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The NCQA Baseline Assessment Tool

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  1. The NCQA Baseline Assessment Tool . . . and How Sharing Information Production Process Metadata Fosters Process Improvement

  2. The BAT and Information Production Process Metadata • What is the Baseline Assessment Tool? • What is this Metadata all about? How it relates to: • Quality Management and Process Improvement • Information Production Processes • HEDIS/QARR • Process Improvement Details Useful for the BAT

  3. What is the BAT?

  4. The NCQA Baseline Assessment Tool • The BAT collects information that helps the NCQA assure that health plan information systems can generate reliable quality measures for HEDIS/QARR • Supports the NCQA's HEDIS Compliance Audit, an audit for compliance with HEDIS specifications for measures.

  5. Sections of the BAT • Data Processing Systems: • Encounters • Members • Providers • Completeness of Data • Integration of Data for Reporting • Controlling Integrity of Reporting • Medical Record Review • Other / General Information

  6. Quality Assurance Reporting Requirements (QARR)

  7. Generating QARR Measures • Extract random samples of member populations relevant to each measure • Calculate rates of those showing compliance with requirements for each measure • Includes visiting primary care sites, physically reviewing medical records, recording compliant instances

  8. What is this Metadata all About? • Metadata Categories • Basic Metadata Purposes • What Quality Management Does • Overview of Relevant Processes • Quality Approach to Information

  9. Metadata Categories • Production Process Factors • People • Process • Tools • Materials • Quality Measures • Timeliness • Completeness • Accuracy • Barriers to Quality (Root Causes) • Improvement Processes • Quality Assessment • Cleanup and Transfer • Process Improvement

  10. Basic Metadata Purposes: • Create common understanding • Foster process improvement • Enable information stewardship

  11. Metadata CreatesCommon Understanding Between: • Information Producers: • Business Process: data acquisition, entry and updating • Technical Process: developers and analysts • Information Stakeholders: • Anybody who uses the information for business

  12. Metadata FostersInformation Process Improvement • Establishes common understanding, from an enterprise standpoint, of all stakeholder requirements for information • Fosters collaboration, empowerment, teamwork, professionalism, pride of workmanship • Makes environment of information stewardship possible

  13. Information Stewardship Willingness to be accountable for a set of business information for the well-being of the larger organization, by operating in service of (rather than under control of) those around us.

  14. What Quality Management Does: • Brings producers and stakeholders together • Makes sure stakeholder requirements are fully represented • Assures completeness and objectivity of measures so they are reliable basis for understanding and managing functionality and performance • Establishes factual basis • Makes process improvement possible • Makes cross-functional teamwork possible • Makes performance management possible • Makes resource management possible

  15. The Definition of Quality Meeting and exceeding stakeholder (customer) expectations and requirements

  16. Process Improvement:PDCA (Shewhart Cycle) • Planan improvement based on factual basis • Doit for awhile • Checkit for improvement • Actto standardize the improvement (Repeat)

  17. Process Improvement:Root Cause Analysis

  18. Overview of Production Processes

  19. Encounters Information Producers

  20. Members Information Producers

  21. Providers Information Producers

  22. Encounters Stakeholders

  23. HEDIS/QARR Quality Assessment and Medical Record Review • Build CRMS • Create population samples • Extract compliant instances based on administrative data, along with member and provider site information, to a special QARR database • Load laptops from this database

  24. Lack of Compliant Instancesby Administrative Data • Compliance with measure conditions requires the following data elements to be present and accurate: • Recipient information • Service and diagnosis codes • Service location information • Provider information • Missing or inaccurate information necessitates the conduct of onsite medical record review

  25. HEDIS/QARR Quality Assessment and Medical Record Review • Review claims histories for all members in samples to identify most likely primary care provider • Sort samples and fax lists to each site, requesting charts for onsite review

  26. HEDIS/QARR Quality Assessment and Medical Record Review • Visit sites and review charts

  27. HEDIS/QARR Quality Assessment and Medical Record Review Track down charts not found at sites: • Verify Member name, CIN, SSN • Review claims history for other providers and spans of care • Check Healthy Beginnings / Mammogram Incentives databases • Check online Immunizations Registry • Check Phone logs • Check NY State Roster • Check • Call Providers • Call Members

