Parallel_Session_1_Talk_5_Tondelli

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Talks of the Swiss Health Economics Workshop 2013

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Parallel_Session_1_Talk_5_Tondelli

  1. 1. Thursday, September 12, 2013 September 13, 2013 | Tribschenstrasse 21, 6002 Luzern Reimbursement Reform and the Distribution of Labor between In- and Outpatient Care: Evidence from Switzerland Timo Tondelli Swiss Health Economics Workshop
  2. 2. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 2 Swiss Health Economics Workshop Reimbursement Reform and the Distribution of Labor between In- and Outpatient Care: Evidence from Switzerland Author: Timo Tondelli PhD Student & Research Associate Supervisor: Prof. Dr. Stefan Felder WWZ, Universität Basel Health Economics timo.tondelli@unibas.ch
  3. 3. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 3 Contribution 1 2 Theoretical model that clarifies the role of specific reimbursement schemes on physicians’ decision how to allocate medical in- and outpatient inputs in the production of patient health. Empirical evidence on the impact of inpatient reimbursement on the distribution of labor between in- and outpatient care by exploiting a quasi-experiment in Switzerland.
  4. 4. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 4 Results at a glance Theoretical prediction: • Increase of outpatient inputs if the proportional share of reimbursement in inpatient care is reduced. • Prospective hospital payment (DRG) is expected to increase the amount of ambulatory care related to inpatient stays. Empirical findings: • Empirical evidence supports theoretical prediction: A less effective cost based inpatient reimbursement increases ambulatory care linked to inpatient stays – shift of treatment parts. • Patient data of a major Swiss Health insurance company. • Ambulatory care is measured by the number of physician visits and billed taxpoints. • Swiss DRG introduction offers a quasi-experiment.
  5. 5. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 5 1. Literature | Theoretical Model | Swiss Inpatient Reimbursement 2. Data Sample & Empirical Strategy 3. Empirical Findings & Conclusion Index
  6. 6. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 6 Literature review • Discharges to nursing homes rise significantly after DRG introduction in the USA (Sloan and Valvona (1986), Sager et al. (1987, 1989)). • Increase in outpatient physician visits in years after DRG introduction in USA (Hadley et al. (1987), Menke (1990)). Visits to physician offices not considered and no link between inpatient an outpatient care on patient level. • No evidence for a shift of treatment parts from inpatient to outpatient care found after German DRG introduction (Fürstenberg et al. (2011), Grobe et al. (2011)). Findings rely solely on data after DRG introduction. • In Switzerland Busato and von Below (2010) look at the effect of hospital compensation on outpatient care costs per capita (descriptive statistics). Empirical evidence on the relationship between inpatient reimbursement and the shift of treatment parts from inpatient to outpatient care contributes to the existing literature.
