st. john’s, newfoundland, canada june 28-29, 2005

St. John’s, Newfoundland, CanadaJune 28-29, 2005

CIA Annual MeetingCIA Annual MeetingSession 3203 Session 3203

Value of WellnessImproving Health, Addressing Costs

Nico Pronk, Ph.D., MA, FACSM, FAWHPHealthPartners Health Behavior Group

HealthPartners Center for Health PromotionHealthPartners Research Foundation

Minneapolis, Minnesota

LOOKING BACK…focused on the futureLOOKING BACK…focused on the future

Outline Outline

• Disease costs, prevention saves• Medical care expenditures and

• Disease status• Modifiable health factors

• Productivity and health risks• Changing health risks and associated costs• Using health assessments to identify opportunities

for cost management• Incentives and participation• Conclusions


Disease cost,

prevention saves

Why invest in prevention?


Healthy/low Risk At-RiskHighRisk

Early Symptoms

ActiveDisease

20% of people

generate

80% of costs

That means, 80% of people generate only 20% of the costs

Disease costs, prevention saves.

Claims Cost Distribution


…improve the health and well being of members (employees, patients)…

…so that, function is improved…

… and quality of life improves…

…and health care cost and utilization reduces

…and disability is controlled

…and productivity is enhanced

The approach is to…


If you maintain the health and well being of currently healthy members (employees, patients)…

…quality of life stays high

…health care cost and utilization stays low

…disability is prevented

…productivity stays high

…excess costs are avoided.

Furthermore…


So, why is it so hard to prove the value of

prevention?


Disease is preventable;

Modifiable health risk factors occur prior to disease onset;

Many modifiable health risks are associated with increased health care costs;

Modifiable health risks can be improved;

Improvements in health risks can lead to reductions in health costs;

Improvements in health risks can lead to improvements in productivity;

Well-designed and well-implemented programs can save more money than they cost (positive ROI)

The Logic Flow


1. A large proportion of diseases and disorders is preventable. Modifiable health risk factors are precursors to a large number of diseases and disorders and to premature death (Healthy People 2000, 2010, Amler & Dull, 1987, Breslow, 1993, McGinnis & Foege, 1993).

2. Many modifiable health risks are associated with increased health care costs within a relatively short time window (Milliman & Robinson, 1987, Yen et al., 1992, Goetzel, et al, 1998, Anderson et al., 2000, Bertera, 1991, Pronk, 1999).

3. Modifiable health risks can be improved through workplace sponsored health promotion and disease prevention programs (Wilson et al., 1996, Heaney & Goetzel, 1997, Pelletier, 1999).

4. Improvements in the health risk profile of a population can lead to reductions in health costs (Martinson, et al., 2003, Edington et al., 2001, Goetzel et al., 1999).

5. Worksite health promotion and disease prevention programs save companies money in health care expenditures and produce a positive ROI (Johnson & Johnson 2002,Citibank 1999-2000, Procter and Gamble 1998, Chevron 1998, California Public Retirement System 1994, Bank of America 1993, Dupont 1990).

The Evidence


Medical CareExpenditures


MEAN CUMULATIVE 3-YEAR MEDICAL CHARGES FOR DIABETES PATIENTS BY CO-MORBIDITIES AND GLYCEMIC CONTROL

DM +HTN+ HD

DM +HD

DM +HTN

DMOnly

HbA1c 6%

HbA1c 7%HbA1c 8%

HbA1c 9%HbA1c 10%

05000

100001500020000250003000035000400004500050000

$

DM = DiabetesHTN = HypertensionHD = Heart Disease Source: Gilmer, et al. Diab. Care, 1997; 20:1847-1853


Nonw

hite wom

an

Nonw

hite man

Whit

e wom

an

Whit

e man

Difference

Low Risk

High Risk

010002000300040005000600070008000

• Mean annual health care charges for low-risk and high-risk individuals by gender and race (adjusted for chronic disease)

• Low-risk: • BMI=25 kg/m2• Never smoker• Physical activity at 3 d/wk

• High-risk:• BMI=27.5 kg/m2• Current smoker• Sedentary (0 d/wk)

• Overall mean charges = $4,201• Absolute difference in charges ranges

between $1,500 and $2,500• Relative risk difference equals 49%

$

Source: Pronk, et al. JAMA 1999;282:2235-2239

Lifestyle-related, Modifiable Risk Factors and Costs


Percent Difference in Medical Expenditures:High-Risk versus Lower-Risk Employees

Independent effects after adjustment70.2

46.3

34.8

21.4 19.714.5 11.7 10.4

-9.3-3.0-0.8

-50

-25

0

25

50

75

100

Per

cen

t

Dep

ress

ion

Str

ess

Glu

cose

Wei

gh

t

To

bac

co-P

ast

To

bac

co

Blo

od

pre

ssu

re

Exe

rcis

e

Ch

ole

ster

ol

Alc

oh

ol

Eat

ing

Source: Goetzel RZ, et al, Journal of Occupational and Environmental Medicine 40 (10) (1998): 843–854.

