A medication app launched in Epic
Innovating inside Hyperspace with SMART on FHIR
Research IT launches a new electronic health record app in Epic Hyperspace in collaboration with Stanford Emerging Apps Lab to help Stanford doctors diagnose life threatening drug reactions
Oct 30, 2020: Heparin‐induced thrombocytopenia (HIT) and Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS) are two immune mediated adverse drug reactions that can be devastating if not properly identified. Diagnosis of both conditions can be difficult and require the assessment of how clinical data, such as laboratory results, are related in time to when patients receive certain medications. The electronic health record (EHR) system at Stanford allows clinicians to review patient medications, but then requires navigation to a separate screen to review other relevant clinical data. In order to evaluate for the presence of drug reactions, clinicians have to manually compare whether certain medications coincide in time with abnormal laboratory results while often also needing to use separate online reference tools to verify diagnostic criteria. This can be a time consuming process that is subject to high levels of variation and error, leading to missed diagnoses that can affect patient care.
Stanford Emerging Apps Lab (SEAL), is a joint effort between Research IT and the Digital Healthcare Integration Team at Stanford Health Care to rapidly innovate, build, and implement lightweight digital apps that integrate into the EHR to improve clinical workflows. Susan Weber PhD, SEAL’s technical lead, and Dr. Ron Li, SEAL’s clinical informatics lead, collaborated with Dr. Bernice Kwong and Dr. Beth Martin to design an app that automatically organizes and visualizes medication and laboratory data in a more clinically meaningful way that is not possible within the current EHR system.
The app can be launched from within a patient chart in the EHR and automatically pulls the medications and laboratory results in real time for that specific patient, which are then displayed together in a timeline. Clinicians can also customize which medications and laboratory results they would want to see on the timeline using a filtering mechanism. The initial release of the app has pre-programmed drug and medication filter sets for DRESS and HIT specified by Drs. Kwong and Martin, and can be easily extended to include filter sets suitable for other syndromes.
Have a clinical process improvement suggestion? Contact the SEAL team and the team will engage with you to:
- Co-design and develop
- Implement and disseminate for Stanford community
- Publish and disseminate beyond Stanford