  7. 7. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 7 Theoretical framework Assumptions & utility function • Patient visits his physician… • Physician examines the patient and decides on treatment (how and where) - Patient acts accordingly • Patient is fully insured and payments are directly made by the insurance company • Treatments consist of inpatient care (i) and/or ambulatory care (a) • For example, an inpatient surgical procedure and an outpatient CT scan equals 1000i and 100a. Assumptions Health care provider utility 𝑢 𝑎, 𝑖 = 𝜋 𝑎, 𝑖 + 𝛾 ∙ 𝐵(𝑎, 𝑖) Profit Patient benefit
  8. 8. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 8 Theoretical framework Components of care providers’ utility Profit Patient benefit 𝜋 𝑎, 𝑖 = 𝑅 𝑎, 𝑖 − 𝑐 𝑎, 𝑖 𝑅 𝑎, 𝑖 = 𝑓𝑎 + 𝑣 𝑎 ∙ 𝑎 + 𝑓𝑖 + 𝑣𝑖 ∙ 𝑖 Reimbursement Cost of providing care 𝑓𝑎, 𝑓𝑖: Fixed prospective component 𝑐 𝑎, 𝑖 = 𝑤 𝑎 ∙ 𝑎 + 𝑤𝑖 ∙ 𝑖 𝑤 𝑎, 𝑤𝑖: Input prices per unit 𝑣 𝑎, 𝑣𝑖: Effective cost based component • B 𝑎, 𝑖 increasing at a decreasing rate up to a maximum 𝑎 𝑚𝑎𝑥 , 𝑖 𝑚𝑎𝑥 • B 𝑎, 𝑖 is a strictly concave function with a unique maximum • Benefit function is allowed to vary across patients/diseases • Inpatient and outpatient care are substitutes: 𝜕2 𝐵 𝑎,𝑖 𝜕𝑎𝜕𝑖 < 0
  9. 9. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 9 Theoretical framework Effect of inpatient reimbursement on outpatient care First order conditions Comparative statics • Derivative of the FOCs with respect to vi • Solve for 𝜕a∗ 𝜕vi and 𝜕i∗ 𝜕vi • Change in ambulatory care: 𝑢 𝑎, 𝑖 = 𝜋 𝑎, 𝑖 + 𝛾 ∙ 𝐵(𝑎, 𝑖) (1) 0 = 𝑣 𝑎 − 𝑤 𝑎 + 𝛾 ∙ 𝜕𝐵 𝜕𝑎 (2) 0 = 𝑣𝑖 − 𝑤𝑖 + 𝛾 ∙ 𝜕𝐵 𝜕𝑖 𝜕𝑎∗ 𝜕𝑣𝑖 = 1 𝛾 ∙ 𝜕2 𝐵 𝜕𝑎𝑖 𝜕2 𝐵 𝜕𝑎𝑎 ∙ 𝜕2 𝐵 𝜕𝑖𝑖 − 𝜕2 𝐵 𝜕𝑎𝑖 2 < 0 Reduction in the proportional share of inpatient reimbursement causes an increase in ambulatory care
  10. 10. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 10 Swiss inpatient reimbursement Major change in 2012 AP-DRG PLT TP MIPP/ABP SDRG 2010 - 2011 Since 2012
  11. 11. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 11 Swiss inpatient reimbursement: Hypotheses Expected levels of outpatient care across Switzerland AP-DRG PLT TP SDRG Note: MIPP/ABP is not included in the analysis as it applied only in 1 canton. 𝒗𝒊 • Effective cost sharing component 𝑣𝑖 drives the shift from inpatient to ambulatory care. • Higher 𝑣𝑖 results in a lower level of ambulatory care. • TP has the highest effective cost sharing component, AP-DRG / SDRG the lowest, and PLT is in between. • Outpatient inputs in the production of patient health are lowest in TP regions, higher in PLT hospitals and highest in AP-DRG/SDRG regions. Inpatient reimbursement Hypothesis
  12. 12. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 12 1. Literature | Theoretical Model | Swiss Inpatient Reimbursement 2. Data Sample & Empirical Strategy 3. Empirical Findings & Conclusion Index
  13. 13. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 13 Data sample Patient data of the largest Swiss health insurer Data sample • Patient level data of the largest Swiss health insurance company: Helsana AG • Detailed information on all patients who had an inpatient treatment covered by a health insurance contract during any second quarter from 2010-2012. Sample selection • Canton of Aargau is excluded. • Patient’s canton of residence has to match hospital location. • Only inpatient stays in somatic care hospitals1 are considered. • Only treatments that are covered by a mandatory health insurance contract. • Top 1% of patients in terms of days in hospital are excluded. 1: K111, K112, K121, K122, K123, K231, K232 or K233 according to the BFS Krankenhaustypologie
