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Ensuring EHR data integrity and accuracy for HEDIS quality measures

How HEDIS measures are negatively impacted by raw EHR data

The rise in electronic health record (EHR) data has made utilizing patient medical records an increasingly complex task, which impacts downstream calculations such as HEDIS quality measure performance. Teams looking to extract insights from medical records must sift through vast amounts of information, often encountering:

  • Disorganized records from numerous sources, with duplicate information scattered across hundreds of pages.
  • Uncoded data buried within free-text fields, making it difficult to extract and analyze crucial information, especially when the records span hundreds of pages.
  • Inconsistent coding and formats, which don’t always translate into the codes HEDIS teams use. This can cause ingestion failures, slowing down workflows and limiting discovery of gap-closing data.
  • Manual Processes, which introduce risks of inconsistency and human error. Without robust validation and cleansing processes, and links to the original raw source data, information hidden in EHR data may get left behind, resulting in misguided HEDIS measures.

Despite the emergence of tools to manage clinical datasets, few automated solutions exist to address these issues and the inability to fully utilize EHR datasets can put HEDIS quality measure performance metrics at risk.

3 Ways to quickly improve your HEDIS quality measures

Ensuring EHR data integrity and accuracy are paramount to improving HEDIS quality measure performance. This can be done quickly, without changing existing processes, using the Orchestrate APIs:

  1. Integrate EHR Data & Enrich for HEDIS
    Seamless integration of EHR data requires translating it to more usable formats and the code systems used by HEDIS. The right technology can ensure that all EHR data is captured efficiently, summarized into categories so it’s easy to find, and converted into the file formats and code systems needed by HEDIS teams.
  2. Implement Data Validation & Cleansing Procedures
    Ensuring EHR data is accurate and complete is foundational to improving HEDIS performance metrics. Maintaining links to the original raw source data is also necessary in order to pass audits.
  3. Incorporate Automation
    Automating EHR data integration and enrichment improves efficiency and reduces the potential for human error. This allows HEDIS teams to focus on analyzing data more efficiently to close care gaps rather than data management.

How Orchestrate Enriches EHR Data for Use by HEDIS Teams

The Orchestrate APIs enrich raw clinical EHR datasets with code reference systems and HEDIS value set names:

HIE icon
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Type Raw Clinical Data Codes Added by the Convert API HEDIS Value Set Name
TypeImmunization Raw Clinical DataHEPATITIS B 0-19 YRS./ENGERIX B08 (Free Text) Codes Added by the Convert API49610 (RXNORM) 08 (CVX) HEDIS Value Set NameHepatitis B Immunization
TypeDiagnosis Raw Clinical DataFinal: Type 1 diabetes mellitus without complications (Free Text) Codes Added by the Convert APIE10.9 (ICD-10-CM) HEDIS Value Set NameDiabetes Mellitus Without Complications
TypeProcedure Raw Clinical DataCHLAMYDIA TRACHOMATIS IGM ABS 125306 (EPIC code) Codes Added by the Convert API134256004 (SNOMED) HEDIS Value Set NameChlamydia Tests
TypeProcedure Raw Clinical DataGI-COLONOSCOPY SCREENING (LVL4) (Free text) Codes Added by the Convert API73761001 (SNOMED) HEDIS Value Set NameColonoscopy
TypeCrosswalk Raw Clinical Data19515-808-52 (NDC) Codes Added by the Convert API150 (CVX) HEDIS Value Set NameInfluenza Immunization
TypeCrosswalk Raw Clinical Data2642200 (RxNorm) Codes Added by the Convert API150 (CVX) HEDIS Value Set NameInfluenza Immunization
TypeCrosswalk Raw Clinical DataCHLAMYDIA TRACHOMATIS IGM ABS 6920-3 (LOINC) Codes Added by the Convert API134256004 (SNOMED) HEDIS Value Set NameChlamydia Tests

Learn more about how APIs quickly unlock value for HEDIS teams.

The HEDIS team invokes the Convert API to organize and standardize and enrich data elements to feed higher quality data to their HEDIS Engine.

Developers at a computerBy implementing these improvements, HEDIS teams can perform more efficient and accurate medical record reviews without losing data to ingestion failures, uncoded free text, or issues with code translation and file format inconsistencies. The Orchestrate APIs make it possible to implement immediately without creating new infrastructure. Payers and health plans that adopt the Orchestrate APIs for EHR data integration and cleaning can ensure data integrity and improve performance without disrupting operations, freeing up resources for other enhancements.

Read about how risk adjustment teams are adopting API technology to improve risk adjustment profiling measures.

Getting started

Contact us to learn how the Orchestrate APIs are being adopted by HEDIS teams to improve clinical data integrity.