Long Term Care International Forum
Preventive Health Screenings
for
Long Term Care Policyholders
4/27/06
Jack Smith, SVP-LLS
Dr. Andrew Manganaro, Chief Medical Officer-LLS
Chris Giese, Actuary-Milliman
Martin McBirney, Actuary-Independent Consultant
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Discussion Overview
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Can Preventive Screening Reduce Claims?-Jack Smith
ƒ Vision for clams saving potential in the LTCI Market.
ƒ Assessing the risk for disease relevant to the LTCI Market.
Vascular Disease & Bone Diminishment-Dr. Andy Manganaro
ƒ Facts about strokes and osteoporosis.
ƒ The impact of preventive screenings.
Effectiveness of Preventive Screens as Claims Management Tool-Chris Giese
ƒ Methodology and analytic model.
ƒ Body of study.
ƒ Results.
LTCI Product Evolution-Martin McBirney
ƒ Declining sales and lack of profitability.
ƒ Possibilities for proactive product model.
2
Can Preventive Screenings
Reduce LTC Claims?
ƒ SVP Business Development at Genworth Financial ‘93-01.
ƒ Relationship Between Preventive Screenings & LTCI
Industry.
ƒ Saw Preventive Screenings as Claims & Underwriting Tool.
ƒ Four Ways to Reduce Claims.
ƒ Engagement of Milliman for Study.
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Assessing the Risk For Disease
ƒ Since 1993, Life Line Screening (LLS) has been the leading provider of
mobile health screening services in the U.S.
ƒ Screenings are conducted at local churches and community centers.
ƒ In 2006 LLS will screen over 1.3 million participants at 19,000 events.
ƒ Target participant is asymptomatic, between the ages of 40-80 with
relevant risk factors. The average age is 62.
ƒ LLS performs 4 preventive screenings to assess the risk for:
ƒ Carotid Artery Disease
ƒ Abdominal Aortic Aneurysm
ƒ Peripheral Arterial Disease
ƒ Osteoporosis Risk Assessment
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Facts about Stroke & Osteoporosis
ƒ Strokes
ƒ 3rd Leading Cause of Death in U.S.
ƒ 2nd Leading Cause of Death among Women.
ƒ #1 Reason of Nursing Home Admissions.
ƒ Peripheral Artery Disease
ƒ Affects approximately 5% of people over age 50.
ƒ 6 times greater risk of heart disease when PVD is present.
ƒ Osteoporosis
ƒ Hip fractures are the 12th leading cause of death among women.
ƒ One of the leading initial causes of LTC claims.
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Vascular DiseaseThe Underlying Cause of Most Strokes
Fact
ƒ Disease can be present before symptoms occur.
ƒ Doctors typically do not prescribe testing for
asymptomatic individuals.
Result
ƒ Individuals remain at risk for a catastrophic event.
ƒ It’s what you don’t know about your health
that can be devastating.
Atherosclerosis
ƒAtherosclerosis or “hardening of the arteries” is the
underlying genesis of the majority of this debilitating
disease.
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The Impact of Preventive Screenings
Asymptomatic Disease Can Be Treated if Discovered Early
ƒ Stroke:
ƒ 50% of all stroke victims have no warning signs.
ƒ Strokes can be prevented through effective detection
and proper treatment.
ƒ Peripheral Vascular Disease:
ƒ A leading indicator of heart disease can be identified
early.
ƒ Osteoporosis:
ƒ A major cause of bone fracture in aging adults.
ƒ Bone loss can be prevented or slowed considerable
with proper identification and treatment.
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Preventive Screenings
For Asymptomatic Individuals
Preventive screenings should
make people aware of the
existence of an undetected health
problem and encourage them to
seek follow up care with their
own personal physician.
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Historical Screening Result Averages
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Vascular
ƒ Abnormal Carotid Rate
ƒ Abnormal Aorta Rate
ƒ Abnormal ABI Rate
Osteoporosis
ƒ High Risk
ƒ Moderate
ƒ Normal
2.1%
1.3%
4.7%
33%
19%
48%
Based on historical averages-Annual results can vary.
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Accurate & Appropriate Screenings
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High Incidence of Disease
ƒ 8-10% of all screenings are abnormal.
Quality Assurance Studies
ƒ University of South Florida and the Cleveland Clinic.
Sensitivity and Specificity
ƒ Sensitivity – our ability to detect disease=100%
ƒ Specificity – our ability to detect normality=94%
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Goal: Determine Effectiveness of Preventive
Screens as Claims Management Tool
Three Questions:
ƒ Do screens provide early warning?
