Chapter 6: Demand for Health and Medical Care

Production of Health

Health Production Function

• Health production is a derived demand for medical care (Grossman, 1972).

• Net investment in health of individual j:

  

  • where $H$ = Level of health

  • $I$ = Investment in health,

  • $\delta_{jt}$ = Rate of Depreciation.

• Medical care and other inputs contribute to good health.

• Gross investment in health during period t:

  

  • I = Investment in health

  • $M_{jt}$ = Medical care services,

  • $T_{jt}$ = Time spent improving health,

  • $C_{jt}$ = Human capital stock,

  • $A_{jt}$ = Age,

  • $B_{jt}$ = Behavior (lifestyle).

Health-Status and Medical Care Spending

• Hypothesized relationship yields a positively sloping function.

  • Health status increases with medical care spending

• However, the function displays diminishing returns.

• Increasing medical care spending moves along function.

• Change in other inputs causes the total product curve to shift.

• After level Q* of spending, the production function has a negative slope.

  • Medical care spending beyond this point yields net harm to patient.

Determinants of Health (Overview)

Deteminants of Health (1 of 5) – Factors Other Than Medical Care

• 1. Income and Education:

  • Higher socioeconomic status often indicates better access to medical care and better health outcomes.

  • Low socioeconomic status does not automatically imply poor health.

    • Nutrition, housing, environment, and other factors play direct roles.

  • Empirically:

    • Low-income Americans experience higher mortality (Pappas et al., 1993).

    • Education is associated with better longevity and life expectancy (Guralnik et al., 1993).

    • Higher education increases production efficiency of health (Grossman, 1972).

Determinants of Health (2 of 5)

2. Environment and Lifestyle:

• Environmental pollution has a strong negative effect on human life and the quality of life.

• Estimated 65 percent of all cancer in the United States associated with lifestyle and environmental factors (American Cancer Society).

• Correlation exists between exposure to environmental toxins and illness in children (Note: correlation does not imply causation).

• Personal behavior also strongly affects health, including:

  • Diet, exercise, sexual behavior, smoking, substance abuse, violence.

Determinants of Health (3 of 5)

3. Genetics

• There is a risk of exposure to a disease (public health) as well as the ability to resist and recover from the disease (genetics)

• Hereditary factor in predisposition to certain diseases

  • e.g., women with family history of ovarian cancer places them at a 40 percent risk of developing the disease, whereas the general population faces a risk of only 7 percent.

  • Strong family predisposition a significant factor in allergies, hypertension, obesity, cystic fibrosis, sickle cell anemia, and snoring.

Determinants of Health (4 of 5)

Public Health

• The state provides services important to health, such as:

  • Water purification, sewage treatment, immunization programs, quarantines, clean air standards, food safety.

• McKeown (1976) attributed historical decline of mortality in North America and Europe to four major sources in order of significance:

  • Living standards, public health intervention, disease decline, and advancements in medical science.

Deteminants of Health (5 of 5)

Beginnings of Public Health

• London cholera pandemic (1846–1860):

  • Two outbreaks, ~250,000 cases and ~75,000 deaths.

• John Snow (obstetrician) identified water as the source:

  • Waterborne disease, not airborne .

  • Used mapping to determine the exact location of the water source:

Measures of Health (1 of 3)

Quantifiable measures of health are important, but those existing are limited

1. Mortality Rates

   • Defined as number of deaths per 100,000.

   • Often reduced to subgroups of age, sex, and race for comparison.

   • Male and female life expectancies at birth and infant mortality other common indicators.

   • Overall poor indicator of quality of life.

   • Low crude mortality rate does not always reflect a healthy population.

Measures of Health (2 of 5) – Table: Common Causes of Death (Rate per 100,000)

Measures of Health (3 of 5)

2. Morbidity Rates

   • Prevalence of certain diseases or medical conditions

     • Common measures include restricted activity days due to illness, the incidence rate of certain chronic conditions, and a self-assessment of health status.

   • Newhouse and Friedlander (1980) used six measures to analyze the health status of a region in relation to the medical services available:

     • Diastolic blood pressure, serum cholesterol concentration, and electrocardiogram abnormalities (reflect cardiovascular disease).

     • Abnormal chest X-rays (cancer), varicose veins (condition of connective tissue), and periodontal index (preventive-care practices)

Measures of Health (4 of 5) – Workdays Lost and Activity Impairments

Measures of Health (5 of 5)

3. Quality of Life Metrics

• Quality-adjusted life years (QALY):

  • Index combining quality of life and survival duration

  • Can be used to set allocation priorities within a program (e.g., waitlist for a kidney).

• Disability-adjusted life expectancy (DALE):

  • Measures time spent living with a health condition considered less than optimal, plus time lost due to premature death.

  • More simply, the number of years living in poor health or lost to illness or injury.

  • Commonly used in cross-country comparisons.

Demand Factors (1 of 5) – Demand for Medical Care as Investment

• Medical care is an investment in human capital.

• Function for medical care demand:

  

  • $H_{jt}$ = health stock,

  • $D_{jt}$ = demographic characteristics,

  • $E_{jt}$ = socioeconomic standing,

  • $P_t$ = physician factors.

• Demand for medical care is derived from the demand for health.

• Affected by factors related to both patients and physicians.

