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NERI Seminar - The Fiscal Implications of Demographic Change in the Health Sector

Slides from The Fiscal Implications of Demographic Change in the Health Sector presented by Paul Goldrick-Kelly

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NERI Seminar - The Fiscal Implications of Demographic Change in the Health Sector

  1. 1. The Fiscal Implications of Demographic Change in the Health Sector Paul Goldrick-Kelly NERI (Nevin Economic Research Institute) Dublin PaulGK@NERInstitute.net www.NERInstitute.net
  2. 2. Outline • Introduction • Data • Model Components – Demographic Cost Drivers – Income and Residual Cost Drivers • Projection Model • Assumptions • Results • Conclusions
  3. 3. Introduction • Context – Substantial increases over two decades preceding crisis of 2008 from low base (Wren,2004). – Fiscal retrenchment results in reduction in spending after crash. Expenditure plans of previous government imply restrained spending growth. – Demographic change proceeds apace, population (still) expanding and ageing. This has associated costs.
  4. 4. Figure 1: Real Current Public Health Expenditure Per Capita 2000- 2013 SHA(2011) (pg. 4) 0 500 1000 1500 2000 2500 3000 3500 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 RealCurrentPublicExpenditurePer capitaatConstant2013€Prices Source: CSO (2015) Ireland’s System of Health Accounts, Annual Results 2013 (Preliminary)
  5. 5. Current Health Expenditure as a Percentage of GDP 2013 SHA(2011) (EU15 Members denoted by *) 0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 12.00% CurrentHealthExpenditureasa%ofGDP Current Public Expenditure Other Current Expenditure Source: Eurostat, CSO (2015) Ireland’s System of Health Accounts, Annual Results 2013 (Preliminary),Author’s Calculations
  6. 6. • This working paper aims to: – Quantify the costs associated with demographic change on overall current public health expenditure using a simple model. – Produce projections of public health spending to 2035. – Briefly highlight likely compositional changes to health spending induced by an ageing and expanding population.
  7. 7. Data • Data Sources include: – CSO (2013) Population Projections M1F1 and M2F2 with attendant life expectancy and mortality rate projections by year cohort. – EU-15 Average Age and Gender Specific costs (EU AWG, 2012).  Irish data unavailable – NERI (2015) and OECD (2013) estimates of GDP growth. – SHA (2011) estimates of Current Public Health Expenditure (CSO, 2015).
  8. 8. Figure 2: Age and Gender Specific Average per Capita Current Public Expenditure EU-15 2013 Adjusted (pg.6)Under1year 3years 6years 9years 12years 15years 18years 21years 24years 27years 30years 33years 36years 39years 42years 45years 48years 51years 54years 57years 60years 63years 66years 69years 72years 75years 78years 81years 84years 87years 90years 93years 96years 99yearsandover €0.00 €2,000.00 €4,000.00 €6,000.00 €8,000.00 €10,000.00 €12,000.00 Male Female Source: EU Commission 2012 Ageing Report
  9. 9. Model Components • Demographic Component – Age Composition - Literature indicates not very important (Zweifel et al.,1999; Anderson and Hussey, 2002). – Death Related Costs – More significant predictor of health costs, proximity to death. High concentration of cost immediately preceding death. (Stooker et al.,2001; McGrail et al.,2000) – Morbidity – Will increases in life expectancy result in a larger portion of life spent ill or healthy? (Expansion vs Compression)
  10. 10. Demographic Cost Drivers • Age Composition – Most intuitive demographic driver of demand increases. – Given high relative cost for certain cohorts (infants, women of child-bearing age, elderly) change in fertility and life expectancy will likely impact healthcare utilisation and cost. – Common assumption that increases in the elderly population will result in higher average expenditures.
  11. 11. • Death related costs – Hypothesis states that relevant factor in cost incidence and care demands is proximity to death rather than age per se (Gray, 2005). – Majority of lifetime healthcare costs accumulate at the end of an individuals life. – Death related costs higher for younger patients than old ones. Generally offset by lower mortality rates.
  12. 12. • Morbidity Compression or Expansion – Debate as to whether healthcare improvements characterised by expansions or contractions with respect morbidity. – Morbidity expansion implies that increases in life expectancy translate into more years spent in ill-health. Chronic illness and disability drives increases. – Morbidity compression proponents suggest that number of years spent in good health will increase as life expectancy increases. The relative portion of life spent in ill-health shrinks. – Some evidence for morbidity compression outpacing life expectancy gains within “treatment groups”-Hubert and Frees (1994), Chakravarty et al. (2008).