  14. 14. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 14 Data sample overview 62’397 inpatient stays in 153 hospitals Note: PLT: Prozess-Leistungs-Tarifierung; TP: Tagespauschale; SDRG: Swiss DRG 10'175 9'565 8'734 8'598 2'332 2'376 20'617 2010 2011 2012 Number of inpatient stays AP-DRG PLT TP SDRG Total 21’241 20’539 20’617 62 66 57 58 16 15 142 2010 2011 2012 Number of hospitals AP-DRG PLT TP SDRG 139135 142
  15. 15. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 15 Ambulatory care measurement Physician visits and taxpoints near an inpatient stay Treatement Pre-inpatient ambulatory care Post-inpatient ambulatory care Inpatient stay (hospital) 20 days before hospitalization 20 days after hospitalization • Ambulatory physician visits (hospital outpatient facilities and physician offices) • Billed taxpoints for ambulatory physician visits and laboratory analyses • Outpatient care 20 days around an inpatient stay is considered inpatient stay linked (Alternatively 10, 5 days) • Outpatient care more than 30 days away from an inpatient stay is considered unrelated. Ambulatory care variables
  16. 16. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 16 Empirical strategy Introduction of Swiss DRG – a quasi experiment • Nationwide DRG introduction in 2012 • SDRG introduction should not cause a major rise in ambulatory care in former AP-DRG regions • Change in inpatient stay linked ambulatory care in other reimbursement systems (PLT, TP) compared to benchmark (AP- DRG) Quasi-experiment like setting – difference-in- difference estimation CommentInpatient reimbursement
  17. 17. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 17 Methodology Difference-in-difference poisson regression • Estimation method • Pooled poisson regression with cluster-robust standard errors • Dependent variable • Ambulatory physician visits and billed taxpoints 20, 10, 5 days around an inpatient stay • Inpatient reimbursement variables • Control variables • Patient level: inpatient stay related, socio-demographic, health, care usage • Hospital level: treated cases, hospital type • Robustness checks • Regression set up • Estimation methodology
  18. 18. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 18 1. Literature | Theoretical Model | Swiss Inpatient Reimbursement 2. Data Sample & Empirical Strategy 3. Empirical Findings & Conclusion Index
  19. 19. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 19 Main Results Prospective payment causes a shift of treatment parts Physician visits Time window 5 days 10 days 20 days PLT -0.116*** -0.0870*** -0.0835*** (0.0315) (0.0251) (0.0230) TP -0.0752** -0.0751** -0.0629** (0.0373) (0.0352) (0.0313) PLT/SDRG 0.0841** 0.0928*** 0.106*** (0.0354) (0.0308) (0.0307) TP/SDRG 0.0655** 0.0697** 0.0692** (0.0317) (0.0289) (0.0281) Taxpoints Time window 5 days 10 days 20 days PLT -0.157*** -0.130*** -0.109*** (0.0434) (0.0306) (0.0304) TP -0.177*** -0.175*** -0.155*** (0.0452) (0.0382) (0.0355) PLT/SDRG 0.0955** 0.101*** 0.111*** (0.0478) (0.0341) (0.0373) TP/SDRG 0.107*** 0.0870*** 0.0942** (0.0402) (0.0334) (0.0401) Note: Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1
  20. 20. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 20 Robustness checks of the regression set up Main results are confirmed Physician visits Taxpoints Note: Used time window is 20 days around IS; Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1 (1) (2) (3) (4) Standard Separate time trends Fixed effects Not near IS PLT -0.109*** -0.104*** -0.0552 (0.0304) (0.0304) (0.0430) TP -0.155*** -0.152*** -0.0380 (0.0355) (0.0354) (0.0366) PLT/SDRG 0.111*** 0.101*** 0.0934*** 0.0644 (0.0373) (0.0364) (0.0356) (0.0436) TP/SDRG 0.0942** 0.0873** 0.0735** 0.0274 (0.0401) (0.0399) (0.0362) (0.0332) (1) (2) (3) (4) Standard Separate time trends Fixed effects Not near IS PLT -0.0835*** -0.0776*** 0.0202 (0.0230) (0.0226) (0.0294) TP -0.0629** -0.0588* 0.0426 (0.0313) (0.0311) (0.0319) PLT/SDRG 0.106*** 0.0946*** 0.0827*** 0.0537 (0.0307) (0.0299) (0.0295) (0.0372) TP/SDRG 0.0692** 0.0609** 0.0447 0.00245 (0.0281) (0.0278) (0.0330) (0.0300)
