Chronic Disease and Health Care Spending Among the Elderly
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1 Chronic Disease and Health Care Spending Among the Elderly Jay Bhattacharya, MD, PhD for Dana Goldman and the RAND group on medical care expenditure forecasting
2 Chronic Disease Plays an Increasingly Important Role in Determining Medicare Spending In the U.S., Medicare pays for the health care of the elderly and disabled. A substantial portion of Medicare expenditures goes to treating chronic disease (like diabetes, hypertension, and arthritis). The U.S. population is aging. Highest obesity prevalence in the world. We need to know how chronic disease will affect future Medicare financing. A6654C-2 5/06
3 Objective Build a tool to predict the impact of medical innovation and demography on future Medicare expenditures Emphasize macro-level effects on: Disease Functional status (disability) Expenditures Can be used for public policy purposes and resource allocation decisions A6654C-3 5/06
4 Our Approach Build demographic-economic model Simulate blue sky scenarios Simulate demographic trends A6654C-4 5/06
5 Our Model Tracks Individuals Over Time New 65 year-olds in 2006 New 65 year-olds in ,000 Medicare beneficiaries (age 65+) in 2005 Survivors Health & functional status, 2006 Survivors Health & functional status 2007 Survivors Etc. Deceased Deceased Deceased 2005 costs 2006 costs 2007 costs A6654C-5 5/06
6 Health & Functional Outcomes Conditions (1) Hypertension Diabetes Heart disease Lung disease Alzheimer s Arthritis Cancer Stroke Functional state (2) Risk Factors (3) (1) Based on self-report; conditions are permanent ( ever had ) (2) Mutually exclusive (3) Do not vary over time A6654C-6 5/06
7 Health & Functional Outcomes Conditions (1) Hypertension Diabetes Heart disease Lung disease Alzheimer s Arthritis Cancer Stroke Functional state (2) 1+ ADLs 3+ ADLs Nursing home Dead Risk Factors (3) (1) Based on self-report; conditions are permanent ( ever had ) (2) Mutually exclusive (3) Do not vary over time A6654C-7 5/06
8 Health & Functional Outcomes Conditions (1) Hypertension Diabetes Heart disease Lung disease Alzheimer s Arthritis Cancer Stroke Functional state (2) 1+ ADLs 3+ ADLs Nursing home Dead Risk Factors (3) Obese Underweight Ever smoked Age Gender Education Race Ethnicity (1) Based on self-report; conditions are permanent ( ever had ) (2) Mutually exclusive (3) Do not vary over time A6654C-8 5/06
9 Relative Risks of Health Conditions, Selected Risk Factors Percent Increase in Probability of Reporting Condition One Year Later: Risk Factor Heart Stroke Alzheim. Hypert. Diabet. Cancer Lung Arthritis Heart disease 30 Hypertension Diabetes Ever smoked Underweight Obese Male African-Amer Hispanic Less than HS College grad A6654C-9 5/06
10 Relative Risks of Disability, Selected Risk Factors % Increase in 1-Year Prob. of: Risk Factor ADL1+ ADL3+ Nurs Home Cancer Heart disease Stroke Alzheimer s Hypertension Diabetes Lung Arthritis ADL>=1 150 ADL>=3 60 Ever smoked Under Weight Obese Male African-Amer Hispanic Less than HS College graduate A6654C-10 5/06
11 % of +65 population Predicted Prevalence of Disease in the Medicare Population Year Heart Diabetes Lung Stroke A6654C-11 5/06
12 Log-hazard of Mortality for Men with Selected Functional Limitations -2 Log-hazard ADLs 1+ ADLs No Limitations age A6654C-12 5/06
13 Our Approach to Estimating Costs New 65 year-olds in 2006 New 65 year-olds in ,000 Medicare beneficiaries (age 65+) in 2005 Survivors Health & functional status, 2006 Survivors Health & functional status 2007 Survivors Etc. Deceased Deceased Deceased 2005 costs 2006 costs 2007 costs A6654C-13 5/06
14 Our Approach to Estimating Costs Predict expenditures as a function of: Risk factors Conditions Functional status Interactions among disease and disability Assume a status quo level of medical technology Corresponds to 1990 s medicine Use Medicare Current Beneficiary Survey A6654C-14 5/06
