PatientGen - synthetic, realistic patient data for use in interoperability testing

Michigan's PatientGen is a FHIR-compatible test data generator that produces “fake people” who have realistic patient histories with clinically relevant patient encounters. In today’s healthcare environment there is a critical shortage of good test data. This shortage is so severe that organizations create their own test data or worse, test with live data – someone’s protected health information – creating security and privacy risks. Testing with real health data is, of course, very dangerous. Therefore, there is a significant need for realistic patient data that does not pose any risks of disclosure and can be safely used for system testing, interoperability testing, and other purposes. PatientGen has created thousands of SimPatients that are highly configurable, including such detailed data points as name, address, gender, race, religion, PCP, practice, specialist, etc. PatientGen also breaks down different risk factors from diet, exercise, alcohol, smoking, drug use and promiscuity.