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All Payer Claims Datasets:    Big Data is Coming to Public Health Officials, Doctors, Hospitals, and Patients             ...
Health Care Transformation - Before•       Focus on the individual patient in front of you•       Physician autonomy is pa...
Health Care Transformation - After•       Population health is the goal•       Patient autonomy is paramount•       Less i...
Health Care Transformation - Before• Valued tools:         – Physician knowledge and experience         – Patient chart   ...
Health Care Transformation - After• Valued tools:         –    Physician analytic and interpersonal skills         –    El...
Steps in the Transformation•       IT infrastructure•       Payment reform•       Transparency•       Workforce education ...
All Payer Claims Dataset• An aggregation of data files – eligibility records        plus medical and pharmacy claims – com...
What Do Claims Tell Us?•       What was done?•       For whom?•       When?•       By whom?•       Then what happened?•   ...
Why an APCD?• Rich information for health policy     – How does spending differ by location? Patient mix?     – What are t...
Why an APCD?• Support for informed consumer choice         – Where should I be treated?         – What will it cost?      ...
National Map of State APCDs                                                        11Source: APCD Council www.apcdcouncil....
Examples• Leading causes of illness and hospitalization• Rates of accidents, infections and cancer• Geographic differences...
       13
Antidepressant Use in Utah                             Utah Atlas of Health Care, Sept. 2010                              ...
Distribution of Antidepressant Use                            Utah Atlas of Health Care, Sept. 2010                       ...
     Source: VT Healthcare Claims Uniform Reporting & Evaluation System                                                   ...
30-Day Readmission Rates                 Source: VT Healthcare Claims Uniform Reporting & Evaluation System               ...
                          18     NHHealthCost.org
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APCD Data Sources•       Commercial (private) carriers•       Medicaid•       Medicare•       Uninsured•       Dental•    ...
Privacy • Patients          – HIPAA as minimum • Providers          – Reputation          – Proprietary information • Paye...
Links to Other Data and Initiatives• Quality – CMS, state reports, regional        collaboratives•       Vital statistics ...
National Collaboration• APCD Council (state and national data users),        America’s Health Insurance Plans, and nationa...
Limitations of APCDs • Based on claims data          – Not real-time          – Completeness and accuracy          – Alter...
Trends and Future Directions• Power and complexity are about to explode• Better understanding what we do and the effects  ...
Discussion               27
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John Freedman - All-payer claims databases - CHC Pilots & Collaborations

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APCDs - How Big Data in Health Care will Empower Patients and Transform Health Care

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John Freedman - All-payer claims databases - CHC Pilots & Collaborations

