Characterizing, Comparing, and Contrasting Patients’ and Providers’ Approaches to Endometriosis Management

Student Classification


Faculty Mentor

Dr. Noemie Elhadad


Computer Science

Document Type


Publication Date

Fall 2019


Patient-generated data (PGD) are emerging as the cornerstone of chronic disease management. Selftracking tools have shown promise in supporting patients with their self-management needs, as many occur outside of doctor visits and throughout patients’ daily lives. There is limited work, however, on the use of self-monitoring and self-tracking data as a means for building trust, ensuring shared decision making between patients and providers, and ultimately improving patient-centered care. Furthermore, there is limited knowledge for complex chronic diseases without clear treatment guidelines. Endometriosis is an enigmatic condition with an often-debilitating impact on patients: there are no bio-markers for providers to monitor patients’ status, treatment response varies across individuals and patients are dissatisfied with the lack of success in their care. The rise of FHIR technologies provides new opportunities to inform the design of self-tracking artifacts for the goal of shared-decision making. We explore endometriosis specialists’ and patients’ perceived opportunities and challenges for using these tools. In particular, we (1) identify convergent and divergent needs across medical specialties for successful encounters; (2) assess from the providers’ and patients’ perspective, the ways in which they negotiate and align goals and expectations with each other, especially when both patients and providers have relevant knowledge; and (3) build engaging and actionable support tools that characterize, compare, and contrast the assessment, self-management, and decisionmaking practices of patients and providers at the point of care. Our work confirms that self-tracked data can act as powerful evidence to re-align knowledge and expectations between patients and providers.

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