R18HS029345
Project Grant
Overview
Grant Description
Diagnostic Accuracy Through Advancing EHR Display, Education and Surveillance (DATA-EYES) - Project Summary:
Diagnostic error (DE) remains one of the most costly and prevalent forms of preventable medical error, with nearly 12 million Americans affected annually at an estimated cost of over $100 billion. Unfortunately, efforts to reduce DE have remained largely unsuccessful. This is in large part due to the fact that etiology of DE is highly complex with multiple contributing factors.
However, central to the diagnostic process are critical cognitive processes such as the physician's ability to find and process relevant information, reason with this information, and formulate a diagnosis. With over 95% of healthcare providers adopting electronic health records (EHRs), these systems are the primary source of nearly all patient information and, therefore, shape the diagnostic process.
While it is recognized that the EHR contributes to the problem of DE, the identification and relative contribution of how, when, and why the EHR contributes to DE, specifically as it relates to the sociotechnical domains of software, user, and system (workflow), are poorly described.
We have attempted to better define this through the analysis of medical malpractice cases (CRICO) and patient safety event (PSE) report forms related to DE in ambulatory care. From our medical malpractice analysis, nearly 60% of cases of DE had a definitive EHR contribution, with another 19% indeterminate. The EHR contributed most often during the testing phase of the diagnostic process with the most common EHR hazards related to data interpretation, order placement, and execution of plan.
However, this analysis relies on manual evaluation of unstructured data which is highly time-consuming, lacks specificity, and is impractical for widespread adoption. Once the relative contribution of EHRs to DE can be determined, health systems can then deploy solutions to help mitigate. Ideally, this will include the ability to use simulation to guide both EHR redesign and training, in situ observation of how the EHR integrates into daily workflow, and a strategy to monitor the impact of these interventions.
The goal of this proposal is to establish a Diagnostic Center of Excellence (DATAEYES) focused on identification of EHR contribution to DE and use this information to deploy a suite of solutions to improve software, user, and system. We will achieve this by using national data to create an informed taxonomy to be integrated into institution data collection tools, to facilitate institution-wide capture of EHR contributions to DE in Aim #1.
We will then develop and validate these tools in Aim #2 and use this information, in combination with in situ workflow observations, to inform how, when, and why the EHR is contributing to DE. This information will be used to create high-fidelity simulated EHR charts to facilitate both workflow-specific training on EHR best practices and guide EHR redesign and monitor the impact of these interventions via EHR audit logs in Aim #3.
The 3 centers participating (OHSU, MedStar Health, Brigham and Women's Hospital) will allow further ascertainment of the impact of both EHR vendors being studied (Cerner and Epic) and local workflow-specific practices. We will then leverage our collaborations with patient safety organizations and industry to disseminate these findings, and the infrastructure developed at DATAEYES will serve as a core resource for the other DCE sites, allowing for rapid evaluation and prototyping of future EHR-based solutions.
Diagnostic error (DE) remains one of the most costly and prevalent forms of preventable medical error, with nearly 12 million Americans affected annually at an estimated cost of over $100 billion. Unfortunately, efforts to reduce DE have remained largely unsuccessful. This is in large part due to the fact that etiology of DE is highly complex with multiple contributing factors.
However, central to the diagnostic process are critical cognitive processes such as the physician's ability to find and process relevant information, reason with this information, and formulate a diagnosis. With over 95% of healthcare providers adopting electronic health records (EHRs), these systems are the primary source of nearly all patient information and, therefore, shape the diagnostic process.
While it is recognized that the EHR contributes to the problem of DE, the identification and relative contribution of how, when, and why the EHR contributes to DE, specifically as it relates to the sociotechnical domains of software, user, and system (workflow), are poorly described.
We have attempted to better define this through the analysis of medical malpractice cases (CRICO) and patient safety event (PSE) report forms related to DE in ambulatory care. From our medical malpractice analysis, nearly 60% of cases of DE had a definitive EHR contribution, with another 19% indeterminate. The EHR contributed most often during the testing phase of the diagnostic process with the most common EHR hazards related to data interpretation, order placement, and execution of plan.
However, this analysis relies on manual evaluation of unstructured data which is highly time-consuming, lacks specificity, and is impractical for widespread adoption. Once the relative contribution of EHRs to DE can be determined, health systems can then deploy solutions to help mitigate. Ideally, this will include the ability to use simulation to guide both EHR redesign and training, in situ observation of how the EHR integrates into daily workflow, and a strategy to monitor the impact of these interventions.
The goal of this proposal is to establish a Diagnostic Center of Excellence (DATAEYES) focused on identification of EHR contribution to DE and use this information to deploy a suite of solutions to improve software, user, and system. We will achieve this by using national data to create an informed taxonomy to be integrated into institution data collection tools, to facilitate institution-wide capture of EHR contributions to DE in Aim #1.
