Patient matching involves the techniques healthcare providers use to identify and match patient data from one provider’s system with patient data from the same or a separate system. When providers are unable to accurately match patients to their data, patient safety and provider efficiency are compromised.
ONC proposed the Patient Matching Algorithm Challenge in April, which asked teams to develop innovative algorithms, benchmark current performance and help industry collaborate for patient matching success, which ultimately influences interoperability.
“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 ONC head Don Rucker, MD.
Here are the three winners that developed the best measure of accuracy factoring in both precision and recall.
1. Vynca
2. Picsure
3. Information Softworks
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