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Encounter Data Validation: Review and Project Update

Join Thomas Miller and Amy Kearney as they present the importance of encounter data for Florida's Medicaid program and discuss the EQR Protocol for data accuracy and completeness.

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Encounter Data Validation: Review and Project Update

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  1. Encounter Data Validation:Review and Project Update Presenters: Thomas Miller, MA Executive Director, Research and Analysis Team Amy Kearney, BA Associate Director, Research and Analysis Team 1

  2. Welcome • About the presenters • Rules for engagement • Presentation overview • The importance of encounter data • CMS protocols • Florida EDV study, including best practices for medical record procurement 2

  3. Objectives 3

  4. Importance of Encounter Data • Accurate and complete data are critical to success of managed care programs • Essential for overall management and oversight of Florida’s Medicaid program • Ability to monitor and improve quality of care • Establish performance measures • Generate accurate and reliable reports • Obtain utilization and cost information 4

  5. Importance of Encounter Data • Used by MCOs and the State for many purposes • Performance measure development and calculation • Performance improvement measurement • Focused studies/quality activities • Rate-setting • Compliance monitoring • Provider practice patterns 5

  6. Key Trends • Importance of Federal and State monitoring • Development of core measurement sets • Medicare versus Medicaid • Health care reform • Holding health care accountable • Data, not anecdotes 6

  7. Objectives 7 7

  8. Objectives 8

  9. EQR Protocol • Developed and refined with the evolution of the External Quality Review program 9

  10. EQR Protocol • Guidelines for External Quality Review Organizations (EQRO) to use when assessing completeness and accuracy of encounter data. • Data submitted by Managed Care Organizations (MCO) to the State 10

  11. EQR Protocol • State establishes standards for encounter data • State must establish the following standards: • Definition of “encounter” • Types of encounters • Data accuracy and completeness • Objective standards for data comparison 11

  12. EQR Protocol • Five key activities • Review state requirements • Review MCO’s capability • Analyze electronic encounter data • Review of medical records • Submission of findings and recommendations 12

  13. EQR Protocol • Attachment A: Encounter Data TablesTable 2: Data Element Validity Requirements 13

  14. EQR Protocol • Five key activities • Review state requirements • Develop understanding of State-specific policies and procedures for collecting and submitting encounter data • Identify data exchange protocols and layouts • Evaluate encounter data system interchange flows, including system edits and submission timelines • Review existing encounter data quality activities, requirements, and performance standards 14

  15. EQR Protocol • Five key activities, continued • Review MCO’s capability • Develop, conduct, and review MCO’s Information System Capabilities Assessment • Identification of IS vulnerabilities • Key informant interviews 15

  16. EQR Protocol • Five key activities, continued • Analyze electronic encounter data • STEP 1 - Develop data quality test plan to determine: • Magnitude and type of missing encounter data • Overall data quality issues • MCO data submission issues 16

  17. EQR Protocol • Five key activities, continued • Analyze electronic encounter data • STEP 2 - Verify integrity of encounter data • Macro-level analysis • Encounter file completeness and reasonableness • Volume and utilization by encounter type and service setting • Internal field consistency • General field completeness and validity 17

  18. EQR Protocol • Five key activities, continued • Analyze electronic encounter data • STEP 3 – Generate and Review Analytic Reports • Micro-level analysis • Encounter record completeness and reasonableness 18

  19. EQR Protocol • Five key activities, continued • Analyze electronic encounter data • STEP 4 – Compare findings to state-identified standards • Identification of appropriate benchmark population 19

  20. EQR Protocol • Five key activities, continued • Review of medical records • Verification of the accuracy of coding • Protocol assumptions • STEP 1 – Determine sampling for medical record review • Identify valid sample size • Encounter- vs. recipient-based samples 20

  21. EQR Protocol • Five key activities, continued • Review of medical records • STEP 2 – Obtain and review medical records and document findings • Procurement efficiencies • Abstraction staff and training • Categorization of errors by level, type, and source • Procurement tracking and abstraction tools 21

  22. EQR Protocol • Five key activities, continued • Submission of findings • Narrative report summarizing findings from Activities 1-4 • Actionable recommendations for overall encounter data quality improvement 22

  23. Questions? 23

  24. Objectives 24

  25. Objectives 25

  26. SFY 2013-2014 Encounter Data Validation (EDV) Study Agency for Health Care Administration Validation of Encounter Data 26

  27. Year One Encounter Data Validation (EDV) Study • Four key steps for conducting successful evaluations • Project implementation • Study design • Data collection &analysis • Reporting & recommendations 27

  28. Year One Encounter Data Validation (EDV) Study • Study design • Prepared and finalized methodology which included: • Study objectives and research questions • Data source and collection procedures • Measurement methodology • Analytic methods • Timeline 28

  29. Year One Encounter Data Validation (EDV) Study • Data collection and analysis • Information systems review • Questionnaire for AHCA • Assessment of AHCA’s policies and procedures for data exchange, its capacity and ability to acquire and process data, and its staff responsible for executing data processing • Questionnaire for MCOs • Assessment of MCOs’ claims processing systems and processes, and its capability to submit encounter data 29

  30. Year One Encounter Data Validation (EDV) Study • Data collection and analysis,continued • Information systems review • MCO questionnaire divided into five sections: • Submitting Encounter Data to AHCA • Handling Submission Information from AHCA • Encounter Data Submission from Capitated Providers • Processing and Submission of Medicare Crossover and other Third Party Claims • Policies and Procedures in Processing Payment Information 30

