john freedman - all-payer claims databases - chc pilots & collaborations

Copyright ©2012 Freedman Healthcare, LLC

All Payer Claims Datasets:Big Data is Coming to Public Health

Officials, Doctors, Hospitals, and Patients Near You

John Freedman MD MBAPilots & Collaborations

December 7, 2012

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

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


Health Care Transformation - Before

• Valued tools:– Physician knowledge and experience– Patient chart– Well-equipped facilities


Health Care Transformation - After

• Valued tools:– Physician analytic and interpersonal skills – Electronic health data– Well-equipped facilities– Learning systems


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 – eligibility records plus medical and pharmacy claims – compiled from multiple health benefits payers

• First statewide APCD created in Maine in 2003


What Do Claims Tell Us?

• What was done?

• For whom?

• When?

• 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


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


National Map of State APCDs

Source: APCD Council www.apcdcouncil.org 11/26/201211

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


Antidepressant Use in Utah

Utah Atlas of Health Care, Sept. 2010

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Distribution of Antidepressant Use

Utah Atlas of Health Care, Sept. 2010

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Source: VT Healthcare Claims Uniform Reporting & Evaluation System

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30-Day Readmission Rates

Source: VT Healthcare Claims Uniform Reporting & Evaluation System

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NHHealthCost.org

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APCD Data Sources

• Commercial (private) carriers

• Medicaid

• Medicare

• Uninsured

• Dental

• Pharmacy


Privacy

• Patients– HIPAA as minimum

• Providers– Reputation – Proprietary information

• Payer protections– Reputation– Proprietary information


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

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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


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


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


Discussion

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john freedman - all-payer claims databases - chc pilots & collaborations

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