The Case for a Comprehensive Cross-Payer
Health DatabaseMac McCarthy, FSA, FCA, MAAA
Middle Atlantic Actuarial ClubSeptember 13, 2013
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SpeakersMac McCarthy,FSA, FCA, MAAA
McCarthy Actuarial Consulting
Tom Persichetti,ASA, FCA, MAAA
Persichetti & Associates
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Agenda• Current State of Healthcare Claim Data• Affected Parties’ Issues
– Buyers– Payers– Researchers & Policymakers– Providers
• Consequences• Why Consolidated, Shared Data Makes Sense• Potential / Emerging Solutions• Impediments & Concerns• Audience Q&A
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Current State of Healthcare Claim Data
• Each payer has proprietary database– Payers include government programs,
insurance companies (including HMOs), and employers
• State all-payer databases• Data warehouse services• No central repository
– Little or no information sharing
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Buyers’ Issues
• Buyers = – Individuals / Consumers / Patients– Employers
• Inability to ascertain providers’ and competing treatments’ value
• Information overload & credibility deficits• Frustration due to:
– Poor communication between care providers– Inconsistent billing and benefit statements– Lack of accountability
• Distrust is widespread
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Payers’ Problems
• Payers =– Insurers– Employers– Governments
• Projecting future costs• Fraud and waste• Assuring value for
clients/employees/constituents• Managing financial risk
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Policymakers’ & Researchers’ Needs
• Credible data on alternative treatments for specific conditions– Prevalence, effectiveness & costs– Stratified by population characteristics– Considering comorbidities
• Reliable information on the impact of:– Plan design– Alternative payment strategies– Wellness & disease management programs– Provider consolidation & density
• Quantification of fraud, abuse and waste in the healthcare industry
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Providers’ Concerns
• Inappropriate / unmanageable risk assumption
• Demand anticipation • Revenue protection• Reputation• Control
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Consequences• FBI estimate for 2009 fraud1: 3% - 10% of
total health spending ($75–$250 billion)– Recoveries in 2012? Only $4.2 billion2
• Truven Payment Integrity Analysis3:– Annual fraud and abuse = $125 – 175 billion– Lack of care coordination = $25 - $50 billion– Provider inefficiency and errors = $75 - $100
billion
1: Health Affairs, 28, no.5 (2009): Combating Fraud In Health Care: An Essential Component Of Any Cost Containment Strategy2: HHS/DOJ Healthcare Fraud and Abuse Control Program, FY20123: Truven Health Analytics: Payment Integrity Analysis, April 2013
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Consequences• Time for recommended evidence-
based practice to be fully implemented4:
9 years
• National Health Expenditures increase, relative to GDP growth, 2000 - 2011: Double
4: Commonwealth Fund: Blueprint for the Dissemination of Evidence-Based Practices in Health Care
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Consolidated, Shared Data Makes Sense
• Fraud payment avoidance• Consumer Driven Health Plans• Shared risk models
– ACOs, PCMHs, Bundled Payments• Efficient capital investments and
provider workforce development• Comparative effectiveness studies• Enhanced disease tracking for early
identification of emerging epidemics and localized “hotspots”
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Potential / Emerging Solutions
• Verisk Health– Pooled-Data Alliance between health
insurers– “For the first time, healthcare payers will
be afforded the same comprehensive view of suspect providers and schemes that has proved so successful for the property/casualty industry.”
– Applies fraud detection tools developed in the property & casualty insurance markets, adapted to the healthcare environment
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Potential / Emerging Solutions
• HealthcarePays– Member-owned “industry utility”
• Membership is open to healthcare payers and providers– “The HealthcarePays network connects employers,
payers, providers, banks, key government agencies and waste and fraud systems to provide a level of transparency that enables unparalleled waste and fraud detection.”
– Mirrors fraud avoidance techniques used by credit card industry
– Cross-payer / cross-provider claims data will be available to members , subject to member defined governance and applicable privacy regulations
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Impediments & Concerns Dialogue
No one understand
s meWhat
do you mean?
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You have Questions
We have Answers