Copyright ©2011 Freedman Healthcare, LLC All Payer Claims Datasets: Big Data is Coming to Public Health Officials, Providers and Patients Near You StrataRx John Freedman MD MBA October 16, 2012

Health Care Transformation - Before Focus on the individual patient in front of you Physician autonomy is paramount All else being equal, more is better Physicians make the decisions Money has no place in the conversation Valued tools: –Patient chart –Physician knowledge and experience –Well-equipped facilities

Health Care Transformation - After Population health management Patient autonomy is paramount All else being equal, less is better 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

Steps in the Transformation IT infrastructure Payment reform Transparency Workforce education & training Evidence-based medicine Access, analysis and distribution of health information

All Payer Claims Dataset An aggregation of data files – including eligibility records plus medical and pharmacy claims – compiled from multiple health benefits payers First statewide APCD created in Maine in

What Do Claims Tell Us? What was done? When? For whom? By whom? Then what happened? What did it actually cost?

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 7

Why an APCD (Cont’d) Support for informed consumer choice –Where should I be treated? –What will it cost? Powerful data for researchers –Policy research and clinical research 8

National Map of State APCDs Source: APCD Council 10/10/2012www.apcdcouncil.org 9

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 10

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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

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APCD Data Sources Commercial (private) carriers Medicaid Medicare Uninsured Dental Pharmacy 19

Privacy Patients –HIPAA as minimum Providers –Reputation –Proprietary information Payer protections –Reputation –Proprietary information 20

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 21

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 22

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 23

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 24