# How Can We Make Invasive Non-Surgical Procedures Safer? Using Big Data to Identify Adverse Events and Opportunities to Mitigate Harm

> **NIH VA I01** · VA BOSTON HEALTH CARE SYSTEM · 2021 · —

## Abstract

Background: This is the second submission of an HSR&D IIR proposal to transition Dr. Hillary Mull, Ph.D.
from her HSR&D Career Development Award (CDA) project toward an independent VA health services
research career. The proposed work seeks to build on Dr. Mull's successful CDA project by adapting her
approach to developing and validating a surveillance model for outpatient surgery to invasive procedures in
non-surgical clinical specialties: interventional cardiology, interventional radiology and gastrointestinal
endoscopy procedures. This informatics-based approach relies on combining text and structured data fields in
the VA Corporate Data Warehouse (CDW). Dr. Mull's CDA-funded surveillance research identified an adverse
event rate of 9% and had a positive predictive value of 85%, dramatically improving adverse event detection.
 Significance/Impact: Presently, there is no active surveillance of invasive procedures and preliminary
analyses and conversations with frontline staff suggest adverse events occur with some frequency and impose
significant patient harm. Prior work found invasive procedures in these three specialties result in post-
procedure emergency room visits or hospitalizations exceeding 50,000 cases annually. Non-VA literature
suggests half of this utilization may be preventable with improvements in clinical care (e.g., adherence to
antibiotic prescribing guidelines). This field of research will become even more important as care increasingly
transitions outside the operating room. Detecting and monitoring adverse events in understudied settings using
existing data in the VA CDW is consistent with HSR&D funding priority C-Healthcare Informatics.
 Innovation: Together with experts from COINs around the country and the support of operational partners
from each clinical specialty, Pharmacy Benefits Management and VA Informatics and Computing
Infrastructure, Dr. Mull proposes to apply her CDA expertise to build a surveillance system to identify invasive
non-surgical procedures with preventable adverse events; these procedures are not subject to any VA
surveillance activities. A second gap this work addresses is the lack of a nationally available dataset capturing
procedural anesthesia use. We will use chart review and text-query data mining methods to obtain this
information. The culmination of our IIR work will be a comprehensive database of adverse events and
potentially modifiable contributing factors, including procedural anesthesia data, available to VA researchers.
 Specific Aims: 1) develop and validate surveillance models using FY17-20 data; 2) test the surveillance
system (apply model coefficients, perform limited chart review on a monthly basis) from FY21-22, and refine
the system using additional CDW variables; 3) test hypotheses related to modifiable processes including
whether a trained anesthesia provider was involved or patients received inappropriate antibiotics.
 Methodology: Our sample includes non-surgical invasive ...

## Key facts

- **NIH application ID:** 10159112
- **Project number:** 5I01HX002694-02
- **Recipient organization:** VA BOSTON HEALTH CARE SYSTEM
- **Principal Investigator:** Hillary Jane Mull
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2021
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2020-04-01 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10159112

## Citation

> US National Institutes of Health, RePORTER application 10159112, How Can We Make Invasive Non-Surgical Procedures Safer? Using Big Data to Identify Adverse Events and Opportunities to Mitigate Harm (5I01HX002694-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10159112. Licensed CC0.

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