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

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, 2012
Copyright ©2012 Freedman Healthcare, LLC

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
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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
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4. Health Care Transformation - Before
• Valued tools:
– Physician knowledge and experience
– Patient chart
– Well-equipped facilities
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5. Health Care Transformation - After
• Valued tools:
– Physician analytic and interpersonal skills
– Electronic health data
– Well-equipped facilities
– Learning systems
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6. Steps in the Transformation
• IT infrastructure
• Payment reform
• Transparency
• Workforce education & training
• Evidence-based medicine
• Access, analysis and distribution of health
information
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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
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8. What Do Claims Tell Us?
• What was done?
• For whom?
• When?
• By whom?
• Then what happened?
• What did it actually cost?
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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
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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
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11. National Map of State APCDs
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Source: APCD Council www.apcdcouncil.org 11/26/2012

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
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13.
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14. Antidepressant Use in Utah
Utah Atlas of Health Care, Sept. 2010
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15. Distribution of Antidepressant Use
Utah Atlas of Health Care, Sept. 2010
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16. Source: VT Healthcare Claims Uniform Reporting & Evaluation System
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17. 30-Day Readmission Rates
Source: VT Healthcare Claims Uniform Reporting & Evaluation System
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18.
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NHHealthCost.org

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21. APCD Data Sources
• Commercial (private) carriers
• Medicaid
• Medicare
• Uninsured
• Dental
• Pharmacy
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22. Privacy
• Patients
– HIPAA as minimum
• Providers
– Reputation
– Proprietary information
• Payer protections
– Reputation
– Proprietary information
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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
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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
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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
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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
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27. Discussion
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