CH 2. Outline l An economic model of utility, health, and medical care l Measuring health status l...

OutlineOutline

An economic model of utility, health, and medical care

Measuring health status Empirical evidence on health production Health care expenditures

A Basic Economic ModelA Basic Economic Model

Health as a consumer durable good: Utility = U (X, Health)

X represents “other goods and services” H is a stock -- every action will affect health On its own or combined with other goods and

services, the stock of H generates a flow of services that yield satisfaction=utility

A Basic Economic Model A Basic Economic Model (cont.)(cont.)

Medical care is not homogeneous and differs in: Structural quality (e.g. facilities and labor) Process quality (e.g. waiting time, case mgmt.) Outcome quality (e.g. patient satisfaction,

mortality)

Therefore medical services are often difficult to quantify

A Basic Economic Model A Basic Economic Model (cont.)(cont.)

Health=H(Profile, Medical Care, Lifestyle, Socioeconomic Status, Environment)

If an individual has a heart attack, then overall health decreases, regardless of the amount of medical care consumed The total product curve for medical care shifts

down

As a person ages, both health and the marginal product of medical care are likely to fall The total product curve shifts down and flattens

out

MEASURING HEALTHMEASURING HEALTH

Important for all health care managers today

Insurers and consumers are demanding

costs AND quality

HEALTH OVER THE LIFE CYCLEHEALTH OVER THE LIFE CYCLE

TIME

HEALTH

BIRTH

Hmin

Appendicitis

Auto Crash

Cancer (radiation therapy)

Cancer complications

Older people have a higher deprecation rate. That is why they have a higher health expenditure

HEALTH OVER THE LIFE CYCLEHEALTH OVER THE LIFE CYCLE

Individuals make choices about health (make tradeoffs) which maximize U over time

Relatively high value for the future• Low discount rate

e.g. Low-fat diet and exercise to avoid heart disease

Relatively low value for the future• High discount rate

e.g. Smoking, excess drinking, drug abuse

DISCOUNTINGDISCOUNTING

Required when costs are incurred in the future Why? Individuals have a positive value of time

preference

If r = 10%, then $100 invested today yields $110 next year

Spending $100 one year from now is “cheaper” than spending $100 today

CHOICES

Spend $100today

Invest $100 = $90.91 (1 + .10)

and

have $9.09 left over


If costs occur over multiple time periods, we must calculate the present discounted value (PDV) of these costs:

PDV = ΣT

t = 0

1(1 + r)t

COSTSt

• Example:

A project requires: $100 in year 1 $ 75 in year 2 $ 50 in year 3

PDV = $100 + $ + $ = $209.50 75(1 + .10)

50(1 + .10)2


If we discount costs, we must also discount benefits

Assume r = 10%

$990

Spend $990to save

1 year of lifetoday

Invest $900 tosave 1 year of life

next yearand

have $90 left tospend this year


Appropriate discount rate?

• The medical literature has settled on 5% for comparative reasons

Discounting is not an adjustment for inflation

COST

YOLS=

Σ

Σ COST

YOLS

1(1 + r)t

1(1 + r)t


Consider an intervention which costs $100 and saves 10 years of life Also assume r = 10%

Why we discount cost AND benefitsWhy we discount cost AND benefits

Option 1:Spend $100 today: = = 10

C

E

100

10

Option 2:Invest for 1 year → $110, saves 11 YOL. If we discount costs to present value, but don’t discount YOL:

CE =

10011 = 9

111

If we discount both costs and benefits:

CE

= = 10

110

111(1 + .10)

1(1 + .10)

Measure of health capital

Mortality Morbidity Quality of life

MORTALITYMORTALITY

Alive vs. Dead

Advantages:

Disadvantages:

MORTALITY MEASURESMORTALITY MEASURES1950 1970 1980 1990 2000

1. Crude death rate 963.8 945.3 878.3 863.8 873.6 (per 100,000)

2. Age-adjusted death rate 1446.0 1222.6 1039.1 938.7 869.0

3. Age-specific death rate

15-24 128.1 127.7 115.4 99.2 81.5

65-74 4067.7 3582.7 2994.9 2648.6 2432.9

4. Infant mortality 29.2 20.0 12.6 9.2 6.9

Neo-natal 20.5 15.1 8.5 5.8 4.6

Postneonatal 8.7 4.9 4.1 3.4 2.3

5. Life Expectancy 68.2 70.8 73.7 75.4 76.9(at birth)

MORTALITY MEASURESMORTALITY MEASURES

Life expectancy NOT a prediction of how long people live

76.9 is a summary of age-specific death rates in 2000

“If those born in 2000 experienced age-specific death rates prevailing in 2000, on average they would live to be 76.9

MORBIDITYMORBIDITY

The relative incidence of disease

Advantages: Captures quality of life

Disadvantages: Difficult to measure Difficult to aggregate when patient has >1

problem

MORBIDITYMORBIDITY

Acute disease e.g. appendicitis, pneumonia, gun shot wounds

Chronic disease e.g. arthritis, diabetes, asthma

Incidence occurrence of new cases in any particular year

Prevalence new and ongoing cases in any particular year

Heart disease is more prevalent, but its incidence is declining

MEASURING MORBIDITYMEASURING MORBIDITY

Distinguish between symptom and disease e.g. high blood pressure vs. stroke

Disabilities are also a sign of morbidity

Subjective measures - i.e. self-rated health

“Is your health excellent/good/fair/poor?” Problem: 1970-80, # of people with high blood pressure

declined. But % of people reporting restricted activity due to HTN doubled!

Depends on what you want to do - e.g. astronaut, airline pilot, or professor?

