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Understanding eMeasures – And Their Impact on the EHR

Understanding eMeasures – And Their Impact on the EHR. June 3, 2014 Linda Hyde, RHIA. Objectives. Using eMeasures for quality measurement and reporting Impact of eMeasures on EHRs Constructing and using eMeasures Using classifications and terminologies in eMeasures

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Understanding eMeasures – And Their Impact on the EHR

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  1. Understanding eMeasures – And Their Impact on the EHR June 3, 2014 Linda Hyde, RHIA

  2. Objectives • Using eMeasures for quality measurement and reporting • Impact of eMeasures on EHRs • Constructing and using eMeasures • Using classifications and terminologies in eMeasures • 2014 Reporting Requirements • What’s coming next???

  3. eMeasures &Quality Measurement • Data collection for quality measurement and reporting traditionally based on claims data and manual collection systems • Used for internal analysis as well as public reporting • Expanding into many different care settings • Increasing ties to reimbursement through P4P, ACOs and Value Based Purchasing initiatives

  4. eMeasures &Quality Measurement • Adoption of Meaningful Use program will change the data capture strategy for quality measures • NQF tasked by HHS to perform an initial conversion of 113 existing measure to electronic format • Review conducted to insure that intent of measure consistent from existing paper/claim based measure to electronic version • Set the stage for the creation of the process and tools needed to formalize the creation of eMeasures

  5. eMeasures &Quality Measurement • eMeasures created by two methods • Retooling existing paper/claims measures • New or ‘de novo’ • Challenges/Opportunities for both methods • Maintaining intent of existing measure while conforming to new structure/format of eMeasure • Limited electronic data available to evaluate the measure performance (affects both methods) • Adoption of new classifications/terminologies (including transition to ICD-10) • Ability to utilize full functionality of data capture by EHRs • Leveraging the current capability of the EHRs systems with the data needed for the measure

  6. Impact of eMeasures on EHRs • A major goal for EHR development under Meaningful Use (MU) is to utilize their capability to capture and report healthcare performance data • Using data routinely collected in EHRs requires the ability to identify how data is stored and create a standardized method to access, classify and extract it • Requires understanding of current EHR capabilities and development of the tools needed to support eMeasures

  7. Impact of eMeasures on EHRs • MU requirements for EHR content through the various stages must be balanced against the eMeasures available for those stages • All key stakeholders in EHR and eMeasure development need to understand the interaction needed to report eMeasure data • Use of structured vs unstructured data • Use of various classifications within the EHR or capability of mapping data to the required classification

  8. Constructing eMeasures • eMeasures are defined using the Quality Data Model (QDM) developed under the auspices of the NQF • Enables expression of data requirement in context of EHR use • Involves mapping data elements to corresponding QDM components • Process defined in the CMS Measures Management Blueprint document • eMeasures are constructed using the Health Quality Measures Format (HQMF) an HL7 standard • Standardizes structure, metadata, definition and logic • Represented in HTML format for easy viewing and XML format for importing into an EHR

  9. Constructing eMeasures • eMeasures are created using the web-based Measure Authoring Tool (MAT) developed by the NQF and now managed by HHS • Based on quality data model (QDM) structure • Data criteria (data element) are defined in ‘value sets’ using healthcare standard vocabularies • Measure exported from MAT in HQMF format • The following examples show how a representative EP and EH eMeasure are constructed

  10. Diabetes: Hemoglobin A1C Poor Control

  11. Diabetes: Hemoglobin A1C Poor Control

  12. Diabetes: Hemoglobin A1C Poor Control

  13. Diabetes: Hemoglobin A1C Poor Control

  14. Statin Prescribed at Discharge

  15. Statin Prescribed at Discharge

  16. Statin Prescribed at Discharge

  17. Statin Prescribed at Discharge

  18. Using Classifications/Terminologies • Vocabularies are used when defining value sets for data elements in the QDM • Each QDM category has recommended vocabulary standards • CMS has listed the recommended vocabularies in their CMS Measures Management Blueprint • For each data concept there is a clinical vocabulary standard and transitional standards

  19. Vocabulary Standards Examples

  20. Value Sets • For each concept that has transition vocabularies, each appropriate vocabulary should be used to define a value set for the eMeasure. • CPT/HCPCS would be used for EP measures • ICD-9-CM Procedures would be used for EH measures • Value sets with multiple vocabularies will be identified as a ‘Grouping Value Set’

  21. Value Sets • Value sets are created and loaded into the Measure Authoring Tool • The NLM has created a repository of all MU value sets in a web-based tool call the Value Set Authority Center (VSAC). • Value sets can be accessed and download individually, for a given measure, or for all measures.

  22. Value Set Example-Diabetes

  23. Value Set Example-HbA1C Test

  24. 2014 Reporting Requirements • All providers whether in Stage 1 or Stage 2 or MU required to report on the 2014 CQMs finalized in the Stage 2 rule • EP 9 measures • EH 16 measures • May report electronically or via attestation • CQMs selected must cover 3 of the 6 National Quality Strategy domains

  25. What’s Coming Next • Expect additional eMeasures to be developed both for MU and CMS quality reporting programs • FY 2014 IPPS Proposed Rule identifies CMS plans to transition reporting programs starting with the Inpatient Quality Reporting Program (IQR) to use of eMeasures • Ultimate goal is to require all IQR measures to be submitted as eMeasures in the coming years • HL7, CMS, NQF all working on expanding and improving the tools needed to define, calculate and report on eMeasures • http://www.lantanagroup.com/especnavigator/

  26. Resources • CMS • Clinical Quality Measures (eMeasures) • https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/ClinicalQualityMeasures.html • eHealth • http://cms.gov/eHealth/index.html • Measure Management System Blueprint • https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/MeasuresManagementSystemBlueprint.html

  27. Resources • AHRQ Meaningful Use Download • http://ushik.ahrq.gov/downloads/MeaningfulUse • National Library of Medicine (NLM) • Value Set Authority Center • https://vsac.nlm.nih.gov/ • Unified Medical Language System (Rx Norm, SNOMED CT information) • http://www.nlm.nih.gov/research/umls/ • HL7 http://www.hl7.org/ • National Quality Forum http://www.qualityforum.org/Home.aspx

  28. Questions

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