15 Costs are a Function of Disease and Functional Status Self-Reported ADLs Condition Nursing Home Cancer $4,491 $7,284 $14,025 $13,800 Heart 4,670 7,501 14,055 12,355 Alzheimer s 4,111 5,905 11,681 8,765 Stroke 4,776 7,830 15,434 11,942 Diabetes 4,290 8,143 15,992 16,430 Hypertension 3,457 6,256 13,200 12,773 Lung 4,247 8,079 15,033 15,343 Arthritis 3,143 5,726 11,899 11,429 A6654C-15 5/06
16 Our Approach Build demographic-economic model Simulate blue sky scenarios Simulate demographic trends A6654C-16 5/06
17 Scenario 1: Prevention of Heart Disease (for non-elderly) Scenario: U.S. prevents heart disease until a person reaches 65 years of age New pill or best practices for statins, antihypertensives, anti-diabetes drugs, etc. Assume cuts risks to zero for non-elderly Method: Recode to zero the heart disease variable for all entering 65 year olds Key Assumption: underlying risks for other diseases unchanged by intervention A6654C-17 5/06
18 Heart Disease Prevention: Effect on Elderly Heart Disease Prevalence of Heart Disease Among the Elderly (%) Intervene among non-elderly in % % A6654C-18 5/06
19 Heart Disease Prevention: Effect on Medicare Expenditures 350 $331 B Medicare Spending, Billions ($ 1998) Saves Medicare $356 billion over 28 years $314 B Year A6654C-19 5/06
20 Scenario 2: Obesity Prevention Scenario: U.S. prevents obesity until a person reaches 65 years of age Riskless and costless pill available to all non-elderly Method: Adjust the incoming BMI for all cohorts entering Medicare A6654C-20 5/06
21 Obesity Prevention: Effects on Heart Disease 42 % with heart disease Status Quo Prevention Year A6654C-21 5/06
22 Obesity Prevention: Effects on Diabetes 20 % with diabetes Status Quo Prevention Year A6654C-22 5/06
23 Obesity Prevention: Effects on Disability Prevalence 72 % without disability Prevention Status Quo Year A6654C-23 5/06
24 Obesity Prevention: Effects on Medicare Spending Medicare Spending ($1998 billion) Saves Medicare $10 billion annually Year Status Quo Prevention A6654C-24 5/06
25 Our Approach Build demographic-economic model Simulate blue sky scenarios Simulate demographic trends A6654C-25 5/06
26 Concern About Demographic Trends Much attention to recent disability declines Accelerated in late 1980s and 1990s Attributed to advances in assistive technologies. Affects Medicare solvency But what about the young? Rising obesity, diabetes, asthma A6654C-26 5/06
27 Disability Rose Among the Young, Declined Among the Elderly (1990 to 1996) Percentage Change in Disability Rate Growth Rate 95% upper 95% lower Age A6654C-27 5/06
28 Disability Falls Among ALL Elderly Until 2015, then Rises Again 20.0% 17.5% 15.0% 12.5% 10.0% A6654C-28 5/06
29 Per Capita Cost Depends on Projected Disability Trends $475 $450 No change Monthly Medicare Costs ($1998) $425 $400 $ A6654C-29 5/06
30 One Prominent Model Predicts Large Decreases in Per Capita Costs $475 $450 No change Monthly Medicare Costs ($1998) $425 $400 Manton $ A6654C-30 5/06
31 Our Model Predicts Increases After 2015 $475 Monthly Medicare Costs ($1998) $450 $425 $400 $ No change Our model Manton A6654C-31 5/06
32 The Bottom Line Even low cost and dramatic technological improvements in care will not reduce forecasted Medicare costs. Increased survival is expensive. Death from other diseases is expensive. Demographic trends (such as changes in disability) will place further burdens on Medicare financing. A6654C-32 5/06
33 Policy Ruminations Do: Increase investments in effective techniques to prevent chronic disease. Weight reduction; screening for hypertension. Increased quality of life would be worth it, even if Medicare costs do not fall very much as a result. Don t: Depend upon a technological fix Technology is as likely to increase costs as decrease them (though that too may be worth it). Do: Prepare government financing systems for the deluge. A6654C-33 5/06
34 A6654C-34 5/06
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