Demand Factors (2 of 5) – Patient Factors

• Health stock

  • Seek medical care to prevent disease or in response to an illness or injury.

• Demographic characteristics

  • Demand varies according to population growth and age, between sexes.

• Economic standing

  • Better access, better consumers, insurance coverage

Demand Factors (3 of 5) – Effect of Insurance on Demand

• Insurance changes patient price exposure and can increase demand due to lower out-of-pocket costs; creates moral hazard.

• Insurance design (deductibles, copayments) and coverage levels influence the quantity and type of care sought.

Demand Factors (4 of 5) – Provider-Induced Demand

• Physician as agent: physicians largely determine medical spending.

• Demand creation concept: Roemer’s Law – a built bed is a filled bed.

• Third-party insurance introduces moral hazard affecting both patients and providers.

• Myth: Increasing capacity automatically expands sales without bound; reality: evidence shows hospital capacity is often underutilized, limiting unconditional capacity-driven demand.

Demand Factors (5 of 5) – Demand Inducement Related to Increased Supply

• Increases in supply can induce higher demand, through mechanisms such as advertising, technology diffusion, and physician practice patterns.

Measuring Demand (1 of 4) – Basic Relationships and Elasticities

• Relationship between demand for medical care and out-of-pocket payments varies by:

  • Insurance status (insured vs uninsured),

  • Deductibles and copayments among insured individuals.

• Key determinants of demand include:

  • Price, income, insurance coverage, time cost.

• Demand is typically estimated via regression analysis.

• Elasticities studied:

  • Price elasticity, income elasticity, insurance elasticity, time-cost elasticity, cross-price elasticity.

• General finding: demand for medical care is relatively inelastic with respect to price.

Measuring Demand (2 of 4) – Elasticities (Selected Studies)

• Table: Price and Income Elasticities (selected studies)

• Davis and Russell (1972):

  • Dependent variable: Outpatient visits; Elasticity: price ≈ −1.00

  • Hospital admissions: price ≈ −0.32 to −0.46

• Rosett and Huang (1973):

  • Hospital and physician spending: price ≈ −0.35 to −1.50

• Newhouse and Phelps (1976):

  • Hospital length of stay: price ≈ −0.06 to −0.29

  • Physicians’ office visits: price ≈ −0.08 to −0.10

• Manning et al. (1987):

  • Overall spending: price ≈ −0.22

  • Hospital care: −0.14

  • Preventive care: −0.43

• Wedig (1988):

  • Level of care: price ≈ −0.16 to −0.23

• Eichner (1998):

  • Medical care: price ≈ −0.62 to −0.75

• Contoyannis et al. (2005):

  • Pharmaceuticals: price ≈ −0.12 to −0.165

• Income elasticities (selected studies):

  • Newhouse (1977): Per capita medical spending: 1.15 to 1.31

  • Parkin, McGuire, and Yule (1987): Per capita medical spending: 0.80 to 1.57

  • Gerdtham and Jönsson (1991): Per capita medical spending: 1.24 to 1.43

  • Moore, Newman, and Fheili (1992): Short-run per capita spending: 0.31 to 0.86; Long-run per capita spending: 1.12 to 3.22

  • Murray, Govindaraj, and Musgrove (1994): Total health expenditures: 1.43

  • Manning and Marquis (1996): Medical expenditures: 0.22

  • Fogel (1999): Health care expenditures: 1.60

  • Okunade and Murthy (2002): Per capita real health care spending: 1.29 to 1.64

  • Herwartz and Theilen (2003): Growth rate per capita health spending: 0.74

  • Dormont et al. (2010): Per capita health spending: 0.75 to 1.59

  • Acemoglu et al. (2013): Per capita health spending: 0.72 to 1.13

Measuring Demand (3 of 4) – RAND Experiment (1971–1982)

• Design:

  • Randomly assigned ~2,000 non-elderly families to insurance plans with two characteristics:

  • Coinsurance rate: 0–95%

  • Deductible: 5, 10, or 15% of annual income

  • Annual spending cap: $1,000

• Measured outcomes:

  • Health spending and health outcomes.

Measuring Demand (4 of 4) – RAND Conclusions

• Demand for medical care appears relatively price-inelastic:

  • Overall price elasticity ≈ −0.2

  • Hospital care elasticity ≈ −0.15

  • Preventive care elasticity ≈ −0.4

• Income elasticities (individual): approximately +0.22, suggesting medical care is a normal good and may be a necessity.

• Aggregate income elasticities tend to be higher, indicating medical care may be a superior good (some would call it a luxury) at the population level.

Additional Notes: Practical and Ethical Implications

• Moral hazard in insurance: insurance coverage can increase utilization beyond the amount chosen by patients, creating cost pressures on payers and potential overuse concerns.

• Provider-induced demand: physicians’ practice patterns and incentives can drive utilization; policy implications include capacity management and payment reform to align incentives.

• Public health investments: historical evidence emphasizes living standards and public health interventions as major contributors to mortality declines, sometimes more than medical care innovations alone.

• Measurement limitations: many health outcomes (quality of life, DALE, QALY) require careful interpretation, cross-country comparability, and may reflect value judgments about quality and duration of life.

• Ethical considerations in allocation: QALYs and DALEs influence resource allocation decisions; trade-offs between extending life, preserving quality of life, and equity across populations must be considered.