# Defining Quality of Care in Lung Cancer

> **NIH VA I01** · ST. LOUIS VA MEDICAL CENTER · 2020 · —

## Abstract

Background: Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality in Veterans.
With the implementation of computed tomography screening, the incidence of Stage I lung cancer (tumors less
than 5 cm with no metastases) is increasing exponentially in Veterans. Stage I NSCLC is potentially curable with
surgery as the recognized gold standard of therapy. Wide variations exist in the care of Veterans with lung
cancer. These inconsistencies in care are directly linked to suboptimal short- and long-term outcomes. Lack of
clear guidelines is an important determinant of variable care. A number of national organizations have proposed
quality measures (QMs) for surgery in lung cancer. However, these measures have largely been developed
based upon retrospective institutional studies or expert opinion. A lack of evidence-based, validated QMs
remains a critical unmet need. To address this crucial gap in knowledge, we will use the large, prospectively
maintained Veterans Health Administration (VHA) database. The goal of this proposal is to develop a model to
define high-quality surgical care for lung cancer and understand factors impacting quality of surgery.
Significance: By creating a model of high-quality surgery for lung cancer, relevant to Veterans and the general
population, our proposal directly addresses the Department of Veterans Affairs (VA) priorities of quality of care
and transforming VA data into a national treasure. The recently launched VA-Partnership to increase Access to
Lung Screening aims to detect 80% of all lung cancers at a curable stage. Our study focuses on optimal therapy
for early-stage lung cancer, a current and, even more importantly, future imperative for the Veteran population.
Innovation: Our proposal is innovative both conceptually and technically. The conceptual innovation relates to
the holistic consideration of modifiable variables to define and impact high quality healthcare. The technical
innovation relates to the implementation of a unique approach utilizing a prospectively maintained dataset for
model development and validation.
Specific Aims: Aim 1. To identify model-based quality measures for surgery in lung cancer and determine which
have the greatest impact on short, and long-term outcomes. We hypothesize that among the candidate QMs,
our models will identify key measures that are associated with improved short-term outcomes (operative
morbidity and mortality) and long-term survival. Aim 2. To evaluate adherence to quality measures for surgery
and understand the contribution of geographic, patient-, disease-, and treatment-related factors in adherence to
quality measures for surgery in lung cancer. We hypothesize that younger, white patients, with smaller tumors,
treated at urban facilities will be associated with meeting QMs for surgery in lung cancer.
Methodology: In Aim 1, utilizing the VHA database, we will examine the relationship between adherence to
previously proposed (e.g. type of...

## Key facts

- **NIH application ID:** 9834082
- **Project number:** 1I01HX002475-01A2
- **Recipient organization:** ST. LOUIS VA MEDICAL CENTER
- **Principal Investigator:** Varun Puri
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2020
- **Award amount:** —
- **Award type:** 1
- **Project period:** 2019-10-01 → 2023-09-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9834082

## Citation

> US National Institutes of Health, RePORTER application 9834082, Defining Quality of Care in Lung Cancer (1I01HX002475-01A2). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/9834082. Licensed CC0.

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