By Brian Carter, senior vice president of product, Validic.
Clinicians, CIOs and virtually every person in a decision-making position in a health system is courted multiple times a week by third-party solution developers with amazing products to help them with some of their most pressing problems. The features look great, but at some point they have to ask: does it integrate with my existing clinical workflows in a way that makes it easy to use, hard to forget about, and actually save my team some time?
This question is extremely important; according to one study about clinical decision support (CDS), zero CDS interventions succeeded when they weren’t delivered automatically in the clinician workflow. By contrast, the same study showed that 75 percent of those interventions succeeded when they were automatically presented in clinical workflow. Workflow integration comes in a variety of flavors, with the value of that integration typically (and somewhat unfortunately) proportional to the amount of investment made in preparing for that integration.
Visual integration is the lightest-weight kind of integration. iFrames, SMART apps and “widgets” are all common technologies that come to mind when describing visual integration. Essentially, you are taking one application and layering it as a self-contained component inside another application. This ideally includes a single sign-on function so the person signed into the main application doesn’t have to sign into another widget on their screen.
A common example on the web is Disqus. If you scroll to the comments section of a web page to share your opinions, you’ll find a nicely-embedded component with other people’s comments. But, if you want to contribute a comment yourself, you have to sign in. This comment feature is actually a totally different application provided by another company called Disqus, which was visually integrated with a few lines of code.
Data integration is often what’s being talked about when interoperability comes up. Data integration simply means enabling the data from one application to flow meaningfully into another application. The concept is simple, but the application of this strategy can be highly complex. It involves getting two systems to not only get data from one place to another, but also to be formatted and codified in a way that the receiving system can actually understand it.
Technologies common in health care surrounding data integration include the emerging FHIR specification from HL7, legacy APIs provided by EHR vendors, health information exchanges that serve as intermediaries between different systems, as well as enterprise data warehouses and big data platforms. Data integration is a critical strategy whenever users of one system need information that users of another system have generated.