  13. 13. Income and Residual Cost Drivers • Income – Response of health demanded to income changes. Measured via and income elasticity of health demand. For every 1% change in income, what is the percentage change in health demanded? • Residual – Expenditure growth left unexplained by demographic or income related factors. – Thought to include factors such as: I. Technology II. Relative Prices III. Institutional Arrangements and Policies – Difficult to forecast these factors. Relative Prices, “Baumol Effect” may be relevant for particular sectors, but can’t be assumed for health service as a whole.
  14. 14. Current Public Health Expenditure Demographic Factors Age Composition of Population Death Related Costs Morbidity Income Residual Technology Relative Prices Institutional Arrangements Determinants of Current Public Health Expenditure Growth
  15. 15. Projection Model ∆ ln H N t = ∆ ln Dt + ε∆ ln Y N t + ∆ ln γt Per capita current public spending cost growth is a function of demographic cost pressure, the response of health demand to changes in income (Real GDP per Capita) and residual growth factors (OECD, 2015).
  16. 16. • Demographic cost growth: – Death Costs → Multiply age/gender specific per capita death costs by decedent population by cohort. Mortality rates from CSO. – Survivor Costs → Subtract cohort specific death costs from total health costs for that cohort and divide by the surviving population. – Under morbidity expansion, survivor and death per capita costs remain constant. Under compression, per capita survivor costs adjusted according to LE gains. Constant ratio between per capita survivor and death related costs used to calculate adjusted death costs in accordance with survivor adjustments.
  17. 17. Assumptions • Demographic Component – Central Scenario uses M1F1 projections. Sensitivity analyses uses M2F2. – Death related costs= 4 times cost of oldest cohort (100+) for all below 60. Thereafter coefficient allowed decline linearly to unity for oldest cohort. (OECD 2015) – Morbidity Compression= constant cost profile across forecast period. – Morbidity expansion= gains in life expectancy translate into healthy years 1 for 1 over 65. Coefficient declines to zero at 44, i.e.LE gains don’t result in adjusted costs for individuals under 45 (Caley and Sidhu, 2010).
  18. 18. • Income Component – Central scenario sets ε at 0.8. Sensitivity performed for elasticities of 0.6 and 1. – M1F1 growth equals QEO projections to 2017, 3% annually thereafter (OECD). – M2F2 growth same to 2017. Rest of forecast growth=Employment Growth + Productivity Growth (1.5%).
  19. 19. • Residual Component – Residual set at 1.5% annually. Country specific residual from growth accounting not included because period analysed potentially atypical and would result in explosive cost growth. – 2 scenarios are presented. First has residual constant for entirety of forecast period. Second sees residual decline linearly to zero by 2035. Second scenario models an implicit policy response to curb cost growth.
  20. 20. Scenario Gains in Life Expectancy= Gains in healthy life years Cost Profile Remains Constant Residual stays a constant 1.5% Residual declines from 1.5% in 2013 to 0 in 2035 Scenario 1 Morbidity Expansion   Scenario 1 Morbidity Compression   Scenario 2 Morbidity Expansion   Scenario 2 Morbidity Compression   Table of Nomenclature for Results
  21. 21. Results Years (Inclusive) Million € Spending Pressure (at 2013 prices) % Overall Annual Expenditure Growth due to demographics Morbidity Expansion Morbidity Compression Morbidity Expansion Morbidity Compression Population Projection M1F1 M2F2 M1F1 M2F2 M1F1 M2F2 M1F1 M2F2 2013-2015 €152.37 €142.42 €121.35 €111.40 1.16% 1.08% 0.92% 0.85% 2016-2018 €195.91 €167.46 €162.53 €134.16 1.44% 1.24% 1.21% 1.00% 2019-2021 €237.49 €189.23 €202.03 €154.01 1.67% 1.35% 1.44% 1.11% 2022-2024 €265.95 €202.07 €228.21 €164.80 1.78% 1.38% 1.56% 1.15% 2025-2027 €281.94 €210.23 €243.00 €171.96 1.79% 1.38% 1.58% 1.16% 2028-2030 €295.92 €220.25 €256.14 €181.40 1.78% 1.39% 1.59% 1.18% 2031-2033 €303.43 €223.18 €264.15 €185.17 1.73% 1.35% 1.57% 1.16% 2034-2035 €306.85 €222.16 €267.87 €184.82 1.68% 1.30% 1.53% 1.13% Table 1: Average Annual Direct Demographic Cost Pressure (pg. 14)