  31. Year One Encounter Data Validation (EDV) Study • Data collection and analysis, continued • Information systems review • AHCA questionnaire divided into three sections: • Data Exchange Policies and Procedures • Data Submission Processing Procedures and Personnel • Encounter Data Processing within the Florida MMIS 31

  32. Year One Encounter Data Validation (EDV) Study • Data collection and analysis,continued • Information systems review • Documentation will be used to assess encounter data quality • Questions target how data moves through AHCA’s data systems and how the MCOs prepare data files for submission 32

  33. Year One Encounter Data Validation (EDV) Study • Data collection and analysis,continued • Information systems review What has been completed? • Questionnaires were approved by AHCA and distributed to AHCA and the MCOs • Received completed questionnaires from AHCA and MCOs What needs to be completed? • Currently reviewing responses from AHCA and MCOs • May conduct additional follow-up for clarification 33

  34. Questions?

  35. Year One Encounter Data Validation (EDV) Study • Data collection and analysis, continued • Comparative data analysis of AHCA and MCO encounter data • Evaluates the extent to which encounters submitted by MCOs to AHCA are accurate, complete, and reasonable • Included all claim/service types—i.e., inpatient/outpatient, physician visits, dental, and pharmaceutical 35

  36. Year One Encounter Data Validation (EDV) Study • Data collection and analysis, continued • Comparative data analysis of State and MCO encounter data • Indicators to measure degree of completeness and accuracy for each encounter type • Overall record matching—percentage of state encounters present in MCO files • Field-level matching—percentage of state encounters with exact value match in MCO file for each select data element 36

  37. Year One Encounter Data Validation (EDV) Study • Data collection and analysis,continued • Comparative data analysis What has been completed? • Distributed data submission requirements documents to AHCA and MCOs • Conducted technical assistance sessions with MCOs on 9/16 & 9/17/2013 • Received, processed, and loaded encounter data 37

  38. Year One Encounter Data Validation (EDV) Study • Data collection and analysis, continued • Comparative data analysis of State and MCO encounter data What needs to be completed? • Conducting preliminary file review • Ensuring files are sufficient for processing • Completing basic checks • Generate comparative analysis tables and figures for final report 38

  39. Phew… Questions? 39

  40. Year One Encounter Data Validation (EDV) Study • Data collection and analysis, continued • Medical record review • Represents the “gold standard” • Evaluation of service level accuracyand completeness • Methodology developed: • Only includes MCOs operational as of January 2013 • Year One – SFY 2016: review one-third of plans each year as selected by AHCA • Minimum 50 cases reviewed per plan • Target professional, dental, and inpatient/outpatient encounters 40

  41. Year One Encounter Data Validation (EDV) Study • Data collection and analysis, continued • Medical record review • Sample selection methodology • To generate list of randomly selected encounters for medical review, HSAG will use AHCA’s data files from comparative analyses • Two-stage stratified sampling design used to ensure: • Member’s record is selected only once • Number of encounters included in final sample covers all encounter types and proportional to total distribution of encounters 41

  42. Year One Encounter Data Validation (EDV) Study • Data collection and analysis,continued • Medical record review • Sample selection methodology • HSAG will evaluate the key data elements below: 42

  43. Year One Encounter Data Validation (EDV) Study • Data collection and analysis, continued • Medical record review • Procurement and abstraction process • Based on established policies and procedures • Continually monitored to ensure validity and accuracy • Inter-rater reliability testing & Rater-to-standard testing • All reviewers must achieve 95% accuracy rate • Variety of reports will be generated, i.e., medical record compliance rates 43

  44. Year One Encounter Data Validation (EDV) Study • Data collection and analysis, continued • Medical record review – analysis of cases • Verify the service(s) provided on selected data of service and one additional date of service • Each enrollee listed on sample has corresponding selected date of service • Validate services conducted by provider on date of service as compared with encounter data • Reviewers to validate services for additional date of service. 44

  45. Year One Encounter Data Validation (EDV) Study • Data collection and analysis,continued • Medical record review – analysis of cases • Analyze record completeness and the accuracy of coding • Four primary indicators for data completeness and accuracy • Medical Record Agreement • Medical Record Omission (surplus) • Encounter Record Omission (missing) • Erroneous 45

  46. Year One Encounter Data Validation (EDV) Study • Data collection and analysis, continued • Medical record review What has been completed? • Introductory letter sent to MCOs on 10/1/13 • Conducted technical assistance calls with all participating MCOs on 10/16 & 10/18/13 46

  47. Year One Encounter Data Validation (EDV) Study • Data collection and analysis, continued • Medical record review What needs to be completed? • Pull samples and send lists of study cases • Provide letter to send to its providers with sample • MCOs will procure records from provider and accommodate various submission methods • MCOs to submit identified medical records to HSAG for review 47

  48. Year One Encounter Data Validation (EDV) Study • Reporting and recommendations • Prepare aggregate EDV report of findings from: • Information system review • Comparative Analysis • Medical Record Review • Preparation of supplemental findings for future evaluation by MCOs • Present statewide and MCO-specific results • Actionable recommendations for improvement 48

  49. Objectives 49

  50. Questions

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