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Informational Only

This challenge is no longer accepting new submissions.

Patient Matching Algorithm Challenge

Integrating patient information for better medical decision making

Department of Health and Human Services

Total Cash Prizes Offered: $75,000
Type of Challenge: Software and apps
Submission Start: 05/02/2017 12:00 AM ET
Submission End: 09/12/2017 02:00 PM ET

This challenge is externally hosted.

You can view the challenge details here:


HHS Names Patient Matching Algorithm Challenge Winners

Thousands of submissions received from more than 140 teams
The U.S. Department of Health and Human Services’ Office of the National Coordinator for Health Information Technology (ONC) today announced the winners of the Patient Matching Algorithm Challenge. ONC selected the winning submissions from over 140 competing teams and almost 7,000 submissions using an ONC-provided dataset.  “Patient matching” in health IT describes the techniques used to identify and match the data about patients held by one healthcare provider with the data about the same patients held either within the same system or by another system (or many other systems). The inability to successfully match patients to any and all of their data records can impede interoperability, resulting in patient safety risks and decreased provider efficiency. “Many experts across the healthcare system have long identified the ability to match patients efficiently, accurately, and to scale as a critical interoperability need for the nation’s growing health IT infrastructure.  This challenge was an important step towards better understanding the current landscape,” said Don Rucker, M.D., national coordinator for health information technology. Winners include: Best “F-score” (a measure of accuracy that factors in both precision and recall):
  • First Place ($25,000): Vynca
  • Second Place ($20,000): PICSURE
  • Third Place ($15,000): Information Softworks
Best First Run ($5,000): Information Softworks Best Recall ($5,000): PICSURE Best Precision ($5,000): Ocuvera Each winner employed widely different methods.   PICSURE used an algorithm based on the Fellegi-Sunter (1969) method for probabilistic record matching and performed a significant amount of manual review. Vynca used a stacked model that combined the predictions of eight different models. They reported that they manually reviewed less than .001 percent of the records. Although Information Softworks also used a Fellegi-Sunter-based enterprise master patient index (EMPI) system with some additional tuning, they also reported extremely limited manual review. The dataset and scoring platform used in the challenge will remain available for students, researchers, or anyone else interested in additional analysis and algorithm development, and can be accessed via the Patient Matching Algorithm Challenge exit disclaimer icon website.


First Place Winner
Cash Prize Amount: $25000

Second Place Winner
Cash Prize Amount: $20000

Third Place Winner
Cash Prize Amount: $15000

Best in category: Precision
Cash Prize Amount: $5000

Best in Category: Best recall
Cash Prize Amount: $5000

Best in Category: First F-Score run
Cash Prize Amount: $5000