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Healthcare

Heals.Asia

One of the largest TPAs ​​in Hong Kong challenged the Edenlab team to switch to a modern FHIR architecture. The project was built on top of the Edenlab Kodjin FHIR server and terminology service.

Task

The project required to automate the appointment process for doctors connected to the Heals.Asia platform clinics and the processing of insurance claims.

Challenges

Heals.Asia needed to decrease their level of unproductive manual work in appointments and claims processing.

The process

Administrative data, appointments, and CD

Challenges

  • The need to expose the provider directory FHIR API (search facilities, search practitioners by name or specialty) and the appointments FHIR API (book an appointment, check in, etc.) for a third-party mobile application.
  • The need to collect the clinical data from two separate EHR systems, connected to the TPA, in the centralized clinical data repository (CDA).
  • The problem of terminology management: different HIS had to be transferred into the same type, and physicians worked with terminologies based on different healthcare standards.

Solutions

  • For the first set of functionalities, we developed a FHIR facade implementing extract-transform-load from the client’s proprietary data in real-time based on the Edenlab Kodjin FHIR server.
  • Our team created custom profiles corresponding to the proprietary data with all the relevant terminologies.
  • We developed the appointments module from scratch with the FHIR-first approach, as well as custom FHIR profiles and a custom business logic layer.
  • We created custom profiles and configured the terminology service with the custom terminologies. A pseudonymization technique was used to protect the patients’ clinical data.
  • Our Terminology Service solves the problem of terminology management by providing unification of all used terminologies. We developed a system where all terminologies are stored on a single cloud health information system (HIS) which is not common in the terminology solutions market.
  • We enabled physicians to easily find and validate any code by its description and do code mapping between different terminologies in real-time without any external support. The mapped codes can be used further in health data exchanges, no matter whether FHIR is used on the other connected systems or not.

Financial data and auto-adjudication engine

Challenges

  • The need to standardize the financial API consumed by various providers connected to the TPA – all the main workflows from the FHIR financial module should be exposed as FHIR operations.
  • The need to automate these workflows from the TPA side, i.e., to introduce the auto-adjudication engine that was able to generate the eligibility responses and claim predetermination responses based on the insurance plan data and the history of claims

Solutions

  • The solution was a hybrid FHIR/non-FHIR application.
    While all the data that was exchanged was stored in the FHIR server, we implemented a complex structure enabling the auto-adjudication logic for the insurance plan.
  • The engine itself was designed as a framework, so new limits and constraints could be added in the future.

Technology stack

  • Kubernetes logo
  • Elastic logo
  • Elixir logo
  • TypeScript logo
  • React logo
  • MongoDB logo

Results

  • Provider directory FHIR API on top of the existing data and processes
  • Appointments FHIR API for a third-party mobile application
  • Mobile application connection to the FHIR API
  • FHIR-based claim exchange module, powered by the auto-adjudication engine

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