ƒ Will people change behavior?
ƒ What is the financial impact?
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Models Developed
First Year
Risk
Reduction
Model
ƒ Early warning
LTC
Claims
Projection
Model
Durational
Impact
Model
ƒ Behavior change
(over time)
ƒ Behavior change
(at start)
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ƒ Financial impact
Flowchart for Stroke
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Flowchart for Stroke
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Aggregate Test Results
Distribution of Test Results 1
Screen
Normal
Moderate
Significant
Carotid Artery
96.2%
2.1%
1.6%
Bone Density
32.7%
32.9%
34.5%
1
Based on roughly 1.2 million screen results at the time of the study.
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Flowchart for Stroke
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Distribution of Follow-up Action
by Test Result
Carotid Artery Screen
Sample Risk Group: Male Age 75
Test Result
Action
Distribution
Normal
None
100%
Moderate
None
Change
Drugs
Surgery
85%
10%
5%
0%
Significant
None
Change
Drugs
Surgery
25%
35%
10%
30%
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Distribution of Follow-up Action
by Test Result
Carotid Artery Screen
Sample Risk Group: Male Age 75
Test Result
Action
Distribution
Normal
None
100%
Moderate
None
Change
Drugs
Surgery
85%
10%
5%
0%
Significant
None
Change
Drugs
Surgery
25%
35%
10%
30%
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Flowchart for Stroke
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Risk Reduction Percentage
by Age and Gender
Stroke
Age
Male
Osteoporosis
Female
Male
Female
55
8%
7%
15%
15%
65
14%
12%
16%
16%
75
17%
15%
17%
19%
85
20%
17%
17%
20%
Example: Male Age 65
100 Strokes (unscreened)
100 x (1-0.14) = 86 strokes (with screen)
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Models Developed
First Year
Risk
Reduction
Model
ƒ Early warning
Durational
Impact
Model
ƒ Behavior change
(over time)
ƒ Behavior change
(at start)
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LTC
Claims
Projection
Model
ƒ Financial impact
Sample Results –
Durational Impact Model
Stroke Risk Reduction - Male Age 75
35%
Risk Reduction
30%
25%
20%
15%
10%
5%
0%
1
6
11
16
Year Following Screen
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Models Developed
First Year
Risk
Reduction
Model
ƒ Early warning
LTC
Claims
Projection
Model
Durational
Impact
Model
ƒ Behavior change
(over time)
ƒ Behavior change
(at start)
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ƒ Financial impact
LTC Claim Dollars
Distribution by Primary Diagnosis
11%
5%
24%
9%
Ischemic Stroke
Fractures - Osteoporosis
Circulatory System Disease
Nervous System Disease
Mental Disorders
21%
Other
30%
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Sample LTC Claim Costs by
Attained Age With and Without Screen
Female : Issue Age 60
1,600
1,400
Claim Cost
1,200
1,000
800
600
Stroke: No Screen
400
Stroke: With Screen
Osteoporosis: No Screen
200
Osteoporosis: With Screen
0
65
68
71
74
77
80
83
86
Attained Age
25
89
92
95
98
Claims Projection Assumptions
ƒ Screen at beginning of sixth policy year.
ƒ Mortality improvement.
ƒ No impact on other diseases.
ƒ One application of screen.
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Baseline Impact of Screens
Statistic
Osteoporosis Claims
Total Claims
16%
14%
2.5%
$175
$144
$319
$340,000
$320,000
$660,000
Stroke Claims
% Reduction of Future LTC Claims 1
Baseline
Savings per Person Screened 1
Baseline
Undiscounted Claim Dollars Saved 2
Baseline
1
Lifetime present values calculated using 6% discount rate.
2 Based on future lifetime claims from 1,000 policyholders.
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Sensitivity Test One
ƒ How do results change if more follow-up action is
assumed?
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Sensitivity One: Impact of Screens
with Maximum Follow-Up
Statistic
Stroke Claims
Osteoporosis Claims
Total Claims
% Reduction of Future LTC Claims 1
Baseline
16%
14%
2.5%
Sensitivity One
23%
25%
4.1%
Baseline
$175
$144
$319
Sensitivity One
$260
$254
$514
Baseline
$340,000
$320,000
$660,000
Sensitivity One
$510,000
$590,000
$1,100,000
Savings per Person Screened 1
Undiscounted Claim Dollars Saved 2
1
Lifetime present values calculated using 6% discount rate.
