MIMS Final Project 2009

Hyoumanity: Social Search and Incentive Alignment in Health Care


The National Institutes of Health estimate that some seven thousand rare diseases cumulatively affect as many as thirty million Americans.  A study by the National Organization for Rare Diseases found that of these patients, 36% took more than one year following their first doctor visit to receive a diagnosis, while 17% took more than six years to get diagnosed. Given that diagnosis is the basis for all subsequent healthcare decisions, the absence of a timely and accurate diagnosis is the limiting factor that prevents patients from pursuing effective treatment.

Given the highly fragmented nature of medical knowledge, resolving many of these cases of difficult diagnosis essentially becomes a matching problem in which a patient with a specific condition must find a clinician with the right expertise to recognize and diagnose it.  Under the current structure of the healthcare delivery system, patients lack the required information and resources to complete this search efficiently and effectively, while physicians lack the tools and incentives to independently locate patients to whom their expertise might be most valuable.

We posit that using technology to facilitate the appropriate patient-to-provider match holds the potential to solve many of these difficult cases.  Hyoumanity is a web-based platform intended as a proof-of-concept for this hypothesis, providing the infrastructure necessary to capture, structure, and index medical records and the qualitative narrative accompanying illness.

Last updated:

October 7, 2016