  1. 1. All Payer Claims Datasets: Big Data is Coming to Public Health Officials, Doctors, Hospitals, and Patients Near You John Freedman MD MBA Pilots & Collaborations December 7, 2012Copyright ©2012 Freedman Healthcare, LLC     
  2. 2. Health Care Transformation - Before• Focus on the individual patient in front of you• Physician autonomy is paramount• More is better• Listen to your doctor• Money has no place in the conversation• Valued tools: – Patient chart – Physician knowledge and experience – Well-equipped facilities   Copyright ©2012 Freedman Healthcare, LLC      2
  3. 3. Health Care Transformation - After• Population health is the goal• Patient autonomy is paramount• Less is more• Physicians guide patients to their decisions• Money has a (limited) place in the conversation• Valued tools: – Electronic health data – Learning systems – Physician analytic and interpersonal skills – Well-equipped facilities   Copyright ©2012 Freedman Healthcare, LLC      3
  4. 4. Health Care Transformation - Before• Valued tools: – Physician knowledge and experience – Patient chart – Well-equipped facilities   Copyright ©2012 Freedman Healthcare, LLC      4
  5. 5. Health Care Transformation - After• Valued tools: – Physician analytic and interpersonal skills – Electronic health data – Well-equipped facilities – Learning systems   Copyright ©2012 Freedman Healthcare, LLC      5
  6. 6. Steps in the Transformation• IT infrastructure• Payment reform• Transparency• Workforce education & training• Evidence-based medicine• Access, analysis and distribution of health information   Copyright ©2012 Freedman Healthcare, LLC      6
  7. 7. All Payer Claims Dataset• An aggregation of data files – eligibility records plus medical and pharmacy claims – compiled from multiple health benefits payers• First statewide APCD created in Maine in 2003   Copyright ©2012 Freedman Healthcare, LLC      7
  8. 8. What Do Claims Tell Us?• What was done?• For whom?• When?• By whom?• Then what happened?• What did it actually cost?   Copyright ©2012 Freedman Healthcare, LLC      8
  9. 9. Why an APCD?• Rich information for health policy – How does spending differ by location? Patient mix? – What are the trends in disease prevalence? – What are the trends in treatment choices? – How do disease, treatments, outcomes, etc. vary from region to region? By gender? By type of insurance coverage? By provider? – Which providers are better/worse in quality and cost?• Support for performance improvement – Transparent reporting of provider and payer results – Data set can be used by providers to drive their QI efforts    Copyright ©2012 Freedman Healthcare, LLC     9
  10. 10. Why an APCD?• Support for informed consumer choice – Where should I be treated? – What will it cost? – Enable market-driven health care• Powerful data for researchers – Policy research and clinical research   Copyright ©2012 Freedman Healthcare, LLC      10
  11. 11. National Map of State APCDs   11Source: APCD Council www.apcdcouncil.org 11/26/2012
  12. 12. Examples• Leading causes of illness and hospitalization• Rates of accidents, infections and cancer• Geographic differences in incidence of diseases, such as diabetes or heart disease• Ethnic, gender or socioeconomic variations in illness• Most expensive diagnoses and procedures• Role of prevention on illness and costs   Copyright ©2012 Freedman Healthcare, LLC      12
  13. 13.    13
  14. 14. Antidepressant Use in Utah Utah Atlas of Health Care, Sept. 2010   14
  15. 15. Distribution of Antidepressant Use   Utah Atlas of Health Care, Sept. 2010 15
  16. 16.    Source: VT Healthcare Claims Uniform Reporting & Evaluation System 16
  17. 17. 30-Day Readmission Rates   Source: VT Healthcare Claims Uniform Reporting & Evaluation System 17
  18. 18.    18 NHHealthCost.org
  19. 19.    19
  20. 20.    20
  21. 21. APCD Data Sources• Commercial (private) carriers• Medicaid• Medicare• Uninsured• Dental• Pharmacy   Copyright ©2012 Freedman Healthcare, LLC      21
  22. 22. Privacy • Patients – HIPAA as minimum • Providers – Reputation – Proprietary information • Payer protections – Reputation – Proprietary information   Copyright ©2012 Freedman Healthcare, LLC      22
  23. 23. Links to Other Data and Initiatives• Quality – CMS, state reports, regional collaboratives• Vital statistics – to assess mortality rates• Hospital Discharge Datasets – for additional data detail and measures• Health Information Exchanges – integrate claims and clinical (EMR) data• Health Insurance Exchanges   Copyright ©2012 Freedman Healthcare, LLC      23
  24. 24. National Collaboration• APCD Council (state and national data users), America’s Health Insurance Plans, and national data standards organizations (ANSI X12, NCPDP)• Supported by the Commonwealth Fund and AHRQ• “Harmonization” to reduce work involved• Allow data sharing across states• Long term goal of creating a national standard   Copyright ©2012 Freedman Healthcare, LLC      24
  25. 25. Limitations of APCDs • Based on claims data – Not real-time – Completeness and accuracy – Alternative payment arrangements • Cost – Implementation and ongoing operating expenses – Still lacks a clear business model • Access – Variable limits on access to data • Comparability between states – Harmonization will improve comparability   Copyright ©2012 Freedman Healthcare, LLC      25
  26. 26. Trends and Future Directions• Power and complexity are about to explode• Better understanding what we do and the effects that it has will make a bigger difference to health than more data about specific individuals   Copyright ©2012 Freedman Healthcare, LLC      26
  27. 27. Discussion   27

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