2 Based on future lifetime claims from 1,000 policyholders.
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Sensitivity Test Two
ƒ Can economic benefit be improved by only paying for
screens for people that are more likely to have significant
test results?
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Sample – Top Scoring Pre-Screen Questions
Based on Logistic Regression Model
Carotid Artery Screen
Question
Base Score
Smoke = Yes
Smoke 50+ Years
Smoke 20-34 Years
Smoke <20 Years
Bone Density Screen
Scoring
55
50
135
100
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Question
Base Score
Weight
Scoring
70
-0.4 x Weight
Age & Gender = Female
4.0 x Max
(Age – 50, 0)
1.5 x Max
(Age -50, 0)
Had Carotid Operation
95
Age & Gender = Male
Prior Heart Flow Problems
80
Had Fracture After 50
50
Diabetes = Yes
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Smoke 35+ Years
25
High Blood Pressure = Yes
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Exercise 3x or More/Wk
-20
Cholesterol = Yes
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Hormone Replacement
Therapy = Yes
-30
High Blood Pressure = No
-30
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Sample – Bone Density Scoring
Calculation
Bone Density Screen
Assumptions
54 year old Female
Exercises 3x or more per week
Weight: 140 lbs.
Calculation
1) Baseline Score
70
2) Weight = -0.4 x 140
-56
3) Female: Age 54 = 4 x (54-50) 16
4) Exercise 3x
-20
Total
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Question
1) Base Score
Scoring
70
2) Weight
-0.4 x Weight
3) Age & Gender = Female
4 x Max
(Age – 50, 0)
Age & Gender = Male
1.5 x Max
(Age -50, 0)
Had Fracture After 50
50
Smoke 35+ Years
25
4) Exercise 3x or More/Wk
-20
Hormone Replacement
Therapy = Yes
-30
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Predictive Model Score for Individual
Probability of Significant Screen
Bone Density Screen
Carotid Artery Screen
Score
Probability
Score
Probability
-5
1.4%
-15
18.2%
35
2.2%
9
22.1%
105
4.3%
30
25.9%
180
8.6%
55
31.1%
225
12.9%
88
38.5%
128
48.3%
177
60.3%
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Sensitivity Two: Impact of Screens
with Segmented Population & Maximum Follow-Up
% Reduction of Future LTC Claims 1
Baseline
16%
14%
2.5%
Sensitivity One
23%
25%
4.1%
Sensitivity Two
28%
28%
5.3%
Baseline
$175
$144
$319
Sensitivity One
$260
$254
$514
Sensitivity Two
$357
$427
$784
Baseline
$340,000
$320,000
$660,000
Sensitivity One
$510,000
$590,000
$1,100,000
Sensitivity Two
$460,000
$550,000
$1,010,000
Savings per Person Screened 1
Undiscounted Claim Dollars Saved 2
1
Lifetime present values calculated using 6% discount rate.
2 Based on future lifetime claims from 1,000 policyholders.
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Summary of Economic Impact
Number of
Screens
Claim Dollars
Saved
Baseline
2,000
$660,000
Maximum Follow-up
2,000
$1,100,000
Predictive Segmenting 1
1,269
$1,010,000
Scenario
1
Number of Screens = 679 (carotid artery) + 590 (bone density)
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Goal: Determine Effectiveness of Preventive
Screens as Claims Management Tool
Three Questions:
ƒ Do screens provide early warning?
Yes, Probability of Stroke/Osteoporosis reduced
by 10-20%
ƒ Will people change behavior?
Overall incidence lower if some slow disease
progress
ƒ What is the financial impact?
Claim dollars saved can be significant
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Today’s Product Model
ƒ An accident of history (Medicare roots, 3 day
hospital stay, etc.)
ƒ Reactive, crisis-driven that comes in after the
event.
ƒ Waits until you’re broken to keep you going
broke.
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A Different Product Model
ƒ Take advantage of trends in consumer driven
health care - Put the Customer in charge.
ƒ Take advantage of current risk and disease
technology to help keep people out of nursing
homes.
ƒ Lower costs, improved outcomes, more profits.
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A Ideal Sales Model
ƒ Empower customers, don’t scare them.
ƒ Explain what they can do to help themselves.
ƒ Show them that you have the resources to help
protect their wealth . . . and their health.
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Thank You
Questions for our panel members can be directed to:
Jack Smith: jsmith@llsa.com
Dr. Andrew Manganaro: amanganaro@llsa.com
Chris Giese: chris.giese@milliman.com
Martin McBirney: mmcbirney@supersat2.net
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