  21. 21. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 21 Robustness checks of the estimation method Main results are confirmed Physician visits Note: Used time window is 20 days around IS; NB denotes negative-binomial regression; Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1 (1) (2) (3) (4) (5) (6) Standard NB Zero Inflated Poisson Zero Inflated NB Poisson Inflated NB Inflated PLT -0.0835*** -0.0801*** -0.0688*** 0.144 -0.0603*** 0.518* (0.0230) (0.0233) (0.0194) (0.183) (0.0190) (0.305) TP -0.0629** -0.0550* -0.0710*** -0.128 -0.0662*** -0.352 (0.0313) (0.0318) (0.0258) (0.191) (0.0189) (0.324) PLT/SDRG 0.106*** 0.0991*** 0.0854*** -0.214 0.0763*** -0.438 (0.0307) (0.0309) (0.0282) (0.245) (0.0259) (0.423) TP/SDRG 0.0692** 0.0688** 0.0636*** -0.106 0.0699*** 0.239 (0.0281) (0.0280) (0.0237) (0.252) (0.0251) (0.430)
  22. 22. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 22 Conclusion & Summary Theoretical prediction: • Increase of outpatient inputs if the proportional share of reimbursement in inpatient care is reduced. • Prospective hospital payment (DRG) is expected to increase the amount of ambulatory care related to inpatient stays. Empirical findings: • Empirical evidence supports theoretical prediction: Reduced share of proportional reimbursement increases ambulatory care linked to inpatient stays – shift of treatment parts. • Patient data of a major Swiss Health insurance company. • Ambulatory care is measured by the number of physician visits and billed taxpoints. • Swiss DRG introduction offers a quasi-experiment.
  23. 23. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 23 THANK YOU! Any questions? → timo.tondelli@unibas.ch
  24. 24. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 24 B A C K U P
  25. 25. Thursday, September 12, 2013 T. Tondelli | Swiss Health Economics Workshop | Sep. 13, 2013 25 References • Busato, A. and G. von Below (2010). The implementation of drg-based hospital reimbursement in Switzerland: A population-based perspective. Health Research Policy and Systems 8 (1), 31. • Fürstenberg, T., M. Laschat, K. Zich, S. Klein, P. Gierling, H. Nolting, and T. Schmidt (2011). G-DRG- Begleitforschung gemäss § 17b Abs. 8 KHG. IGES Institut. • Grobe, T., H. Dörning, and F. Schwartz (2011). BARMER GEK Arztreport 2011 – Auswertung zu Daten bis 2009. Schwäbisch Gmünd. • Hadley, J., S. Zuckerman, and J. Feder (1989). Profits and fiscal pressure in the prospective payment system: Their impacts on hospitals. Inquiry 26, 354–65. • Menke, T. (1990). Impacts of PPS on medicare part b expenditures and utilization for hospital episodes of care. Inquiry 27, 114–26.Sager, M., E. Leventhal, and D. Easterling (1987). The impact of medicare’s prospective payment system on wisconsin nursing homes. JAMA 257 (13), 1762–1766. • Sager, M. A., D. V. Easterling, D. A. Kindig, and O. W. Anderson (1989). Changes in the location of death after passage of medicare’s prospective payment system. New England Journal of Medicine 320 (7), 433–439. • Sloan, F. A. and J. Valvona (1986). Why has hospital length of stay declined? an evaluation of alternative theories. Social Science & Medicine 22 (1), 63 – 73. backup

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