Use Case: Shared Health Records

In contexts of multiple disparate, heterogeneous and isolated clinical systems, data integration is a must to provide better care quality and to reduce administrative and maintenance costs of dealing with multiple systems to get back usable information.

EHRServer is an ideal tool for centralizing the information that needs to be shared between clinicians, specialties, offices, and even with the patient through a PHR or a Patient Portal.

Steps to follow

1. Analyze which information should be shared between your systems, start small, focus on the basics: general encounters, vital signs, allergies and other diagnosis, family history, immunizations, etc.
2. Model that information using openEHR. Check the openEHR intro guide. This will serve as a canonical model that will standardize the information from your different systems.
3. Transform your data sources into canonical model instances. We have tools to help you on that process. Also a middleware like Mirth Connect (open source) can help you on the transformation task. Of course, we can help with this process.
4. Commit send your instances to the EHRServer to be persisted as part of each patient's EHR. Repeat until your current data is cimmitted. This is like a batch process to load historical data. Now the data is ready for quering!
5. Query the data from any external system, even from systems that are not part of the data sources! Create some basic queries over your data, like get all the vital signs from an EHR. That can be done easily using the Web Console of the EHRServer, yes from a GUI! The result of each query will be consistent, openEHR compliant, and you can choose between JSON and XML formats to get your data for processing (yes you can do things like evaluating rules for clinical decision support), analysis, or just nice visualizations. If you don't want to query, you can get full clinical documents by their id in XML or JSON.
6. Integrate this solution in your environment to synchronize data regularly, so you get current data when your systems and apps execute the queries. The first commit round is the heavy loading, now it's time to receive data online instead of a batch process.

Open a world of possibilities

Following those steps you didn't just loaded data into another database, you standardized and integrated data from heterogeneous, and maybe inconsistent / incompatible clinical systems. This opens a whole wolrd of new possibilities! Sharing clinical data between your systems is the first step, but you can add more apps that use queries to access existing data to create more services to clinicians and patients, explore data visualizations, integrate this data into clinical decision support tools, and more. Your imagination is the limit.

Also, following the same setps you can scale your integration in terms of the information that is being shared, sharing more information and creating new queries over data. With that you can offer new services and continously improve your app ecosystem. Keep this mantra in mind: Better apps for clinicians, better access to meaningful clinical information, better care for patients.