MEASURING MORBIDITYMEASURING MORBIDITY

How far do we go in classifying “medical” problems?

e.g. cosmetic surgery

Beware of phrases in contracts or policy statements such as “providing all medical care” or “basic needs”

LEADING CAUSES AND NUMBER OF LEADING CAUSES AND NUMBER OF DEATHS, PERSONS AGED 15-24 (2000)DEATHS, PERSONS AGED 15-24 (2000)

CAUSE OF DEATH DEATHS

Unintential injuries 14,113

Homicide 4,939

Suicide 3,994

TOTAL “Violent Deaths” 23,046 85%

Cancer 1,713

Heart Disease 1,031

Congenital anomalies 441

All other nonviolent causes 757

TOTAL “Nonviolent Deaths” 3,942 15%

LEADING CAUSES AND NUMBER OF LEADING CAUSES AND NUMBER OF DEATHS, PERSONS AGED 65+ (2000)DEATHS, PERSONS AGED 65+ (2000)

CAUSE OF DEATH DEATHS

Heart disease 593,707

Cancer 392,366

Cerebrovascular Disease 148,045(Stroke)

Chronic Lower Respiratory Disease 106,375

Pneumonia and Influenza 58,557

Diabetes mellitus 52,414

Alzheimer’s disease 48,993

Kidney disease 31,225

Unintentional Injuries 31,050

Empirical Evidence on Health Prod’nEmpirical Evidence on Health Prod’n

Hadley (1982) a 10% ↑ in medical care $ per capita →↓mortality rate by only 1.5%

Auster et al. (1969) 10% ↑ in medical services →↓age-adjusted mortality rate by 1%

Enthoven (1980) “flat-of-the-curve” medicine

LIFESTYLELIFESTYLE cigarette smoking 10% → mortality:

blacks whites

men 45-64 2.3% 1.4%

women 45-64 1.1% 1.1%(Hadley, 1982)

A one-pack-a-day smoker incurs 10.9 more sick days every six months than a comparable non-smoker

(Leigh and Fries, 1992)

Not smoking, regular exercise, moderate/no use of alcohol, 7-8 hours of sleep per day, proper weight, eating breakfast, and no snacking leads to 28% lower mortality for men, 43% lower for women

(Breslow and Enstrom, 1980)

OTHER FACTORS AFFECTING HEALTHOTHER FACTORS AFFECTING HEALTH

EducationOne more year of schooling →↓prob of

dying w/in 10 years by 3.6% (Lleras-Muney 2001)

IncomePeople w/o high school educ & income

<$10k were 2-3 x’s more likely to have functional limitations and poorer self-rated health

Sturm, Health Affairs 2002

OTHER FACTORS AFFECTING HEALTHOTHER FACTORS AFFECTING HEALTH

Determinants of Infant HealthDeterminants of Infant Health

Whites Blacks1964 16.2 27.61977 8.7 16.1

Neonatal Mortality per 1000 Live Births

Corman and Grossman, 1985


Corman and Grossman, 1985

Selected Regression Results,

Neonatal Mortality RatesWhites Blacks

% HS Educated -0.037 -0.056

Newborn Intensive Care Hospitals/1000

-44.196 -86.196

Abortion Providers/1000 -3.198 -16.838


Does more schooling and the availability of more providers improve infant health?

Is the marginal productivity of more providers greater for blacks or whites?


Why might the marginal productivities for blacks and whites differ?The regressions have poor controls for

income,health status, preferences, etc. which may be correlated with schooling and the availability of providers

If the marginal productivity for most factors is greater for blacks then whites, why isn’t the overall neonatal mortality rate lower for blacks than whites?

Marginal Productivity of Provider Marginal Productivity of Provider Services for Infant HealthServices for Infant Health

(1-mortality rate)%

Medical Care

Blacks

Whites

Marginal Productivity of Provider Marginal Productivity of Provider Services for Infant Health Services for Infant Health (cont.)(cont.)

For any given level of provider services, marginal productivity may be higher for blacks than whites

However, the level of services may be higher for whites than blacks

Knowing the shape of the total product curve is not enough. You must also know where you are on it

Health in the 50 StatesHealth in the 50 States

One measure of health status in the population in the # of deaths (per 100,000 residents) from heart disease

Suppose we have data on deaths from heart disease and other population characteristics by state See Excel Spreadsheet

What factors might explain death from HD? Why?


150

200

250

300

# o

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m h

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dis

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.1 .15 .2 .25 .3Fraction of residents who smoke


150

200

250

300

# o

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dis

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.5 .55 .6 .65Fraction of residents overweight or obese


150

200

250

300

# o

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dis

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.05 .1 .15 .2 .25Fraction who are binge drinkers


150

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250

300

# o

f de

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fro

m h

eart

dis

ease

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r 1

00,0

00

35000 40000 45000 50000 55000 60000Median household income


150

200

250

300

# o

f de

aths

fro

m h

eart

dis

ease

pe

r 1

00,0

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.5 .6 .7 .8 .9Fraction who graduated form high school


Which of the previous variables would you include in the multivariate regression for the determinants of death from heart disease? Smoking? Overweight/Obese? Binge Drinking? Household Income? High School Graduation Rate?


Which of the variables are statistically significant at the 95% confidence level?

Suppose the fraction of residents who are obese/overweight were reduced by 0.10. How much would death rates from heart disease

fall?

Suppose that you could obtain data on a different variable that may explain heart disease death rates, but isn’t in this data set. What would it be?

ConclusionsConclusions

In an economic model, medical care and other goods and services are combined to produce health, which yields utility to the consumer

The production of health can be measured in a variety of ways

Both higher health care expenditures and other factors are improving health status over time

CH 2. Outline l An economic model of utility, health, and medical care l Measuring health status l...

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