Access to accurate, complete, and timely data is one of the most valuable assets in any healthcare organization. Quality data improves care coordination, 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 difference sources, but sharing the data successfully requires the capacity to connect each patient with the correct record.
When: Thursday, June 2nd | 2:00 PM ET
Overview:
Access to accurate, complete, and timely data is one of the most valuable assets in any healthcare organization. Quality data improves care coordination, 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 difference 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 to include duplicate records and record overlays continue to be a major problem for health care.
During this session, 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.
Speakers:
- Craig Jones, Partner, Capitol Health Associates
- Muthu Kuttalingam, Senior Vice President of Product Development and Technology, 4medica