Incremental Impact of 10 Modifiable Risk Factors on Medical Expenditures


Source: Anderson, D.R., et. al, American Journal of Health Promotion, 15:1, 45-52, September/October, 2000. Health care expenditures - 1996 dollars. Independent effects after adjustment

• High stress generates annual per capita cost of $136 (1996 dollars)

• $428 per capita for assessed areas• 24.9% of health care costs

• High stress generates annual per capita cost of $136 (1996 dollars)

• $428 per capita for assessed areas• 24.9% of health care costs

Population Risk and Cost Impact

Per Capita Cost of High-Risk Status

$136

$97

$70$56

$44$29 $26

$8-$33-$3-$2

$(75)

$(50)

$(25)

$-

$25

$50

$75

$100

$125

$150

$175

Str

ess

Tob

acco-

Past

Weig

ht

Exerc

ise

Tob

acco

Glu

cose

Dep

ressio

n

Blo

od

Pre

ssu

re

Alc

oh

ol

Ch

ole

ste

rol

Eati

ng

Dollars

Per

Em

plo

yee


Productivity and Work Performance


Source: Pronk, NP. ACSM’s Health & Fitness Journal 2003;7(3):31-33

100

75

50

25

0

-25

-50

-75

-100

Optimal, best possible performance, fully present

Fully absent, no work or duties performed

Worst possible performance, fully present

Per

form

ance

Qua

lity

Uni

ts (

%) 100

75

50

25

0

-25

-50

-75

-100

Hou

rs-o

n-T

ask

(%)

Work Performance Scale


• Obesity impact on work limitations

• NHANES III and NHANES 1999-2000 data

• Obese workers, regardless of gender, are more likely than normal weight workers to report being limited in the amount or type of work they can do because of physical, mental or emotional problems (6.9% vs. 3.0%, respectively)

Source: Hertz, et al. JOEM 2004; 46:1196-1203.

0

2

4

6

8

10

12

14

16

Normal Weight 1.9 3.6 8.4

Overweight 2 3.6 8.1

Obese 4.1 8 14.5

20-39 40-59 60+

Impact of obesity on work limitations is akin to 20 years of

aging

Productivity and Health RisksObesity and Work Limitations


• Annual excess absenteeism, presenteeism, and critical incidents studied in:

• Reservation agents• Customer service representatives• Executives • Railroad engineers

• Assessment tool:• WHO Health and Work Performance Questionnaire

(WHO HPQ) (www.hpq.org)

Source: Wang, et al., JOEM, 2003; 45(12):1303-1311.

Chronic Conditions and Work Performance


PA moderate Quality 0.0574 0.0017 ImprovementWork rate 0.0517 0.0047 Improvement

PA vigorous Work rate 0.0538 0.0039 Improvement

Cardiorespiratory Quantity 0.0118 0.0454 ImprovementFitness Extra effort 0.2098 0.0299 Improvement

BMI obese Getting along -0.239 0.0156 Decrement

BMI morbid Work loss days 1.0155 0.032 Decrement

Dep. Var. β p Effect on PROD

Source: Pronk, et al., JOEM, 2004; 46(1): 19-25.

Work Performance and Physical Activity, Cardiorespiratory Fitness, and Obesity


Does a Change in Health Risk Result in a Change

in Cost?


-1000

-500

0

500

1000

1500

2000

2500

Hi-Hi

Hi-Lo

Lo-Hi

Lo-Lo

Medical STD

• Improving health risks contains escalating medical costs and improves productivity (esp. STD costs)

• Largest reduction in costs experienced in those moving from high-risk to low-risk

• Total 2-year costs for groups was follows:

• H-H = $6,942• H-L = $3,919• L-H = $3,897• L-L = $2,477

• Those who remain at low risk maintain the best cost and productivity profile

• Note: Risk assessed by HRA; linked to medical and STD costs for the years 1998-1999 compared to 2000-2001

Source: Edington and Musich. HPM 2004;3(1):12-15.

$

Change in Health Risk and Change in Cost


• Prospective cohort study (N=2,393 adults, age 50 and older)

• Predicting changes in health care charges between two 1-year periods (Sept ’94 to Aug ’95 and Sept ’96 to Aug ’97) due to increased physical activity

• Statistical adjustment for age, gender, co-morbidity, smoking, BMI

Source: Martinson, et al. Preventive Medicine 2003;37:319-326.