  22. 22. Figure 5: Cumulative Demographic Cost Pressure at 2013 Prices (pg.15) 0 1 2 3 4 5 6 CumulativeDemographicCostPressure2013 Prices(€Billions) M1F1 Morbidity Expansion M1F1 Morbidity Compression M2F2 Morbidity Expansion M2F2 Morbidity Compression
  23. 23. Figure 6: Decomposition of Real Average per Capita Current Health Expenditure growth 2013-2035 (pg.18) Expanded Morbidity Scenario 1 Compression of Morbidity Scenario 1 Expanded Morbidity Scenario 2 Compression of Morbidity Scenario 2 Average Real GDP Growth Per Capita 0.00% 0.50% 1.00% 1.50% 2.00% 2.50% 3.00% 3.50% 4.00% AnnualAveragePerCapitaCostGrowth Demographic Component Income Component Residual Component
  24. 24. Figure 7: M1F1 Projections 2035 Sensitivity Analysis according in Income Elasticity (pg.19) 7.29% 7.29% 7.29% 7.29% 2.91% 2.48% 1.34% 0.97% 0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 12.00% Mobidity Expansion Scenario 1 Mobidity Compression Scenario 1 Mobidity Expansion Scenario 2 Mobidity Compression Scenario 2 PublicHealthSpendingasa%ofGDP Current Public Spending as % GDP 2013 Relative Current Public Spending Increase % GDP 2035
  25. 25. Figure 8: M2F2 Projections 2035 Sensitivity Analysis according in Income Elasticity (pg.21) 7.29% 7.29% 7.29% 7.29% 2.91% 2.48% 1.34% 0.97% 0.21% 0.18% 0.18% 0.16% 0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 12.00% Mobidity Expansion Scenario 1 Mobidity Compression Scenario 1 Mobidity Expansion Scenario 2 Mobidity Compression Scenario 2 CurrentPublicHealthSpendingasa%ofGDP Current Public Spending as a % GDP 2013 Relative Increase in Spending as % GDP M1F1 Relative Deviation from M1F1 Estimates as % GDP
  26. 26. Figure 9: Age Decomposition of Current Health Expenditure Cost Growth (pg.22) 70.00% 58.68% 59.63% 56.16% 57.06% 30.00% 41.32% 40.37% 43.84% 42.94% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2013 2035 M1F1 Morbidity Expansion 2035 M1F1 Morbidity Compression 2035 M2F2 Morbidity Expansion 2035 M2F2 Morbidity Compression Under 65 Over 65
  27. 27. Conclusions • Significant demographic cost pressures exist in the forecast model. – Annual cost pressure exceeds €100 million in all cases. – Doesn’t attain €200 for MC M2F2. In all other cases, exceeds €200 million from 2019. Reaches €300 million in 2034 in ME M1F1. – Cost growth ≈ 1% annually – Cumulative demographic costs exceed €1 billion between 2019 and 2021. Range from €3.57 billion to €5.66 billion in 2035.
  28. 28. • Current Public Health Spending will increase to 2035. – Range of central estimates between 8.3 and 10.2% of forecast GDP in 2035, Though this is higher under the most pessimistic assumption set (maximum ≈ 11.6%). • Changes in composition of public health spending. – Over 65s go from 30% to over 40% of spend 2013 to 2035.
  29. 29. • Complicating factors to consider include: – Possible inefficiency within the current system upwardly biasing forecast estimates. – Absence of Irish Specific cost profiles. – Residual cost growth accuracy given its lack of explanatory power. – European and domestic rules restraining expenditure growth. – Likely endogeneity between components. – Political Choices.
  30. 30. Policy Questions • What are appropriate investment levels? • Are there efficiencies that can mitigate residual cost growth? • What is the vision for the health service? • What is a reasonable time frame for such a vision’s realisation?
  31. 31. www.NERInstitute.net

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