# Enhancing the Efficiency of Data Collection for Surgical Quality Improvement

> **NIH VA I01** · VETERANS HEALTH ADMINISTRATION · 2021 · —

## Abstract

Background: Although the majority of national quality initiatives utilize electronic health record (EHR) or
administrative data, their ability to adequately discriminate performance has been brought into question and it
is unclear certain outcomes, such as postoperative complications, are accurately ascertained. By comparison,
clinical registry data, like the VA Surgical Quality Improvement Program (VASQIP), are widely considered
robust for performance evaluation and quality improvement (QI). But, VASQIP data collection is resource
intensive—data are manually abstracted by trained local Surgical Quality Nurses (SQNs) for a systematic
sample of surgical cases performed at all VA hospitals. VASQIP then uses the data to characterize the quality
and safety of surgical care at each hospital based on risk-adjusted 30-day morbidity and mortality rates.
Significance: VASQIP data collection practices present two important limitations. First, perioperative
outcome rates have significantly decreased the past two decades making it unclear whether systematic case
sampling is adequately powered to identify underperforming hospitals. Second, the time required for VASQIP
data collection detracts from SQNs’ ability to engage in other important job functions, like local QI activities.
Because SQNs spend substantial time working with VASQIP data, this represents an important missed
opportunity to identify a quality problem when it is evolving rather than when it has already occurred. As such,
alternative approaches that can provide reliable data and decrease the burden of data collection would have
tangible benefits for other national surgical and non-surgical QI initiatives within VA and the private sector.
Innovation: This project is novel because it can change the paradigm regarding the collection of QI data from
purely EHR or clinical registry to a more efficient hybrid model that could address reliability concerns
associated with the use of EHR (or administrative) data alone. It will also provide real-world, generalizable
data that can only be obtained within VA's data platform and can inform VA and the private sector national
surgical and non-surgical QI initiatives. We have two national operational partners: 1.) VA National Surgery
Office (NSO); 2.) Office of Reporting, Analytics, Performance, Improvement, and Deployment (RAPID).
Specific Aims: The overall goal is to address two important questions. First, given low perioperative
outcome rates across VA, is systematic sampling robust enough to inform surgical QI? Second, are hybrid data
(i.e.: EHR combined with clinical registry variables) a potentially reliable alternative for measuring VA
hospital surgical performance? These questions will be explored through the following specific aims: (1)
Evaluate whether analyzing all VASQIP-eligible surgical cases, relative to current systematic case sampling,
improves negative predictive value (i.e.: decreases false negative rates) for identifying VA hospitals with o...

## Key facts

- **NIH application ID:** 10547734
- **Project number:** 7I01HX003127-02
- **Recipient organization:** VETERANS HEALTH ADMINISTRATION
- **Principal Investigator:** Nader Nabile Massarweh
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2021
- **Award amount:** —
- **Award type:** 7
- **Project period:** 2021-05-01 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10547734

## Citation

> US National Institutes of Health, RePORTER application 10547734, Enhancing the Efficiency of Data Collection for Surgical Quality Improvement (7I01HX003127-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10547734. Licensed CC0.

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