Change in Physical Activity, Change in Costs

Considering a more rigorous study design using an actual underlying cause of mortality, i.e., physical activity


-2,500

-2,000

-1,500

-1,000

-500

0

$

Inactive-Active

Inactive-Inactive

Change in Mean Annual Total Charges

• Increased PA among older adults is associated with lower annual health care charges within 2 years (1994-1995 to 1996-1997) as compared to continuously inactive controls

• Among those who increase PA from 0-1 to 3+ days per week, decline in costs is as much as ~$2,200

• Such cost savings easily justify investments in PA programs

Source: Martinson, et al. Preventive Medicine 2003;37:319-326.

Change in PA, Change in Costs


Focus: • Peer reviewed journals (English Language) – 196 studies pared down to 72

studies meeting inclusion criteria for reviewScoring Criteria:

• A (experimental design)• B (quasi-experimental – well controlled)• C (pre-experimental, well-designed, cohort, case-controlled)• D (trend, correlational, regression designs)• E (expert opinion, descriptive studies, case studies)

Health promotion program impact on health care costs:• 32 evaluation studies examined – Grades: A (4), B (11), other (17)• Average duration of intervention: 3.25 years• Positive impact: 28 studies• No impact: 4 studies (none with randomized designs)• Average ROI: 3.48 to 1.00 (7 studies)

Steven G. Aldana, Ph.D. American Journal of Health Promotion, May/June, 2001, 15:5.

Literature Review on Financial Impact


Using Health Assessments to identify health behavior

change opportunities in order to better manage costs


• 9,981 employees were invited to complete the HA in early 2004• 5,113 (51.2%) completed the HA• Selected risk-related variables were associated with paid medical care expenditures• Analyses were limited to employees who were members for 9-12 months of enrollment in 2003 (n=3,937)• Gender ratio of HA responders: 83% female, 17% male• Non-responders were, on average, 7 years older than responders• Compared to a multi-employer comparison group, HP HA responders have significantly higher rates of

asthma, depression, diabetes, periodontal disease, back pain, and gestational diabetes (based on self-report)

Responders Non Responders

n 3,937 3,827

Average age 42.2 years 49.3 years

Average paid claims $3,685 $4,280

Prevalence of CHF* 0.25% 1.52%

Prevalence of CAD* 1.87% 6.54%

Prevalence of Diabetes* 1.41% 4.7%

* Based on HealthPartners diagnosed disease registry, 2004 data. All values significant at p<0.05.

Background


Paid Amount by Total Health Potential Score

5629

44894222

3422

2846

2351 2350

0

1000

2000

3000

4000

5000

6000

300-699

700-749

750-799

800-849

850-899

900-949

950-1000

Score Categories

0

10

20

30

40

50

60

70

80

90

100

Paid Dollars % of Respondents

• Total Health Potential Score is out of a possible 1,000 points

• n = 3,937

• Paid expenditures tend to decrease as the Total Health Potential Score increases

• Averages for the lowest Total Health Potential Score categories are significantly higher than the means for the highest Total Health Potential Score categories (p<0.05)

$ %

HA Total Health Potential Score and Paid Medical Care Costs


Paid Amount by Modifiable Health Potential Score

40954301

39003523

3018 2897

0

1000

2000

3000

4000

5000

6000

Low-300

301-350

351-400

401-425

426-450

451-High

Score Categories

0

10

20

30

40

50

60

70

80

90

100


• Modifiable Health Potential Score is out of a possible 520 points for men or 505 points for women

• n = 3,937

• Paid expenditures tend to decrease as the Modifiable Health Potential Score increases

• Averages for the lowest Modifiable Health Potential Score categories are significantly higher than the averages for the highest Modifiable Potential Score categories (p<0.05)

$ %

HA Modifiable Health Potential Score and Paid Medical Care Costs


Paid Medical Care Costs for Those with HA-based Report of Heart Disease Compared to Those Who are at High-Risk for Heart Disease and Those Who are at Low-Risk for Heart Disease

Paid Amount by Disease or Risk Status

8,688

5,790

3,242

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

Heart Disease High-Risk Low-Risk

0

10

20

30

40

50

60

70

80

90

100


• n = 3,937• Average expenditures are

significantly different from each other (p<0.0001)

$ %


Paid Amount by BMI Category

3,856

3,1773,346

4,802

0

1000

2000

3000

4000

5000

6000

BMI < 18 BMI 18 to<25

BMI 25 to<30

BMI 30 andover

0

10

20

30

40

50

60

70

80

90

100


• n = 3,937

• Members with BMI between 18 and <25 are in the normal BMI range

• Average expenditures for those with BMI of 30 and over is significantly higher than all other categories (p<0.05) $ %

Paid Medical Care Costs Comparison by Body Mass Index Category


Paid Amount by Level of Physical Activity

5,170

3,698 3,6043,198

0

1000

2000

3000

4000

5000

6000

Sedentary Low PA ModeratePA

Very Active

0

10

20

30

40

50

60

70

80

90

100


• n = 3,937

• Average expenditures decrease with increasing levels of physical activity

• Average expenditures for those who are sedentary is significantly higher than all other categories (p<0.05)

