Using AI/Machine Learning for Patient Matching to Support Patient Safety and Improve Care

Access to accurate, complete, and timely data is one of the most valuable assets in any healthcare organization. Quality data improves care coordination, and clinical outcomes, and saves lives but can only be achieved with accurate patient identification or matching across multiple sources. Interoperable electronic health records (EHRs) allow the electronic sharing of patient information between these different sources, but sharing the data successfully requires the capacity to connect each patient with the correct record. Despite best practices in patient access and medical record management, patient matching issues including duplicate records and record overlays continue to be a major problem for health care.

During this session recording, you will learn how AI/Machine Learning Prediction is being used to further improve the patient match rate and ensure medical record data is accurately matched to the right patient identity.


  • Craig Jones, MD, Chief Medical Officer, Idaho Health Data Exchange
  • Muthu Kuttalingam, Senior Vice President of Product Development and Technology, 4medica