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Underwriting A medical director’s perspective. Michael L. Moore, MD FACP Vice President - Chief Medical Director Nationwide Insurance. What we’ll cover today. Underwriting definition and principles Current approaches to information gathering Why surprises happen Underwriting variation
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Underwriting A medical director’s perspective • Michael L. Moore, MD FACP • Vice President - Chief Medical Director • Nationwide Insurance
What we’ll cover today • Underwriting definition and principles • Current approaches to information gathering • Why surprises happen • Underwriting variation • Q & A
Underwriting • We are in business to sell insurance, NOT turn it away! • But we must add good cases NOT every case--> why we underwrite • Life insurance is a different animal than auto, health, or home insurance • Underwriting according to Life Insurers Fact Book (ACLI) • Underwriting is the process of classifying applicants for insurance by identifying such characteristics as age, gender, health,occupation, and hobbies. People with similar characteristics are grouped together and charged a premium based on the group’s level of risk. • Law of Large Numbers • Standard vs Man off of the Street • Applicants hold the ultimate trump card in underwriting!
Underwriting • Keep pushing closer and closer to the limits • Make underwriting process more convenient: • making decisions with less information • lower costs, more convenient • move processes behind the scene • leverage technology
Underwriting • eliminate MD examinations • eliminate stress tests • eliminate Chest X-Rays • Consumer Driven Interview • Wellness Credits • use saliva or urine when possible over blood test
Why do we underwrite? • Adverse Selection • Inequality in the amount of information between the two contracting parties • More concisely: • placing your bet when the race has already been run.
Underwriting • Surveillance Databases • Driving records, background checks • Medical Information Bureau (MIB)
Underwriting • Medical Information Bureau (MIB) • Started by medical directors over 100 years ago • Could be named: Insurance Fraud Prevention Bureau • collect basic information on life insurance applicants to prevent fraud • information is coded using a limited number of codes • forbidden to underwrite on the basis on MIB codes • Alert that other information may be present • May ask reporting company for “code details”
Pharmacy database • Provides listing of prescription activity including drug name, date, prescribing doctor • Approximately 60% of pharmacy plans are covered • Useful in: • low face amount cases i.e cheap and easy • confirm lack of meds admitted on history • obtain physician name and contact information
Despite all of the best efforts the following still happens!
“Failure to be candid” crosses all age and socioeconomic groups!
People LIE!! • The average adult tells 3 lies in the course of a day • Four out of ten regularly call in sick to get a day off of work • One in ten have lied that a relative died to get a day off • A quarter of all job applicants lied on the application • March 29,2012 USA Today survey: • Is it OK to cheat on taxes? • 5.5% “a little” • 7.5% “as much as possible”
In Life Insurance • One in fourteen did not provide correct information about their health or lifestyle • A second survey showed 15% lied on life insurance applications • 52% of men, 43% of women regularly lie to employers, friends, family and colleagues about the state of their health • Crosses all income levels- Feb 2012 National Academy of Science study showed the wealthy are even more likely to lie!
What do people lie about? • Their weight • How much they drink • How much they smoke • According to industry lab data: 2.5% of “non-smoking” applicants test positive for nicotine • Existing health problems • Driving history • Dangerous hobbies
What do people lie about? • Lies of omission • Seem more justifiable • Passive not active • Protect your loved ones • Favorite story
Man Faces Charges After Claiming $20,000 for Fake Dead Cat • On March 27, 2009, YevgenlySamsonov was reportedly involved in a minor traffic accident in Tacoma. A driver behind him was stopped at a traffic light when her foot slipped off the brake. Reported damage to both vehicles was minor. • Samsonov filed a claim that included chiropractic treatment of soft tissue injuries. The other driver’s insurer, PEMCO, paid him $3,452, according to the Insurance Commissioner’s office. • More than two years later Samsonov sought additional payment from PEMCO claiming that in addition to the vehicle damage and medical claim his cat Tom had been in the car and killed in the accident. The company issued him a check for $50 to compensate him for the cat, according to Kriedler’s office. • Samsonov then told PEMCO that he’d paid $1,000 for the cat, who’d been like a son to him, and he wanted to be paid $20,000, reports state. He sent the company two photos he said he’d taken of his cat.
Man Faces Charges After Claiming $20,000 for Fake Dead Cat MORAL It’s better to have a $50 check in hand than an internet cat picture in jail! • A PEMCO claims representative reportedly conducted a Google search under “Images” and discovered identical cat images appearing on websites, blogs and Facebook pages. The two images Samsonov submitted are of two different cats, and neither belonged to Samsonov, PEMCO canceled its $50 check and forwarded the case to the Insurance Commissioner’s anti-fraud unit.
What increases chances of misrepresentation? WSJ 5/26/12
Surprises- Unexpected Lab Results • Currently experiencing an epidemic of obesity • A study from Cancer (March 2012) showed an • increase in esophageal, pancreatic, uterine, and • kidney cancers --572,000 cases /year • data since 1985:
Obesity Trends* Among U.S. AdultsBRFSS, 1985 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% Source: Behavioral Risk Factor Surveillance System, CDC.
Obesity Trends* Among U.S. AdultsBRFSS, 1986 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% Source: Behavioral Risk Factor Surveillance System, CDC.
Obesity Trends* Among U.S. AdultsBRFSS, 1987 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% Source: Behavioral Risk Factor Surveillance System, CDC.
Obesity Trends* Among U.S. AdultsBRFSS, 1988 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% Source: Behavioral Risk Factor Surveillance System, CDC.
Obesity Trends* Among U.S. AdultsBRFSS, 1989 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% Source: Behavioral Risk Factor Surveillance System, CDC.
Obesity Trends* Among U.S. AdultsBRFSS, 1990 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% Source: Behavioral Risk Factor Surveillance System, CDC.
Obesity Trends* Among U.S. AdultsBRFSS, 1992 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% Source: Behavioral Risk Factor Surveillance System, CDC.
Obesity Trends* Among U.S. AdultsBRFSS, 1993 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% Source: Behavioral Risk Factor Surveillance System, CDC.
Obesity Trends* Among U.S. AdultsBRFSS, 1994 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% Source: Behavioral Risk Factor Surveillance System, CDC.
Obesity Trends* Among U.S. AdultsBRFSS, 1995 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% Source: Behavioral Risk Factor Surveillance System, CDC.
Obesity Trends* Among U.S. AdultsBRFSS, 1996 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% Source: Behavioral Risk Factor Surveillance System, CDC.
Obesity Trends* Among U.S. AdultsBRFSS, 1997 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% ≥20% Source: Behavioral Risk Factor Surveillance System, CDC.
Obesity Trends* Among U.S. AdultsBRFSS, 1999 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% ≥20% Source: Behavioral Risk Factor Surveillance System, CDC.
Obesity Trends* Among U.S. AdultsBRFSS, 2000 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% ≥20% Source: Behavioral Risk Factor Surveillance System, CDC.
Obesity Trends* Among U.S. AdultsBRFSS, 2001 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24% ≥25% Source: Behavioral Risk Factor Surveillance System, CDC.
Obesity Trends* Among U.S. AdultsBRFSS, 2002 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24% ≥25% Source: Behavioral Risk Factor Surveillance System, CDC.
Obesity Trends* Among U.S. AdultsBRFSS, 2003 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24% ≥25% Source: Behavioral Risk Factor Surveillance System, CDC.
Obesity Trends* Among U.S. AdultsBRFSS, 2004 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person) No Data <10% 10%–14% 15%–19% 20%–24% ≥25% Source: Behavioral Risk Factor Surveillance System, CDC.