The Office of the National Coordinator for Health Information Technology (ONC) has recently released an interoperability rule that advances the use of APIs in healthcare systems. The intent of this rule is to empower patients and provide them with enhanced access to their healthcare information. Importantly, the interoperability rule can also help reduce clinicians’ burden and improve quality of care.
Manual entry of patient and lab data leads to significant error rate and data integrity issues as well as inefficiencies for transplant programs and transplant center staff affecting delivery timelines. For example, delays in receiving potential donor and recipient data may result in adding recipients to the waitlist without sufficient information. Insufficient or limited data cause delays which require manual investigation and clarification. This results in missed opportunities for full-picture data analysis into post-transplant outcomes, recovery and follow-up which are often deprioritized because of data entry inefficiencies.
There are also significant integration implementation challenges such as varying data across multiple sources. Integration requires significant investment of hospital integration resources to disentangle transplant data from end-to-end, including EMR and lab systems. Ingestion of a variety of feeds is time consuming to translate and maintain by the destination system. It also requires continual transformation when sources change.
A common way to enable integration between local, regional, and national systems is through API Connectors and workflow logic. And once you have many APIs, you need API management.
Enter Afflo. Afflo has prebuilt connectors to transplant-specific components as well as general HIS/LIS systems. Some transplant programs use transplant-specific systems but many don’t.
Afflo provides transplant data capture and management functionality, and it can integrate with in-place systems to enable true interoperability, empowering patients and healthcare providers alike with high-quality and consistent data to drive full-picture data analysis.