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Payer Extract
Connectathon Update
Using the FHIR Clinical Reasoning Module to Enable
Calculation of Payer Quality Measures
What is Payer Extract
 An approach to enable retrieving relevant patient
information directly from provider systems
 Leverage emerging standards to streamline the payer
quality measure calculation process
 Decrease development time for EHR Vendors, Payers,
and Quality Reporting Vendors
Payer Extract Approach
EHR
Data
Payer
Payer Extract
Processing
EHR FHIR
Service
Payer
Extract
FHIR
Service
Terminology
Server
Terminology Integration
 This connectathon we focused on terminology
integration
 When the source server doesn’t have the value sets, use
the terminology server to resolve them
 Engine “in-lines” the valueset codes into the URL
 Obvious cons here, but for reasonably small valuesets, it’s
functional
 Found and fixed several issues, we now have a
functional implementation that uses Apelon’s FHIR STU3
terminology server
Participant Feedback
 We were able to successfully expose HEDIS valuesets as
FHIR ValueSet resources, and along the way found and
fixed several implementation issues
 We were able to successfully calculate CQL-Based
measure cohorts using a FHIR server as the data source
 We feel that we can move forward with the approach
using FHIR rather than the myriad other formats we
currently have to consume

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Payer extract connectathonupdate

  • 1. Payer Extract Connectathon Update Using the FHIR Clinical Reasoning Module to Enable Calculation of Payer Quality Measures
  • 2. What is Payer Extract  An approach to enable retrieving relevant patient information directly from provider systems  Leverage emerging standards to streamline the payer quality measure calculation process  Decrease development time for EHR Vendors, Payers, and Quality Reporting Vendors
  • 3. Payer Extract Approach EHR Data Payer Payer Extract Processing EHR FHIR Service Payer Extract FHIR Service Terminology Server
  • 4. Terminology Integration  This connectathon we focused on terminology integration  When the source server doesn’t have the value sets, use the terminology server to resolve them  Engine “in-lines” the valueset codes into the URL  Obvious cons here, but for reasonably small valuesets, it’s functional  Found and fixed several issues, we now have a functional implementation that uses Apelon’s FHIR STU3 terminology server
  • 5. Participant Feedback  We were able to successfully expose HEDIS valuesets as FHIR ValueSet resources, and along the way found and fixed several implementation issues  We were able to successfully calculate CQL-Based measure cohorts using a FHIR server as the data source  We feel that we can move forward with the approach using FHIR rather than the myriad other formats we currently have to consume