MIE’s Muge Capan and Colleagues Obtain Grant to Improve Diagnostic Equity in Ambulatory Healthcare Settings

Content

Muge Capan

Appropriate healthcare delivery depends on the proper and timely diagnosis of each patient’s health condition, and yet diagnostic errors remain the leading cause of morbidity and mortality in the U.S. What’s more, the incidence of diagnostic errors, especially delays in diagnosis, disproportionally impacts medically underserved patients. Now Assistant Professor Muge Capan of the Mechanical and Industrial Engineering (MIE) Department and her collaborators at Medstar Health will be using a four-year R01 grant of $1.9 million (UMass share is $900,577) from the Agency for Healthcare Research and Quality (AHRQ) to address the troubling inequalities in diagnostic errors between the “haves” and the “have nots.”

As Capan and her colleagues explain, “Diagnostic disparities occur when preventable diagnostic errors are experienced disproportionately among certain demographic subgroups of patients. Research has shown disparities in diagnostic errors by race and ethnicity, sex, gender, geographic location, and socioeconomic status, in part due to implicit bias, discrimination, and stigma.”

Capan is one of the three principal investigators for the grant, titled “Improving Diagnostic Equity in Ambulatory Care Setting (I.D.E.A.S.): Research to Practice.” The project is an interdisciplinary collaboration between MedStar Health and UMass Amherst, and the principal investigators at Medstar Health are Dr. Kristen Miller and Dr. William Gallagher.

As the AHRQ proposal explains, “Considering the volume and variety of primary care patients, combined with the practical challenges of scarce and costly referral and testing resources, the incidence of diagnostic errors can disproportionally affect medically underserved and vulnerable patient populations.”

However, the relationship between diagnostic equity (i.e., diagnostic disparities related to diagnostic error due to systemic issues in policies and practices) and diagnostic uncertainty (i.e., subjective perception of an inability to provide an accurate explanation of the patient's health problem) is poorly understood. Moreover, the complexity, time dependency, and uncertainty of the diagnostic process makes such knowledge quite challenging.

To answer this continuing challenge, Capan and her colleagues at MedStar Health have developed the I.D.E.A.S. project to evaluate diagnostic errors in the context of diagnostic equity and diagnostic uncertainty by utilizing health systems engineering, decision-modeling, and human-factors methodologies.

As the three researchers state, “The novelty of the proposed study lies in its unique interdisciplinary approach, bringing together clinical diagnostician expertise, data science, operations research, and human-factors engineering to work towards methodological advances in conceptualizing and measuring diagnostic errors.”

The three researchers add that their expected research outcomes will lay the foundation for designing a comprehensive framework to inspire interventions which reduce diagnostic inequity and improve the management of diagnostic uncertainty.

The AHRQ project fits into the ongoing research that Capan undertakes in her lab in the MIE department. As Capan says, she uses “data science, statistical analysis, and decision modeling in healthcare to develop smart and connected clinical-decision support systems.”

The AHRQ grant will support four UMass Amherst students (two Ph.D. and two undergraduate students) in Capan’s research lab, providing them with a unique interdisciplinary research experience. (September 2023)