We will then develop and validate these tools in Aim #2 and use this information, in combination with in situ workflow observations, to inform how, when, and why the EHR is contributing to DE. This information will be used to create high-fidelity simulated EHR charts to facilitate both workflow-specific training on EHR best practices and guide EHR redesign and monitor the impact of these interventions via EHR audit logs in Aim #3.
The 3 centers participating (OHSU, MedStar Health, Brigham and Women's Hospital) will allow further ascertainment of the impact of both EHR vendors being studied (Cerner and Epic) and local workflow-specific practices. We will then leverage our collaborations with patient safety organizations and industry to disseminate these findings, and the infrastructure developed at DATAEYES will serve as a core resource for the other DCE sites, allowing for rapid evaluation and prototyping of future EHR-based solutions.
Funding Goals
TO SUPPORT RESEARCH AND EVALUATIONS, DEMONSTRATION PROJECTS, RESEARCH NETWORKS, AND MULTIDISCIPLINARY CENTERS AND TO DISSEMINATE INFORMATION ON HEALTH CARE AND ON SYSTEMS FOR THE DELIVERY OF SUCH CARE INVOLVING: (1) THE QUALITY, EFFECTIVENESS, EFFICIENCY, APPROPRIATENESS AND VALUE OF HEALTH CARE SERVICES, (2) QUALITY MEASUREMENT AND IMPROVEMENT, (3) THE OUTCOMES, COST, COST-EFFECTIVENESS, AND USE OF HEALTH CARE SERVICES AND ACCESS TO SUCH SERVICES, (4) CLINICAL PRACTICE, INCLUDING PRIMARY CARE AND PRACTICE-ORIENTED RESEARCH, (5) HEALTH CARE TECHNOLOGIES, FACILITIES AND EQUIPMENT, (6) HEALTH CARE COSTS, PRODUCTIVITY, ORGANIZATION, AND MARKET FORCES, (7) HEALTH PROMOTION AND DISEASE PREVENTION, INCLUDING CLINICAL PREVENTIVE SERVICES, (8) HEALTH STATISTICS, SURVEYS, DATABASE DEVELOPMENT, AND EPIDEMIOLOGY, (9) DIGITAL HEALTHCARE RESEARCH, AND (10) PATIENT SAFETY RESEARCH, INCLUDING HEALTHCARE-ASSOCIATED INFECTIONS. IN SUPPORT OF THIS RESEARCH, THE AGENCY HAS A SPECIAL INTEREST IN HEALTH CARE AND ITS DELIVERY IN THE INNER CITY, IN RURAL AREAS, AND FOR PRIORITY POPULATIONS (LOW-INCOME GROUPS, MINORITY GROUPS, WOMEN, CHILDREN, THE ELDERLY, AND INDIVIDUALS WITH SPECIAL HEALTH CARE NEEDS).
Grant Program (CFDA)
Awarding Agency
Place of Performance
Portland,
Oregon
972393011
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 298% from $999,999 to $3,984,765.
Oregon Health & Science University was awarded
Enhancing Diagnostic Accuracy with EHR Optimization - DATAEYES Grant
Project Grant R18HS029345
worth $3,984,765
from Center for Quality Improvement and Patient Safety in September 2022 with work to be completed primarily in Portland Oregon United States.
The grant
has a duration of 4 years and
was awarded through assistance program 93.226 Research on Healthcare Costs, Quality and Outcomes.
The Project Grant was awarded through grant opportunity Diagnostic Centers of Excellence: Partnerships to Improve Diagnostic Safety and Quality (R18).
Status
(Ongoing)
Last Modified 9/24/25
Period of Performance
9/30/22
Start Date
9/29/26
End Date
Funding Split
$4.0M
Federal Obligation
$0.0
Non-Federal Obligation
$4.0M
Total Obligated
Activity Timeline
Transaction History
Modifications to R18HS029345
Additional Detail
Award ID FAIN
R18HS029345
SAI Number
R18HS029345-3865100832
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Public/State Controlled Institution Of Higher Education
Awarding Office
75AHRQ AHRQ Office of Management Services/Division of Grants Management
Funding Office
75EL00 AHRQ CENTER FOR QUALITY IMPROVEMENT AND PATIENT SAFETY
Awardee UEI
NPSNT86JKN51
Awardee CAGE
0YUJ3
Performance District
OR-01
Senators
Jeff Merkley
Ron Wyden
Ron Wyden
Budget Funding
Federal Account | Budget Subfunction | Object Class | Total | Percentage |
---|---|---|---|---|
Healthcare Research and Quality, Agency for Healthcare Research and Quality, Health and Human Services (075-1700) | Health research and training | Grants, subsidies, and contributions (41.0) | $1,999,995 | 100% |
Modified: 9/24/25