids for
pneumonia using national practice data and qualitative interviews. Aim 2. Identify local conditions related to
emergent change in the use of empiric antibiotics and steroids using an exploratory mixed-methods design.
Aim 3. Identify and evaluate optimized, interpretable, tailored decision trees for empiric antibiotic and steroid
treatments in Veterans with pneumonia.
Methodology: Our mixed methods approach includes secondary data analyses of patient-, provider-, and
setting-level EHR data including treatment decisions and patient outcomes, combined with natural language
processing. We will apply mixed effects models to model the changes in selected treatments and outcomes
(hospitalization, deaths, secondary infection) between the pre-pandemic and later (July 2021-present)
periods, and to characterize heterogeneity in the trajectories of these variables across VA sites. To that
quantitative analysis, we will add qualitative data examining changes in VA providers’ cognitive processes
of diagnosis and management of pneumonia, incl...

## Key facts

- **NIH application ID:** 10830986
- **Project number:** 5I01HX003500-02
- **Recipient organization:** VA SALT LAKE CITY HEALTHCARE SYSTEM
- **Principal Investigator:** Barbara Ellen Jones
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2024
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2023-05-01 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10830986

## Citation

> US National Institutes of Health, RePORTER application 10830986, Leveraging pandemic practice changes to optimize evidence-based pneumonia care (5I01HX003500-02). Retrieved via AI Analytics 2026-05-29 from https://api.ai-analytics.org/grant/nih/10830986. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*