Introduction
Scenario: Dr. Smith’s patient, Michael, has been diagnosed with colon cancer and is seeking to participate in a clinical trial that offers hope of a new treatment for his medical condition. Dr. Smith considers the trials she is familiar with at her hospital and manually reviews Michael’s medical history against the trial criteria – determining that he is not a match. This process is laborious and sometimes error prone – especially when required data is not fully accessible. In Michael’s case, Dr. Smith could not consider his full medical history as he’d recently moved to the area. Together, these challenges mean that neither Michael nor Dr. Smith are aware that there’s a potential trial at another hospital across town. As a patient, Michael is able to conduct a search on his own, however this entails a highly manual process, clinical trial data from various tools is not always up-to-date and can quickly become overwhelming. Given the complexities of this process, Michael is eventually ‘matched’, but it is too late – the desired trial has closed enrollment.Questions to Address:
- How can we build interoperability into this process with HL7 Fast Healthcare Interoperability Resources (FHIR®) – automating trial matching by fitting patient data and clinical trial criteria together like puzzle pieces?
- Two separate-but-related teams within one of the world’s leading health data standards organizations are independently addressing aspects of this complicated puzzle. Through more standardized patient medical records and machine-readable, digital clinical trial protocols, we can make progress toward a future state where trial matching is more accurate and seamless. You can be part of the journey!