Application of Data Quality Summary Reports (DQ-SR) at One MII-MeDIC - A Technical Case Report.
TL;DR
A FHIR native solution is proposed that enables reviewing the harmonization of such a fragmented infrastructure and further developed the FHIRwood dashboard that enables MeDICs to also review locally relevant DQ aspects.
Abstract
In the German Medical Informatics Initiative (MII), Medical Data Integration Centers (MeDICs) make routine care data from German university hospitals available to researchers. The MII common data model is the Core Data Set (CDS) built on HL7 FHIR. Extensive effort is put into providing FHIR profiles with corresponding Implementation Guides (IGs). While the technical specification of IGs is centrally governed, implementation is distributed among all MeDICs. Each MeDICs is to build compatible processes within the diverse landscape of Electronic Health Record (EHR) systems in Germany. Therefore, the characteristics of FHIR resources between MeDICs might differ. Different constraints in underlying processes explain this, yet the central CDS specification needs transparent ways to capture the differences. MeDICs spend considerable effort on localized Data Quality (DQ) checks, like source data validation or plausibility analyses. Local checks do not enable the central CDS specification working group to assess the degree of harmonization of CDS implementation reached between different MeDICs. We propose a FHIR native solution that enables reviewing the harmonization of such a fragmented infrastructure. HL7 Clinical Quality Language (CQL) is utilized to generate DQ Summary Reports (DQ-SRs). We further developed the FHIRwood dashboard that enables MeDICs to also review locally relevant DQ aspects. The lessons learned during the DQ-SR and FHIRwood application at one MeDIC give insights for future IG development.