Diagnostic error is believed to be the most common type of patient safety event. Affecting between 5-10% of all patient encounters, it results in significant patient morbidity and mortality. Ambulatory care is especially susceptible to this, with diagnostic errors outnumbering other types 6:1 and 5% of patients seeking ambulatory care experiencing diagnostic error. Comprised of delayed and missed diagnosis, diagnostic error is frequently the consequence of the inability to effectively access and/or synthesize complex medical information for medical decision making. With the adoption of the HITECH Act over 95% of hospitals and 80% of office based practice utilize Electronic Health Records (EHRs) as their primary source of patient information. With the rapid expansion of EHRs, there is growing appreciation of the myriad of ways in which EHRs contribute to failures in information gathering and/or synthesis. These EHR use errors are often a combination of system design issues and poor user training. Simulation affords a powerful tool to both study, in a systematic way, the means in which EHRs contribute to said errors as well as provide a powerful training tool. We previously demonstrated that hi-fidelity EHR based simulation exercises in the ICU, using purposively designed EHR charts, uncovers the contribution of EHR use errors to diagnostic error. Participation in these exercises improves the recognition of embedded trends in patient information required for effective diagnostic accuracy by 50%. While we have created a number of simulation based exercises for critical care, the workflow, cognitive errors and EHR chart structure are fundamentally different for ambulatory care, representing a greater degree of longitudinal care and the need to process information acquired across multiple individual encounters. This places even more importance on information loss during transitions of care. Further, a number of barriers exist to implementation of EHR based simulation activities at most medical centers, an issue magnified in community practices. Therefore the goal of this proposal is to create and validate a turn-key library of EHR based simulations to improve diagnostic safety in ambulatory care which is both generalizable and scalable.
In Aim #1, we will perform our problem analysis by using a combination of administrative data from the Pennsylvania Patient Safety Authority and claims data from The Doctors Company to identify diagnoses at risk for diagnostic error in ambulatory care and EHR use errors associated with said errors. We will integrate these data to create a rubric to allow for the design of a comprehensive EHR based simulation library to study and reduce diagnostic error across the 5 major ambulatory specialties.
In Aim #2, we will develop these simulations for 5 ambulatory specialties. We will in-turn validate the ability of the simulation activities to serve as a training tool to fundamentally change EHR use patterns and reduce diagnostic error. Finally, this library, including all simulation materials, scripts and EHR charts will be coalesced into an online repository in Aim #3. We will further create a series of FHIR based applications which will facilitate ?loading? of the simulated EHR charts into the major EHR systems. Thus, by the end of the funding period, we will have created a library of validated EHR base simulation exercises to reduce diagnostic error in ambulatory care and developed novel technology to facilitate widespread implementation.

Public Health Relevance

Diagnostic error is the most common type of preventable medical error in Ambulatory care and central to its genesis is failure to either effectively access and/or synthesize complex medical information; Electronic Health Records (EHRs) are the primary source of this medical information with numerous studies documenting significant and serious patient safety events with their use. This proposal will develop and validate a library of EHR based simulation exercises designed to reduce the likelihood of diagnostic error across 5 major ambulatory care specialties. We will then create, using Fast Healthcare Interoperability Resources (FHIR) a novel simulation tool which will allow for importation of these simulated charts into the major EHR vendors in the U.S., allowing for these cases to be reliably implemented by the majority of health care practices across the country.

National Institute of Health (NIH)
Agency for Healthcare Research and Quality (AHRQ)
Research Demonstration and Dissemination Projects (R18)
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Healthcare Patient Safety and Quality Improvement Research (HSQR)
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Chew, Emily
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Oregon Health and Science University
United States
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