You need a reliable source that consistently provides the appropriate data at the appropriate times, to the appropriate people, and at the appropriate locations if you want to get the most out of your Healthcare Information Exchange (HIE) platform and clinical systems. The power plants that drive the interchange of health information are interface engines.
We recently discussed a number of frequently asked issues about the use of interface engines with our team of interoperability experts.
We provide the following synopsis of our discussion below as a tool for everyone participating in the transmission of health information. Enjoy the discussion summary that follows.
What is the most common misunderstanding regarding interface engines?
Many people we interact with believe that interoperability standards should indicate that fundamental systems (such as electronic medical records, practise management, and hospital information systems) should be able to easily interchange data. That is not the situation in reality. These essential systems cannot be normalised because there are too many variables, mappings, and permissions. That method also doesn’t scale well because you have to deal with a lot of point-to-point interactions. You can immediately see the usefulness of a programme to assist effectively manage numerous connections once you factor in the problems associated with different healthcare systems employing various versions of standards and variations in adherence to best practises. Each interfacing system, including Epic, Meditech, Cerner, NextGen, and eCW (etc.), has its own peculiarities.
Integration engines act as a normalizer for variables and various “standards” for data interchange implementations, versions, or interpretations. And with the correct preparation, these engines can power the flow of data in the most effective way possible.
How are Interface Engines are misused in health information exchange initiatives today?
Although we wouldn’t necessarily call them “misused,” Better to say “under-utilized.” Frequently, enterprises are attempting to address just one interoperability use case. They miss the chance to create a well-architected strategy that performs well at scale and supports a wide variety of use cases in an effort to fix that one issue.
It brings to mind the story of the sports car owner who never planned to shift out of first gear.
Which providers of Interface Engines are now excelling in terms of data exchange?
The good news is that a variety of HL7 interface engines are effectively driving data sharing. These solutions are helping our customers in regional HIEs, enterprise/hospital environments, and health IT vendors succeed in a variety of processes. If you’re curious, the top integration engines are listed below in alphabetical order.
- Cloverleaf,
- Corepoint,
- Iguana,
- Mirth Connect,
- Rhapsody (now Lyniate)
Starting with the appropriate underlying technology and architecture (operating system, database, hardware resources, redundancy), validating data quality and optimising workflows, interface testing plans, and post-go-live monitoring and support planning are the common denominators in the success across all of these interface engines.
What is the most typical error made while putting an open-source interface engine into practise?
The most frequent error is failing to consider the long term. Instead of considering the supportability, performance, and scalability of the integration engine and/or interface over the long term, it is far too simple to address the immediate demand (I have a deadline to get this interface up!). If built properly, even “free” open-source integration engine technologies like Mirth® can perform quite well.
Conclusion
KPi-Tech takes pride in developing HL7-compliant HIE software solutions that enable full interoperability within all medical data management systems. Our HIE software integration services achieved milestone to support the storage and transmission of medical data interfaced with the following medical data management systems: Laboratory Information Systems (LIS), Health Information Systems (HIS), Electronic Health Record (EHR), Electronic Medical Record (EMR), Practice Management Systems (PMS), Patient Administration Systems (PAS), Personal Health Records (PHR).
