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Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
Information Quality and Metadata in Healthcare Management
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Information Quality and Metadata in Healthcare Management

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This presentation is targeted to department heads and frontline staff who produce provider, member and medical treatment information in a Medicaid Managed Care enterprise. It covers the quality …

This presentation is targeted to department heads and frontline staff who produce provider, member and medical treatment information in a Medicaid Managed Care enterprise. It covers the quality approach to information, while fostering a work culture of information stewardship by clarifying information producer roles and how they can foster improving enterprise information and their own daily processes through updating and sharing of metadata in an annual process of completing the National Committee for Quality Assurance's Baseline Assessment Tool (now the HEDIS Roadmap).

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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) Childhood Immunization Status Annual Dental Visit Lead Testing Frequency of Ongoing Prenatal Care Use of Appropriate Medications for People with Asthma Children's Access to Primary Care Practitioners Antidepressant Medication Management Adults' Access to Preventive/Ambulatory Health Breast Cancer Screening Services Cervical Cancer Screening Ambulatory Care Comprehensive Diabetes Care Inpatient Utilization Controlling High Blood Pressure Births and Average Length of Stay, Newborns Follow-up After Hospitalization for Mental Illness Discharges and Average Length of Stay-Maternity Well Child and Preventive Care Visits in the 1st 15 Care Months of Life Mental Health Utilization-Inpatient Well Child and Preventive Care Visits - Children Chemical Dependency Utilization-Inpatient Ages 3-6 Years Frequency of Selected Procedures Adolescent Well-Care and Preventive Visits Timeliness of Prenatal Care Practitioner Turnover Postpartum Care Enrollment by County Board Certification/Residency Completion
  • 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 Creates Common 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 Fosters Information 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) • Plan an improvement based on factual basis • Do it for awhile • Check it for improvement • Act to standardize the improvement (Repeat)
  • 17. Process Improvement: Root Cause Analysis People Process Defect Tools Materials
  • 18. Overview of Production Processes Information Finance QM UM Etc. Stakeholders Information Operational Information Producers Data Mart Knowledge Workers Data Entry Members HEDIS/ Data QARR Claims/ Acquisition CRMS Encounters Providers Systems Performance Development Management
  • 19. Encounters Information Producers Data Entry Claims Data Acquisition CLAIMS/ ENCOUNTERS Care Providers Vendors Systems Development Developers/ Analysts
  • 20. Members Information Producers Data Entry Enrollment Data Acquisition MEMBERS Marketing Member Services Recertification Systems Development Developers/ Analysts
  • 21. Providers Information Producers Data Entry Network Information Data Acquisition PROVIDERS Network Development Provider Relations Systems Development Developers/ Analysts
  • 22. Encounters Stakeholders Information Stakeholders Finance QM UM Etc. HEDIS/ QARR Operational Decision Support Information System Quality Management Utilization Members Management Community Claims/ Health CRMS Encounters Institute Data Mining Providers P erformance Management
  • 23. HEDIS/QARR Quality Assessment and Medical Record Review Data Mart • Build CRMS • Create population samples • Extract compliant instances CRMS based on administrative data, along with member and provider site information, to a Special QARR special QARR database Review Database • Load laptops from this database
  • 24. Lack of Compliant Instances by 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 http://www.whitepages.com • 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 Data Mart • Send results to NY State Department of CRMS 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. Quality Approach to Information • 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
  • 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 Data Entry datasets, forms Information • Checking against (Encounters, authoritative source: Members, Providers) comparison to real Data Acquisition world entity
  • 34. Measure Information Quality in Voice of Stakeholders Information Finance QM UM Etc. Stakeholders Information Operational Information Producers Data Mart Knowledge Workers Data Entry Members HEDIS/ Data QARR Claims/ Acquisition CRMS Encounters Providers Systems Performance Development Management
  • 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 Product to 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 not the 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 Machines on the Assembly Line Applications Information
  • 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 Regular Estimated, Automated Corrections Operational Decision Support Systems System Cleanup & Transfer Members Claims/ CRMS Encounters Providers
  • 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 Operational Measure: Information Data - Definitions - Timeliness Entry - Completeness Members - Accuracy - Usability Data Claims/ Acquisition Plan Encounters Do Check Providers Systems Act Development (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 Business Process Quality Business Processes Personnel Methods / Procedures Information Documented Producers Procedures Data Process Intermediaries Steps Specific Defect Application Source Forms Database Hardware External Data Application / Source Data System
  • 49. Root Cause Analysis for Information Development Process Quality Development Personnel Methods Developers Application Development Analysts Data Analysis Specific Defect Metadata Definitions/ Repository Specifications, Business Rules Forms, Reports, Data Procedures, etc. Dictionary Development Source Materials Tools
  • 50. Process Improvement Details Useful for the NCQA Baseline Assessment Tool
  • 51. Process Improvement Steps • Plan: – Identify stakeholders/customers – Identify 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)
  • 52. 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
  • 53. Production Process Factors • People – Stakeholders, Information Producers, Knowledge Workers – Developers, Analysts • Process – Business Information Production Processes – Application/Data Development Methods • Tools – Systems, Applications, Databases, Hardware – Metadata Repositories, Data Dictionaries, CASE Tools • Materials – Requirements, Specifications, Business Rules, Documented Procedures, Reports, Forms, External Data Sources
  • 54. Simplified Picture For each entity (Encounters, Members, Providers) – Who are its stakeholders? – What processes use it? – What are their requirements? – Then standards, measures, rules, definitions, specifications, etc.
  • 55. Slightly More Detailed Picture • Definition Standards • Goals / Motivations • Product Specifications • Roles – Owners, Stakeholders • Business Requirements • Production Processes • Improvement Processes • Performance Measures • Performance Rates
  • 56. Very Complex Structure
  • 57. Purposes of Metadata • Foster process improvement for information • Enable information producers to understand requirements from an enterprise standpoint, for both business and technical/development processes • See all stakeholders, their processes that depend on the information, and their requirements • Provide clear, accurate consensus definitions to enable problem resolution • Enable developers to standardize and reuse specifications and business rules • Manage information as a resource, including identifying needless cost, how much value you're deriving, how and where
  • 58. Useful Steps to Take • Work on information production processes by surveying stakeholders for their requirements • Measure business and development processes according to requirements for the information as voiced by stakeholders • Improve information production processes at the point of capture • Devise rules for cleanup and transfer to decision support systems (CRMS) in collaboration with stakeholders • Begin to store metadata: Document and share stakeholders, processes, requirements, performance measures, business rules, etc.
  • 59. Foster Process Improvement through Common Understanding of Information Production Processes

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