  28. HEDIS/QARR Quality Assessment and Medical Record Review • Visit new locations and review again

  29. HEDIS/QARR Quality Assessment and Medical Record Review • Integrate and upload laptop data to CRMS • Use CRMS to generate rates • Send results to NY State Department of Health

  30. HEDIS/QARR Quality Assessment and Medical Record Review • Massive costs due to nonquality data • Nurses to sites throughout network, three times • Hunting down members, what provider they're getting care from, missing or miscoded services and diagnoses • 4300+ members in samples

  31. Foster common understanding between producers and stakeholders by use of shared metadata Accuracy can’t be automated; only people can assess and correct for accuracy Information is an enterprise resource Measure information quality in voice of downstream customers/stakeholders To improve a production process, measure its product Improve information quality at the point of capture Quality Approachto Information

  32. Foster Common Understanding Between Producers and Stakeholders

  33. Accuracy Can’t be Automated • Only people can create, assess, or correct for accurate information • Automatic business rules can only prevent gross errors • Checking against a surrogate source: comparison to external datasets, forms • Checking against authoritativesource: comparison to real world entity

  34. Measure Information Qualityin Voice of Stakeholders

  35. Information Quality Measures • Definitions/Specifications • Timeliness • Time from first capture to record of reference • Completeness • Represent each instance in the real world • Completeness of values in existing fields • Accuracy • To surrogate source • To authoritative source • Usability • Presence of fields to address functional requirements

  36. Measure the Productto Improve its Process • Purpose is not to improve a product by measuring it, but to improve its production process • Product is of concern only from a limited perspective • Quality measures show how well processes for producing information are functioning; i.e., how well they address all stakeholder requirements

  37. Applications are notthe Product to Measure • Assessing applications addresses narrow requirements, not downstream requirements for the information • Address information as the product, understood as an enterprise resource • Measure the information that applications work on to assess development • Applications are machines on the assembly line, not the product

  38. Applications are Machineson the Assembly Line

  39. Improving Information (the Product) is not the Chief Concern • Right product to measure, but wrong purpose • Improving the product doesn't prevent errors or assure ongoing quality • Improve production processes • Information product improvement is all cost basis/scrap and rework • Correction of issues preventable by process

  40. Three Ways to Correct Information Quality • As a one-time process • As a regular conversion process • At the point of capture

  41. As a One-time Process for a Special Table • Not preventative; same problems recur because information production process has not changed • Quality of data decays; not addressing changes in the information • Creates a redundant table for the entity (encounters, services, providers, members)

  42. As a Regular Conversion for a Data Mart or Data Warehouse • Performed under constraint of a regular load for up-to-the-moment, daily analysis • Too late: requires automatic, estimated corrections • Corrections need to feed back to operational tables

  43. As a Regular Conversion for a Data Mart or Data Warehouse

  44. At the Point of Capture • Actual process improvement • Actually preventative • Based on understanding of information as enterprise resource • Information producers assess and improve business and technical/development processes based on understanding of stakeholder requirements

  45. At the Point of Capture Measure: - Definitions - Timeliness - Completeness - Accuracy - Usability Plan Do Check Act (Repeat)

  46. Do Both: • Improve at Point of Capture:Measure and improve information production process quality at the point of capture, from the standpoint of the requirements of all downstream stakeholders • Regular Cleanup and Transfer: Establish and document business rules for integration (cleanup and transfer), through stakeholder involvement (i.e., for CRMS load)

  47. Process Improvement for Information • Plan: • Identify stakeholders/customers • Survey stakeholders for requirements • Measure quality of product against requirements • Determine root cause for identified issues • Do: • Implement improvement for awhile • Check: • Measure again to determine success of improvement • Act: • Act to standardize the improvement (Repeat)

  48. Root Cause Analysis for Information

  49. Root Cause Analysis for Information

  50. Process Improvement Details Useful for the NCQA Baseline Assessment Tool