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date: 25 February 2020

(p. x) List of Figures

(p. x) List of Figures

  1. 2.1 Health care sector share of total health care spending in the medianOECD country, 1970–2005 14

  2. 2.2 Decomposition of average annual growth in health spending intogrowth in GDP, aging, and excess in OECD countries, 1970–2005 17

  3. 3.1 The health system 34

  4. 3.2 Out-of-pocket share of total health expenditure in relation to GDPper capita 36

  5. 3.3 Median coverage levels for priority maternal, neonatal, and childhealth interventions (68 priority countries) 41

  6. 3.4 Use of public and private services 42

  7. 3.5 Volatility of external funding 51

  8. 3.6 External funding for maternal and neonatal health in relation to need 53

  9. 4.1 Government health expenditures as a share of all healthexpenditures and as a share of all government outlays, 2005 62

  10. 5.1 Life expectancy per capital GDP (US dollars) 84

  11. 6.1 Illustration of the productivity of health capital 100

  12. 6.2 Illustration of the demand for health capital 105

  13. 6.3 Illustration of the effect of age on the demanded amountof health capital 106

  14. 6.4 Illustration of the effect of a wage rate increase 107

  15. 6.5 Illustration of the effect of an increase in educational capitalon the demanded amount of health capital 108

  16. 7.1 Education and mortality among adults over 40, US and Europe 125

  17. 7.2a Education and mortality, US adults over 25 128

  18. 7.2b Education and self-reported health, US adults over 25 129

  19. 7.3a Income and mortality, US adults over 25 130

  20. 7.3b Income and self-reported health, US adults over 25 131

  21. 7.4 Occupation and mortality, US adults ages 25–65 132

  22. 7.5a Race and mortality, US adults over 25 133

  23. (p. xi) 7.5b Race and self-reported health, US adults over 25 134

  24. 11.1 Managed care rationing by shadow prices 247

  25. 11.2 Budgets and incentives for public mental health services 249

  26. 13.1 Optimal wealth levels depending on the state of health 287

  27. 14.1 Cost growth in OECD countries 309

  28. 14.2 Total health expenditures as a share of gross domesticproduct, 1960–2004 310

  29. 15.1 Optimality of user charges as a revenue-raising device 337

  30. 17.1 Three modalities of organizing the payment flows of a subsidy system 396

  31. 18.1 Characteristics of 4 stereotypical types of health insurance plans 414

  32. 21.1 Quotients of urban nurse-to-population ratios divided by ruralnurse-to-population ratios 493

  33. 21.2 Quotients of urban physician-to-population ratios dividedby rural physician-to-population ratios 494

  34. 21.3 Estimates of health worker emigration rates in sub-SaharanAfrican countries, 2004 509

  35. 24.1 Projected changes in employment (% change of employed peopleaged 15–64 between 2003 and 2050), EU 25 582

  36. 24.2 Changes in the targeting of community care services for olderpeople by sector of provision, 1993–2008 584

  37. 25.1 Physician preferences and choice of treatment in mixedpayment systems 614

  38. 26.1a Panel A—marginal revenue (MR), marginal cost (MC) of quantity 631

  39. 26.1b Panel B—marginal revenue (MR), marginal cost (MC) of quality 631

  40. 29.1 Production frontier: data envelopment analysis 697

  41. 29.2 Production frontier: stochastic frontier analysis 698

  42. 31.1 Assessing the cost-effectiveness of an intervention givenan objective of maximizing health subject to a fixed budget 737

  43. 31.2 The incremental cost-effectiveness plane 750

  44. 31.3 Top right quadrant of the cost-effectiveness plane for options Z, W, and Y as defined in Tables 31.1 and 31.2 752

  45. 32.1 Incremental cost-effectiveness plane 779

  46. 32.2 Cost-effectiveness acceptability curves for three mutuallyexclusive interventions 780

  47. 32.3 Cost-effectiveness acceptability frontier and populationEVPI for three mutually exclusive alternatives 780

  48. (p. xii) 33.1 Standard gamble for a chronic health state valued as betterthan dead 791

  49. 33.2 Time trade-off for a chronic health state valued as betterthan dead 792

  50. 33.3 Visual analog scale 793

  51. 33.4 Observed and predicted EQ-5D scores using a variety of modelsmapping the SF-36 and SF-12 onto EQ-5D 798

  52. 33.5 Time trade-off for a chronic health state valued as worse than dead 801

  53. 33.6 Predicted EQ-5D health state utility values using the standardand episodic RUM model 803

  54. 33.7 “Lead time” time trade-off for a health state valued as better than dead 804

  55. 33.8 “Lead time” time trade-off for a health state valued as worse than dead 804

  56. 34.1 The determinants of ill health 817

  57. 34.2 Equality, efficiency, and trade-offs 824

  58. 34.3 A more general health frontier 825

  59. 35.1 Two hypothetical concentration curves 840

  60. 35.2 Horizontal inequity indices for probability of a specialist visit, by country (with 95% confidence interval) 854

  61. 35.3 Decomposition of inequity in the probability of a specialist visit (excluding need contributions) 855

  62. 35.4 Short-run (SR) versus long-run (LR) “conservative” inequityfor number of GP visits, by country 857

  63. 35.5 Short-run (SR) versus long-run (LR) “conservative” inequityfor number of specialist visits, by country 858

  64. 36.1 Health spending by age group, US, 2004 871

  65. 36.2 Distribution of spending by age in Canada 874

  66. 36.3 Ratio of elderly to non-elderly health spending, Japan 875

  67. 36.4 Distribution of US health spending by age group 875

  68. 36.5 Net benefits from Medicare, by cohort 886

  69. 37.1 A simple example of potential outcomes 895

  70. 38.1 Williams' plumbing diagram 928