# Understanding physicians' diagnostic accuracy in the EHR era

> **NIH VA IK2** · MICHAEL E DEBAKEY VA MEDICAL CENTER · 2020 · —

## Abstract

Background and significance. Diagnostic errors are highly prevalent, affecting 12 million US adults
per year (~1 in 20) in outpatient settings alone. Half are estimated to be harmful, with an estimated 40,000-
80,000 people dying every year in the US because of diagnostic errors. Furthermore, Veterans, who have
more medical conditions than non-Veterans do, may be disproportionately affected by diagnostic errors.
Indeed, at least 1 million Veterans may have diagnostic errors each year, preventing them from receiving the
timely and helpful treatments they deserve. Given a high prevalence of diagnostic errors, researchers have
begun to identify the origins of these errors and have attributed cognitive causes to a majority of them. Many
times, however, the source of each error has been identified as a cognitive bias, which has been found to be
very difficult to detect and address. However, evidence suggests that cognitive characteristics of physicians
(e.g., their situation awareness [SA; ability to assess the current situation] and their metacognitive calibration
[ability to accurately assess their performance]) and the way they use the electronic health record (EHR) may
be two important, yet understudied factors contributing to diagnostic error. These areas of research and an
educational intervention to improve such factors to decrease error are the focus of this proposal. This research
addresses the overall goal of high quality and safe care for Veterans and the use of health care informatics, a
VA HSR&D cross-cutting priority area, by understanding how physicians utilize the EHR to diagnose patients
and how we can improve EHR use to improve diagnosis.
 Research plan. In this proposal, both cognitive characteristics of physicians and patterns of EHR use
will be examined as they relate to diagnostic accuracy. Then, an educational intervention aimed at improving
these factors will be developed and pilot-tested for the long-term goal of improving diagnostic accuracy and
reducing diagnostic errors in Veterans. The specific aims of this research are to: Aim 1) examine the
relationship between diagnostic accuracy and cognitive characteristics of physicians in a series of general
medical vignettes, Aim 2) investigate patterns of EHR use during diagnostic decision making and related
accuracy in a simulated, naturalistic EHR setting using standardized patients, and Aim 3) develop and pilot an
educational intervention that provides assessment and feedback on diagnosis-related performance in a
naturalistic EHR environment. We will use the SA in Adaptive Decision Making Framework from the human
factors field to guide this work. Aim 1 will consist of measuring physicians' cognitive characteristics, including
SA and metacognitive calibration obtained while physicians solve validated patient vignettes. Then the
relationships between these characteristics and diagnostic accuracy on the vignettes will be examined. Aim 2
will utilize simulation and Naturalistic Dec...

## Key facts

- **NIH application ID:** 9838672
- **Project number:** 5IK2HX002586-02
- **Recipient organization:** MICHAEL E DEBAKEY VA MEDICAL CENTER
- **Principal Investigator:** Ashley ND Meyer
- **Activity code:** IK2 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2020
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2018-10-01 → 2023-09-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9838672

## Citation

> US National Institutes of Health, RePORTER application 9838672, Understanding physicians' diagnostic accuracy in the EHR era (5IK2HX002586-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9838672. Licensed CC0.

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