Health, Medical Care, and Medical Spending

1. Health, Medical Care, andMedical Spending Health EconomicsProfessor Vivian HoFall 2009 These slides summarize material in Santerre & Neun: Health Economics, Theories Insights and Industry Studies, Southwestern Cengate 2010

2. Can we apply the tools of managerial economics to health care?

3. Outline • An economic model of utility, health, and medical care • Measuring health status • Empirical evidence on health production • Health care expenditures

4. A 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

5. A Basic Economic Model (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

6. A Basic Economic Model (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

7. MEASURING HEALTH • Important for all health care managers today • Insurers and consumers are demanding  costs AND  quality

8. HEALTH OVER THE LIFE CYCLE HEALTH Appendicitis Auto Crash Cancer (radiation therapy) Cancer complications Hmin TIME BIRTH

9. HEALTH 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

10. DISCOUNTING • 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

11. DISCOUNTING CHOICES Invest $100 = $90.91 (1 + .10) and have $9.09 left over Spend $100 today

13. DISCOUNTING • If costs occur over multiple time periods, we must calculate the present discounted value (PDV) of these costs: T Σ 1 (1 + r)t PDV = COSTSt t = 0 • Example: • A project requires: $100 in year 1 • $ 75 in year 2 • $ 50 in year 3 75 (1 + .10) 50 (1 + .10)2 PDV = $100 + $ + $ = $209.50

14. DISCOUNTING • If we discount costs, we must also discount benefits Assume r = 10% $990 Invest $900 to save 1 year of life next year and have $90 left to spend this year Spend $990 to save 1 year of life today

15. DISCOUNTING • Appropriate discount rate? • The medical literature has settled on 5% for • comparative reasons • Discounting is not an adjustment for inflation 1 (1 + r)t COST Σ COST YOLS = 1 (1 + r)t Σ YOLS

16. Why we discount cost AND benefits • Consider an intervention which costs $100 and saves 10 years of life • Also assume r = 10% 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: C E 100 11 1 11 = = 9 • If we discount both costs and benefits: 1 (1 + .10) 110 C E = = 10 1 (1 + .10) 11

17. MORTALITY • Alive vs. Dead • Advantages: • Disadvantages:

18. MORTALITY MEASURES 19501970198019902000 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)

19. MORTALITY 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

20. MORBIDITY • The relative incidence of disease • Advantages: • Captures quality of life • Disadvantages: • Difficult to measure • Difficult to aggregate when patient has >1 problem

21. MORBIDITY • 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

22. MEASURING 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?

23. MEASURING 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”

24. LEADING CAUSES AND NUMBER OF 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%

25. LEADING CAUSES AND NUMBER OF 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

26. Empirical 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

27. LIFESTYLE •  cigarette smoking 10% → mortality: blackswhites 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)

28. OTHER FACTORS AFFECTING HEALTH • Education • One more year of schooling →↓prob of dying w/in 10 years by 3.6% (Lleras-Muney 2001) • Income • People w/o high school educ & income <$10k were 2-3 x’s more likely to have functional limitations and poorer self-rated health

29. OTHER FACTORS AFFECTING HEALTH Sturm, Health Affairs 2002

30. Determinants of Infant Health Corman and Grossman, 1985

31. Determinants of Infant Health Corman and Grossman, 1985

32. Determinants of Infant Health • Does more schooling and the availability of more providers improve infant health? • Is the marginal productivity of more providers greater for blacks or whites?

33. Determinants of Infant Health • 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?

34. Marginal Productivity of Provider Services for Infant Health (1-mortality rate)% Blacks Whites Medical Care

35. Marginal Productivity of Provider Services for Infant Health (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

36. Health 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?

37. Health in the 50 States

38. Health in the 50 States

39. Health in the 50 States

40. Health in the 50 States

41. Health in the 50 States

42. Health in the 50 States • 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?

43. Health in the 50 States • 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?

44. Conclusions • 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