$ %

Paid Medical Care Costs Comparison by Level of Physical Activity


Perceived Health Status - Poor or Other

8185

3349

7

93

0

2000

4000

6000

8000

10000

Yes No

0

20

40

60

80

100

Paid Dollars

% of Respondents

Physical Health Concerns

7915

3263

9

91

0

2000

4000

6000

8000

10000

Yes No

0

20

40

60

80

100

Paid Dollars

% of Respondents

Emotional Health Concerns

3960

3161

34

66

0

2000

4000

6000

8000

10000

Yes No

0

20

40

60

80

100

Paid Dollars

% of Respondents

For all graphs, comparison For all graphs, comparison groups are significantly groups are significantly different from each other:different from each other:Perceived health = p<0.0001Perceived health = p<0.0001Physical health = p<0.0001Physical health = p<0.0001Emotional health = p<0.001Emotional health = p<0.001

Paid Medical Care Costs comparison by Perceived Health Status (n=3,937)


For all graphs, comparison For all graphs, comparison groups are significantly groups are significantly different from each other:different from each other:All = p<0.0001All = p<0.0001

Paid Medical Care Costs comparison by Medication Use (n=3,937)

Use of Non-Prescription Medications

4247

3139

4951

0

1000

20003000

4000

5000

Yes No

0

20

4060

80

100

Paid Dollars

% of Respondents

Polypharmacy (7+ Medications)

7662

3469

5

95

0

2000

4000

6000

8000

10000

Yes No

0

20

40

60

80

100

Paid Dollars

% of Respondents

Use of Prescription Medications

4600

201665

35

0

1000

2000

3000

4000

5000

Yes No

0

20

40

60

80

100

Paid Dollars

% of Respondents


Do Incentives Drive Participation?


Review on Impact of Financial Incentives on Health Assessment Participation

0

1020

3040

50

6070

8090

100

0 50 100 150 200 250 300 350 400 460 510

Incentive Amount ($)

Par

tici

pat

ion R

ate

(%)

Source: Serxner, et al. The Art of Health Promotion Newsletter. 2004; March/April.

What Does the Literature Tell Us?


• Harvard Medical School, Department of Health Care Policy• HealthPartners, Center for Health Promotion and Research Foundation• Group Health Cooperative, Center for Health Studies• Kaiser Permanente, Denver• American Airlines, Dallas

The effect of intensity of recruitment effort on response disposition


20.126.4

51.8

67.7

0

10

20

30

40

50

60

70

80

IVR 1 IVR2 Tel Tel$

The effect of intensity of recruitment effort on response disposition

IVR interview with one or two mailings Telephone interview with no incentive or $20 incentive

Overall cumulative response rate was 26.4%

%

Source: Wang, et al. Medical Care, 2002;40:752-760

Results-HRA Response Disposition


• Data reflects:• Incentives/Marketing and

communication• 78 companies in 3rd/4th Q 2003• Total of 22,838 HA invitees

• 77.1% of the variance in HA completion is explained by type of incentive and marketing and communication

• Incentives• Low = e.g., merchandise awards,

drawing, small gift, etc.• Medium = $25 gift certificate, prize

drawings, etc.• Strong = e.g., mandatory, premium

reduction, co-pay reduction, etc.• Marketing and communication

• Low = e.g., very limited messaging, short timeline

• Medium = “soft” messaging, no strategic communication plan

• Strong = e.g., appropriate messaging, communication plan and timeline

Impact of Incentives and Marketing/ Communication on HA Completion

92

64.561.5

43.3

7.315.1

Trend R2 = 0.771

0102030405060708090

100

Stro

ng/S

trong

Stro

ng/M

ediu

m

Med

ium

/Stro

ng

Stro

ng/Low

Low/S

trong

Med

ium

/Med

ium

Low/L

ow

Perc

enta

ge c

om

ple

tion


• Modifiable health risk factors are associated with health care expenditures and productivity

• Health assessments (HA) can be used to measure modifiable health risks

• HA can be used to project associations between health risks and costs

• Incentives work

Conclusions


Nico Pronk, PhDVice President, Center for Health PromotionExecutive Leader, Health Behavior GroupResearch Investigator, HealthPartners Research Foundation HealthPartners, Inc.8100 34th Ave. S., MS21111HP.O. Box 1309Minneapolis, MN 55440-1309 Telephone: 952-967-6729 Fax: 952-967-6710 Email: [email protected]

Thank you

Contact Information

st. john’s, newfoundland, canada june 28-29, 2005

Documents

health costsimprovements

health care expenditures

health costs martinson

health risk profile

worksite health promotion

minnesotalooking backfocused

tolooking backfocused

value of prevention