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1 Underwriting with Prescription Histories Texas Wide Underwriting Conference April 4, 2011 Mark Franzen, Ph.D., FSA Milliman IntelliScript
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2 Agenda How Rx Histories work Myths / Realities Measuring Value Client Studies RGA mortality study Interpreting Rx History Reports Red / Yellow / Green Rule Engine
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3 How does it work? 1.Obtain the authorization 2.Submit the query 3.Review the results Data Source
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4 Pharmacy Benefit Manager (PBM) PBM Health Plans Retail Pharmacies PBMs administer Rx benefits Employers Gov’t
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5 Prescription Histories have become a standard In use for 10 years IntelRx founded in 2001 Acquired by Milliman in 2005 – renamed IntelliScript 100% focus on Rx-history solutions Widely adopted in individual health, LTC, life Milliman: More than 150 insurance company clients 3.4 million queries in 2010
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6 What’s returned on an Rx History? Prescription Brand and generic name Dosage, quantity Date of fill Underwriting significance indicator Physician Specialty Contact info Pharmacy Contact info Dates of eligibility
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7 Fully Compliant with HIPAA and FCRA Applicant authorizes access to pharmacy records Authorization elements specified by HIPAA All Insurers using Rx Histories are audited Applicants may request a free copy of their Rx report May dispute inaccuracies directly with Rx provider Insurer must provide FCRA notice when an adverse decision is based on the Rx report
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8 Myths “Prescription Database” “My company is not subject to HIPAA” “Recent legislation threatens use of Rx Histories” “Hit Rates are too low”
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9 Measuring value Insurer studies 35+ proprietary insurer studies Results owned by insurer RGA Mortality Study
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10 Insurer Studies Two ways insurers measure benefit to cost: Retrospective Study Select sample of recently issued cases “Re-underwrite” using Rx histories Track decision changes “Live” Pilot Underwriters track decision changes while using Rx Histories Online survey and reporting In either case: Value of Rx = Sum of actuarial value of decision changes
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11 RGA Rx Mortality Study – March 2009
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12 RGA Rx Mortality Study 1.1 million insurance applicants from 2005-2007 All with Rx histories at time of application 21 million distinct prescription fills 2,530 deaths between 2005-2007 (from Social Security Death File) Relative mortality ratios calculated for Red / Yellow / Green and other subgroups based on prescription history.
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13 Mortality Study Results 13 Exposure Proportion No Hit Slightly worse than average Eligibility Only About average Green/Yellow Only Significantly better than average Red Significantly worse than average
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14 Red Fill Frequency 14 Exposure Proportion
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15 Tools for Interpreting Rx Histories Red / Yellow / Green Indicator Rule Engine
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16 Red / Yellow / Green Classification System Every drug mapped to an underwriting significance Significant (e.g. Digoxin) Potentially Significant (e.g. Norvasc) Likely Not Significant (e.g. Amoxicillin) Separate mappings for Life / Health / LTC Insurers use mappings “out of the box” or customize
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17 Why might you consider an Rx rule engine? Large volume of applications Large number of Rx fills Inconsistent Rx expertise Inconsistent interpretation
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18 What is RxRules? Rx Guidance Conditions Severity Decision IntelliScript Rx data RxRules Rule variables: Indication / Therapeutic class Drug combinations Red / Yellow / Green Fill timing (date or duration ranges) Fill counts / patterns Dosage / quantity Physician specialty / count Gender / Age Eligibility Confidential for
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19 RxRules... 400+ Rules Identify condition Provide underwriting guidance Transparency All rules visible / editable Guidance tailored to match insurer’s policies / underwriting guidelines Confidential for
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20 Thanks for your time! Mark Franzen, FSA, Ph.D. Milliman IntelliScript 262-796-3450 mark.franzen@milliman.com
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