1 Underwriting with Prescription Histories Texas Wide Underwriting Conference April 4, 2011 Mark Franzen, Ph.D., FSA Milliman IntelliScript

2 Agenda  How Rx Histories work  Myths / Realities  Measuring Value Client Studies RGA mortality study  Interpreting Rx History Reports Red / Yellow / Green Rule Engine

3 How does it work? 1.Obtain the authorization 2.Submit the query 3.Review the results Data Source

4 Pharmacy Benefit Manager (PBM) PBM Health Plans Retail Pharmacies PBMs administer Rx benefits Employers Gov’t

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

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

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

8 Myths  “Prescription Database”  “My company is not subject to HIPAA”  “Recent legislation threatens use of Rx Histories”  “Hit Rates are too low”

9 Measuring value  Insurer studies  35+ proprietary insurer studies  Results owned by insurer  RGA Mortality Study

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

11 RGA Rx Mortality Study – March 2009

12 RGA Rx Mortality Study  1.1 million insurance applicants from All with Rx histories at time of application  21 million distinct prescription fills  2,530 deaths between (from Social Security Death File)  Relative mortality ratios calculated for Red / Yellow / Green and other subgroups based on prescription history.

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

14 Red Fill Frequency 14 Exposure Proportion 

15 Tools for Interpreting Rx Histories  Red / Yellow / Green Indicator  Rule Engine

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

17 Why might you consider an Rx rule engine?  Large volume of applications  Large number of Rx fills  Inconsistent Rx expertise  Inconsistent interpretation

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

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

20 Thanks for your time! Mark Franzen, FSA, Ph.D. Milliman IntelliScript