Healthcare organizations are increasingly turning to APIs to enhance interoperability between EHRs, internal apps, and other data exchange tools. APIs are interfaces that allow disconnected programs or systems to communicate with each other, acting as bridges that allow the flow of information. APIs are being looked at as ways to reduce development time, save storage space on devices and systems, and overcome any differences in the standards or formats in data at either end of the bridge.
ONC proposed three technical outcomes for healthcare APIs in its 2015 Edition of Certified EHR Technology.
- Data security: The APIs needs to establish a trusted connection with the application requesting patient data. This includes a means for requesting the application to register with the data sources, become authorized to request data, and log all the interactions taking place between the application and the data source.
- Patient selection: The APIs should have enough measures for the application to query for an ID or any other identifier in a patient’s record in order to execute the subsequent data requests.
- Data requests, response scope, and return format: The APIs need to include a means to support two major kinds of data requests and responses: “by data category,” and “all.” In both cases, the scope required for certification may be limited to the specified data sets in the Common Clinical Data Set, but additional data is allowed.
There are several advantages of using APIs, some of which are listed below:
- Real-time access to crucial patient information
- Autonomous processing and customized data governance
- Minimized delay in receiving or extracting information
- Better clinical decision-making and integrated workflows for providers
This is only the tip of the iceberg and through an API-first approach, healthcare organizations can simplify interoperability by enabling seamless data flow backed by a robust infrastructure. However, creating a one-stop solution to access important data and applications is a necessary step in making healthcare data intensive.