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Plenary_Talk_1_Meyer

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Talks of the Swiss Health Economics Workshop 2013

Talks of the Swiss Health Economics Workshop 2013

Published in: Economy & Finance, Business
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  • 1. Background Model and Data Results Conclusion Inpatient Payment Schemes and Cost Efficiency Evidence from Swiss Public Hospitals Stefan Meyer Department of Health Economics, University of Basel 13 September 2013 Swiss Health Economic Workshop, Lucerne Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 2. Background Model and Data Results Conclusion Outline 1 Background 2 Model and Data 3 Results 4 Conclusion Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 3. Background Model and Data Results Conclusion Inefficiencies in Healthcare Swiss healthcare expenditure has risen by 46% over the last decade, reaching CHF 62.5 billion (10.9% of GDP) in 2010 (BFS, 2010). A significant part of healthcare costs arise due to inefficient allocation of resources and inefficient production of goods and services (OECD, 2010). A recent US study by the WHO (2010) estimates total costs of inefficiencies to be in a range of $ 600 - 850 billion per year (≈ 30% of total health spending). Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 4. Background Model and Data Results Conclusion Inefficiencies in Healthcare Swiss healthcare expenditure has risen by 46% over the last decade, reaching CHF 62.5 billion (10.9% of GDP) in 2010 (BFS, 2010). A significant part of healthcare costs arise due to inefficient allocation of resources and inefficient production of goods and services (OECD, 2010). A recent US study by the WHO (2010) estimates total costs of inefficiencies to be in a range of $ 600 - 850 billion per year (≈ 30% of total health spending). Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 5. Background Model and Data Results Conclusion Inefficiencies in Healthcare Swiss healthcare expenditure has risen by 46% over the last decade, reaching CHF 62.5 billion (10.9% of GDP) in 2010 (BFS, 2010). A significant part of healthcare costs arise due to inefficient allocation of resources and inefficient production of goods and services (OECD, 2010). A recent US study by the WHO (2010) estimates total costs of inefficiencies to be in a range of $ 600 - 850 billion per year (≈ 30% of total health spending). Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 6. Background Model and Data Results Conclusion Inefficiency and Payment Schemes Well-known factors like income, technological progress, and demography have contributed to the continuing upward trend. Still, as these forces are hardly controllable, policies aimed at reducing inefficiencies have become essential. Prospective reimbursement schemes can serve as controlling instruments for lowering cost inefficiency. Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 7. Background Model and Data Results Conclusion Inefficiency and Payment Schemes Well-known factors like income, technological progress, and demography have contributed to the continuing upward trend. Still, as these forces are hardly controllable, policies aimed at reducing inefficiencies have become essential. Prospective reimbursement schemes can serve as controlling instruments for lowering cost inefficiency. Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 8. Background Model and Data Results Conclusion Inefficiency and Payment Schemes Well-known factors like income, technological progress, and demography have contributed to the continuing upward trend. Still, as these forces are hardly controllable, policies aimed at reducing inefficiencies have become essential. Prospective reimbursement schemes can serve as controlling instruments for lowering cost inefficiency. Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 9. Background Model and Data Results Conclusion Inpatient Sector in Switzerland I A substantial part of healthcare resources is allocated to the inpatient sector, amounting to CHF 21.7 billion (34.9%) in 2009 (OECD, 2012). Small efficiency gains in this sector may lower total healthcare costs considerably. Saved resources can be reallocated to socially beneficial areas of healthcare. The average length of stay (ALOS) in Swiss hospitals remains high room for improving cost efficiency. Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 10. Background Model and Data Results Conclusion Inpatient Sector in Switzerland I A substantial part of healthcare resources is allocated to the inpatient sector, amounting to CHF 21.7 billion (34.9%) in 2009 (OECD, 2012). Small efficiency gains in this sector may lower total healthcare costs considerably. Saved resources can be reallocated to socially beneficial areas of healthcare. The average length of stay (ALOS) in Swiss hospitals remains high room for improving cost efficiency. Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 11. Background Model and Data Results Conclusion Inpatient Sector in Switzerland I A substantial part of healthcare resources is allocated to the inpatient sector, amounting to CHF 21.7 billion (34.9%) in 2009 (OECD, 2012). Small efficiency gains in this sector may lower total healthcare costs considerably. Saved resources can be reallocated to socially beneficial areas of healthcare. The average length of stay (ALOS) in Swiss hospitals remains high room for improving cost efficiency. Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 12. Background Model and Data Results Conclusion Inpatient Sector in Switzerland I A substantial part of healthcare resources is allocated to the inpatient sector, amounting to CHF 21.7 billion (34.9%) in 2009 (OECD, 2012). Small efficiency gains in this sector may lower total healthcare costs considerably. Saved resources can be reallocated to socially beneficial areas of healthcare. The average length of stay (ALOS) in Swiss hospitals remains high room for improving cost efficiency. Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 13. Background Model and Data Results Conclusion Length of Stay in Selected OECD Countries (2009) Source: OECD, 2009 (Greece: 2007 Data) Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 14. Background Model and Data Results Conclusion Inpatient Sector in Switzerland II Until 2011: Considerable differences in inpatient reimbursement among hospitals and local healthcare areas (cantons) As of 2012: Implementation of cased-based payment (SwissDRGs) in public and private hospitals all over Switzerland Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 15. Background Model and Data Results Conclusion 4 Payment Systems in Question I Revenue per case (Ri ) under 4 payment schemes: per diem: flat payment per patient day Rdiem i = pt · ti APDRG: flat payment per case (according to a national DRG catalogue) RDRG i = CW k · ¯P Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 16. Background Model and Data Results Conclusion 4 Payment Systems in Question II DCB: flat payment per case (according to the hospital department involved) RDCB i = Bk PLT (hybrid): flat payment per case + flat payment per patient day (both depending on the hospital department involved) RPLT i = Bk + pk t · ti PLT: Prozess-Leistungs-Tarifierung, DCB: Department case-based payments (Abteilungspauschalen). We treat the patient pathway system (MIPP, Cantonal Hospital of Aarau) as DCB, since the two systems do not differ in the way they offer financial incentives to the hospital. Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 17. Background Model and Data Results Conclusion Payment Schemes in Swiss Cantons (2009) Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 18. Background Model and Data Results Conclusion Research Outline I I aim to... estimate cost (in)efficiency (CE) scores for Swiss public hospitals by means of Stochastic Frontier Analysis (SFA), show that flat payment schemes decrease inefficiency (c.p.). analyse the consequences of heteroscedasticity (to be discussed later on). Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 19. Background Model and Data Results Conclusion Research Outline I I aim to... estimate cost (in)efficiency (CE) scores for Swiss public hospitals by means of Stochastic Frontier Analysis (SFA), show that flat payment schemes decrease inefficiency (c.p.). analyse the consequences of heteroscedasticity (to be discussed later on). Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 20. Background Model and Data Results Conclusion Research Outline I I aim to... estimate cost (in)efficiency (CE) scores for Swiss public hospitals by means of Stochastic Frontier Analysis (SFA), show that flat payment schemes decrease inefficiency (c.p.). analyse the consequences of heteroscedasticity (to be discussed later on). Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 21. Background Model and Data Results Conclusion Research Outline II I take advantage of the fact that... until 2011, health insurers employed 4 different inpatient payment schemes in 26 cantons. the problem of unobserved heterogeneity across observation areas is alleviated, as we only focus on one country. the public sector (cantons) reimburses hospitals on the same basis (object financing = global budget, deficit guarantee). Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 22. Background Model and Data Results Conclusion Research Outline II I take advantage of the fact that... until 2011, health insurers employed 4 different inpatient payment schemes in 26 cantons. the problem of unobserved heterogeneity across observation areas is alleviated, as we only focus on one country. the public sector (cantons) reimburses hospitals on the same basis (object financing = global budget, deficit guarantee). Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 23. Background Model and Data Results Conclusion Research Outline II I take advantage of the fact that... until 2011, health insurers employed 4 different inpatient payment schemes in 26 cantons. the problem of unobserved heterogeneity across observation areas is alleviated, as we only focus on one country. the public sector (cantons) reimburses hospitals on the same basis (object financing = global budget, deficit guarantee). Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 24. Background Model and Data Results Conclusion Econometric Model: Cobb Douglas Cost Frontier ln TCit = α + m βm ln ym it + n βn ln pn it + k βksk it + vit + uit εit TCit Total costs of hospital i at time t ym it Outputs pn it Factor prices sk it Hospital characteristics vit Two-sided random noise component uit Non-negative inefficiency component Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 25. Background Model and Data Results Conclusion Econometric Model: Inefficiency Term Battese and Coelli (1995) propose a model in which inefficiency effects are assumed to be a function of firm-specific variables and time: uit = zitδ + wit, uit ∼ N+(zitδ, σ2 u) zit Vector of hospital-specific and regional variables (payment scheme and other variables) wit Random noise component (truncated normal distributed) δ Vector of parameters to be estimated Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 26. Background Model and Data Results Conclusion Distribution of the Inefficiency Term Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 27. Background Model and Data Results Conclusion Data BFS data on 122 public and publicly-financed hospitals in Switzerland Period: 2004 - 2009 (T = 6) Information on hospital category, teaching, inputs, inpatient and outpatient outputs, and costs 5 observations per hospital on average, total sample size of 606 (inclusion criterion: ≥ 2 obs., ≥750 inpatient days) Data covers a total of 4.9 million cases (≈ 58% of all hospital cases between 2004 and 2009) Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 28. Background Model and Data Results Conclusion Despriptive Statistics I (N = 606) Variable Description Mean SD Cost frontier variables TC Total costs (k CHF) 130 010.4 195 921.7 CASES Number of CMI-adjusted discharges 8 283.1 10 109.3 OUTP Revenue from outpatients (k CHF) 24 746.3 37 935.3 PL Price of labour (k CHF) 100.1 14.4 PK Price of capital (k CHF) 170.6 76.9 SERVICE Number of hospital services 36.2 18.0 INTERN Number of advanced training categories* 20.5 27.9 *FMH Weiterbildungskategorien Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 29. Background Model and Data Results Conclusion Despriptive Statistics II (N = 606) Variable Description Mean SD Inefficiency variables APDRG APDRG-based payment system* 0.27 PLT Hybrid payment system* 0.54 DCB Department level case-based system* 0.06 OCC Bed occupancy rate 0.88 0.10 BEDS Acute care beds per 1,000 residents 2.95 0.70 PHYS GPs specialists per 1,000 residents 2.00 0.57 MCARE Managed Care contracts / total number of MHI contracts 0.17 0.11 POP Population density (Residents / sq km) 536.10 1 062.30 *Dummy variable Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 30. Background Model and Data Results Conclusion Heteroscedasticity SFA are likely to suffer from severe heteroscedasticity (HEC), especially if the hospitals are of different size. Coefficients are biased in SFA models if HEC is overlooked (frontier is changed when dispersion increases; s. Caudill et al., 1995). Heteroscedastic uit: Large hospitals have more“under their control”, efficiency gets more important with size large hospitals have much more in common than their small counterparts Heteroscedastic vit: Greater impact of random shocks on small units (“Law of large numbers”) Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 31. Background Model and Data Results Conclusion Heteroscedasticity SFA are likely to suffer from severe heteroscedasticity (HEC), especially if the hospitals are of different size. Coefficients are biased in SFA models if HEC is overlooked (frontier is changed when dispersion increases; s. Caudill et al., 1995). Heteroscedastic uit: Large hospitals have more“under their control”, efficiency gets more important with size large hospitals have much more in common than their small counterparts Heteroscedastic vit: Greater impact of random shocks on small units (“Law of large numbers”) Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 32. Background Model and Data Results Conclusion Heteroscedasticity SFA are likely to suffer from severe heteroscedasticity (HEC), especially if the hospitals are of different size. Coefficients are biased in SFA models if HEC is overlooked (frontier is changed when dispersion increases; s. Caudill et al., 1995). Heteroscedastic uit: Large hospitals have more“under their control”, efficiency gets more important with size large hospitals have much more in common than their small counterparts Heteroscedastic vit: Greater impact of random shocks on small units (“Law of large numbers”) Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 33. Background Model and Data Results Conclusion Specifying HEC Three different specifications: (1) No HEC (2) HEC in uit (3) HEC in both uit and vit Assumption: σ2 uit = exp(CASESitη) and σ2 vit = exp(CASESitφ), where η and φ are parameters to be estimated. Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 34. Background Model and Data Results Conclusion HEC: Findings 1 Both σ2 uit and σ2 vit are negatively correlated with hospital size (p 0.01), indicating that variation of uit and vit is more distinct among smaller institutions. 2 Coefficients (and standard errors) slightly change when HEC is taken into acount. Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 35. Background Model and Data Results Conclusion SFA Results ln TC σ2 u/ σ2 v σ2 ui / σ2 v σ2 ui / σ2 vi ln CASES 0.830*** (0.015) 0.882*** (0.013) 0.864*** (0.014) ln OUTP 0.117*** (0.014) 0.098*** (0.010) 0.102*** (0.012) ln PL 0.026 (0.072) 0.057 (0.037) 0.000 (0.039) ln PK 0.271*** (0.027) 0.249*** (0.016) 0.258*** (0.020) ln SERVICE 0.027* (0.014) 0.001* (0.000) 0.001* (0.000) ln INTERN 0.029*** (0.007) 0.002*** (0.000) 0.002*** (0.000) YEAR 0.014*** (0.004) 0.014*** (0.004) 0.007 (0.005) APDRG =0.407** (0.171) =0.298*** (0.081) =0.289*** (0.072) PLT =0.136 (0.084) =0.080* (0.043) =0.092** (0.040) DCB =0.931 (0.810) =0.561** (0.237) =0.593* (0.338) OCC =1.754** (0.869) =1.108*** (0.339) =1.239*** (0.359) BEDS =0.414** (0.180) =0.246*** (0.067) =0.256*** (0.066) PHYS 0.330** (0.156) 0.103** (0.050) 0.131*** (0.046) MCARE =0.997 (0.775) =0.396* (0.239) =0.457** (0.229) POP 0.000 (0.000) 0.000** (0.000) 0.000** (0.000) YEAR 0.097 (0.067) 0.043** (0.020) 0.058*** (0.018) Note: N = 606; Cluster robust standard errors are given in parentheses; *p 0.10, **p 0.05, ***p 0.01; The sign of the efficiency variables are to be read as effects on inefficiency; Both constants not shown Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 36. Background Model and Data Results Conclusion Main Findings I Compared to per diem, all three systems are associated with decreased inefficiency. This finding is most pronounced among hospitals that apply flat payment schemes (APDRG, DCB). High bed density in acute care is associated with enhanced CE (highly competitive markets little market / bargaining power) Inefficient hospitals are likely found in population-dense areas with a high penetration of GPs and specialists ( proxy measure of demand; s. Chirikos, 1998). Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 37. Background Model and Data Results Conclusion Main Findings I Compared to per diem, all three systems are associated with decreased inefficiency. This finding is most pronounced among hospitals that apply flat payment schemes (APDRG, DCB). High bed density in acute care is associated with enhanced CE (highly competitive markets little market / bargaining power) Inefficient hospitals are likely found in population-dense areas with a high penetration of GPs and specialists ( proxy measure of demand; s. Chirikos, 1998). Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 38. Background Model and Data Results Conclusion Main Findings I Compared to per diem, all three systems are associated with decreased inefficiency. This finding is most pronounced among hospitals that apply flat payment schemes (APDRG, DCB). High bed density in acute care is associated with enhanced CE (highly competitive markets little market / bargaining power) Inefficient hospitals are likely found in population-dense areas with a high penetration of GPs and specialists ( proxy measure of demand; s. Chirikos, 1998). Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 39. Background Model and Data Results Conclusion Main Findings II As found in an earlier study by Rosko (2004), managed care penetration is positively correlated with CE (Insurers may place financial pressure on hospitals when prices are being negotiated). Mean cost inefficiency increased significantly from 7.8% in 2004 to 12.3% in 2009. CE scores only changed marginally when the panel was almost balanced (from 2006). Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 40. Background Model and Data Results Conclusion Main Findings II As found in an earlier study by Rosko (2004), managed care penetration is positively correlated with CE (Insurers may place financial pressure on hospitals when prices are being negotiated). Mean cost inefficiency increased significantly from 7.8% in 2004 to 12.3% in 2009. CE scores only changed marginally when the panel was almost balanced (from 2006). Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 41. Background Model and Data Results Conclusion Mean Inefficiency Estimates by Payment Scheme Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 42. Background Model and Data Results Conclusion Conclusion Positive correlation of flat payment and CE in Swiss public hospitals (controlling for hospital characteristics, the market environment, and time trends). Findings are in line with the basic economic theory on the financial incentives of payment schemes (Ellis and McGuire, 1986). Considerable differences in mean inefficiencies across hospital categories (maximum gap of about 15% between per diem and DLCB hospitals in 2009). In SFA, heteroscedastic error terms (uit and vit) lead to biased coefficients and standard errors. Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 43. Background Model and Data Results Conclusion Conclusion Positive correlation of flat payment and CE in Swiss public hospitals (controlling for hospital characteristics, the market environment, and time trends). Findings are in line with the basic economic theory on the financial incentives of payment schemes (Ellis and McGuire, 1986). Considerable differences in mean inefficiencies across hospital categories (maximum gap of about 15% between per diem and DLCB hospitals in 2009). In SFA, heteroscedastic error terms (uit and vit) lead to biased coefficients and standard errors. Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 44. Background Model and Data Results Conclusion Conclusion Positive correlation of flat payment and CE in Swiss public hospitals (controlling for hospital characteristics, the market environment, and time trends). Findings are in line with the basic economic theory on the financial incentives of payment schemes (Ellis and McGuire, 1986). Considerable differences in mean inefficiencies across hospital categories (maximum gap of about 15% between per diem and DLCB hospitals in 2009). In SFA, heteroscedastic error terms (uit and vit) lead to biased coefficients and standard errors. Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 45. Background Model and Data Results Conclusion Limitations I do not account for quality differences among hospitals (evidence suggests that ignoring them may not be a serious problem; s. Mutter et al., 2008). Unobservable differences among cantons biased coefficients of the payment scheme variables. Potential endogeneity in the outputs and the factor prices as a major drawback in SFA (especially the price proxies may reflect the hospitals’ choices about the average skill-mix and the amount and mix of capital; s. Zuckermann et al., 1994). Small sample of Swiss public hospitals unclear whether these findings can be applied to private hospitals as well (or even other healthcare systems). Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 46. Background Model and Data Results Conclusion Limitations I do not account for quality differences among hospitals (evidence suggests that ignoring them may not be a serious problem; s. Mutter et al., 2008). Unobservable differences among cantons biased coefficients of the payment scheme variables. Potential endogeneity in the outputs and the factor prices as a major drawback in SFA (especially the price proxies may reflect the hospitals’ choices about the average skill-mix and the amount and mix of capital; s. Zuckermann et al., 1994). Small sample of Swiss public hospitals unclear whether these findings can be applied to private hospitals as well (or even other healthcare systems). Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 47. Background Model and Data Results Conclusion Limitations I do not account for quality differences among hospitals (evidence suggests that ignoring them may not be a serious problem; s. Mutter et al., 2008). Unobservable differences among cantons biased coefficients of the payment scheme variables. Potential endogeneity in the outputs and the factor prices as a major drawback in SFA (especially the price proxies may reflect the hospitals’ choices about the average skill-mix and the amount and mix of capital; s. Zuckermann et al., 1994). Small sample of Swiss public hospitals unclear whether these findings can be applied to private hospitals as well (or even other healthcare systems). Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 48. Background Model and Data Results Conclusion Limitations I do not account for quality differences among hospitals (evidence suggests that ignoring them may not be a serious problem; s. Mutter et al., 2008). Unobservable differences among cantons biased coefficients of the payment scheme variables. Potential endogeneity in the outputs and the factor prices as a major drawback in SFA (especially the price proxies may reflect the hospitals’ choices about the average skill-mix and the amount and mix of capital; s. Zuckermann et al., 1994). Small sample of Swiss public hospitals unclear whether these findings can be applied to private hospitals as well (or even other healthcare systems). Stefan Meyer Inpatient Payment Schemes and Cost Efficiency
  • 49. Background Model and Data Results Conclusion Thank you! Many thanks for your attention! Stefan Meyer Inpatient Payment Schemes and Cost Efficiency

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