My team recently had a brownbag on the types of healthcare data available and I took the opportunity to share a bit about electronic health records. Other types of data shared included the MIMIC dataset and imaging data (e.g., X-rays, CTs, MRIs). I received feedback that it was a useful “EHR 101” and thought to share it here too.
Healthcare has a problem
In most places around the world, primary care and hospitals maintain their own, distinct systems for electronic medical record (EMR) data. As a result, patient and medical data across different providers are incompatible with each other, leading to a lack of interoperability.
Providers want to control all digital records of their patients, ensuring patient retention. This leads to data being siloed at each institution. Patients’ prescriptions, lab tests, diagnosis, etc. are not visible across institutions, contributing to significant wastage.
The other problem is that of poor usability. Often, these systems don’t account for human computer interaction principles. Thus, clinicians often spend more time talking to their laptop than to the patient, contributing to clinician burnout. Furthermore, while the system works and data is dumped in, it is often in such a mess that it is impossible to use.
Enter the electronic health record (EHR).