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Comparison of Cost and Outcomes of Inpatient and Outpatient Treatment for Substance Use Disorders

Comparison of Cost and Outcomes of Inpatient and Outpatient Treatment for Substance Use Disorders. Paul Barnett PhD Mistry Gage MPH John Finney PhD. Outline. Background on Effect of Inpatient Setting on Substance Use Treatment Instrumental Variables (IV) VA Outcomes Monitoring Project .

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Comparison of Cost and Outcomes of Inpatient and Outpatient Treatment for Substance Use Disorders

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  1. Comparison of Cost and Outcomes of Inpatient and Outpatient Treatment for Substance Use Disorders Paul Barnett PhD Mistry Gage MPH John Finney PhD

  2. Outline • Background on Effect of Inpatient Setting on Substance Use Treatment • Instrumental Variables (IV) • VA Outcomes Monitoring Project Health Economics Resource Center

  3. Overview • Assess effectiveness of outcomes and cost in inpatient and outpatient substance use treatment while controlling for selection bias Health Economics Resource Center

  4. Background • Treatment for substance use disorders has shifted from inpatient to outpatient setting • Payers have shifted from inpatient treatment • Extra cost of inpatient setting • number of studies have not found any advantage to inpatient care Health Economics Resource Center

  5. Clinical Trials • No advantage to inpatient setting (Alterman et al. 1994; McKay et al. 1998; Rychtarik et al. 2000; Weithmann and Hoffman, 2005) • Short-term advantages of inpatient treatment not sustained over the long-run (Greenwood et al. 2001;Schneider et al. 1996) Health Economics Resource Center

  6. Clinical Trials • Limitations • Exclusion criteria • Substance use disorder severity • Psychiatric co-morbidities (Finney et al. 1996) • Estimate treatment effect • External validity Health Economics Resource Center

  7. Observational Studies • Few studies show better outcomes from inpatient treatment (McKay et al. 2002; Mojtabai and Graff Zivin, 2003) • Majority find no significance once patient characteristics are controlled (Harrison and Asche, 1998;McLellan et al. 1994) Health Economics Resource Center

  8. Observational Studies • Limitations • Selection bias • Non-randomized groups differ in observed and unobserved characteristics • Sicker patients are assigned to inpatient care • Differential selection into treatment group Health Economics Resource Center

  9. Instrumental Variables (IV) • Predictor of treatment that has no independent effect on outcome • Uses exogenous variables to control for selection bias Health Economics Resource Center

  10. Instrumental Variables (IV) Y=β0 + β1T+ β2X +εi • Treatment (T) may be correlated with unobserved case-mix εi • Violation of assumptions of OLS • β1 may be biased • Parameter may understate or overstate effect of T on Y Health Economics Resource Center

  11. Instrumental Variables (IV) Assumptions • Relevance: Instrumental variable causes variation in the treatment variable • Exogeneity: Instrumental variable has no direct effect on the outcome variable • (Newhouse and McClellan, 1998) Health Economics Resource Center

  12. Instrumental Variables (IV) Examples • Randomization to intervention group leads to more likely receipt of intervention • Distance from patient residence to nearest cardiac facility predicts likelihood of coronary angioplasty • Inclusion of drug in nearest pharmacy formulary predicts greater likelihood that drug will be dispensed to patient Health Economics Resource Center

  13. Instrumental Variables (IV) • Instrumental Treatment • variable(s) variable(s) • Other Outcome • variables measure • (Adapted from Newhouse and McClellan, 1998) Health Economics Resource Center

  14. Instrumental Variables (IV) Estimation • 2 Stage Least Square (2LS) • Stage 1: T=α0 + α1Z + α2X + ε • ^ • Stage 2: Y=β0 + β1T + β2X + υ ^ T: predicted value of T from the first stage Z: instrumental variable X: patient characteristics Health Economics Resource Center

  15. Testing Assumptions • Good instrument • statistical significance of the instrument in the first stage • the instrument is not a direct determinant of outcomes Health Economics Resource Center

  16. Outcomes Monitoring Project • Evaluate performance of VA substance abuse programs • Selection of study sites • Enumerated and stratified • 141 VA treatment sites • Selection of study participants • Up to 50 new patients at each site Health Economics Resource Center

  17. Outcomes Monitoring Program • Enrollment • 3 waves FY01-04 • 4,905 at baseline • 3,286 at follow-up • Outcomes Measure • Improvement in substance use • Abstinence Health Economics Resource Center

  18. Addiction Severity Index (ASI) • Domains • Alcohol • Drug • Psychiatric • Measures problems/functioning in last 30 days • Composite score ranges from 0 to 1 Health Economics Resource Center

  19. Statistical Methods Outcomes • Multiple Imputations • To address missing ASI follow-up data and attrition bias (Schafer, 1997; Shafer & Graham, 2002) • Estimated regressions for outcomes for each imputation and combined with Rubin’s method. Health Economics Resource Center

  20. Statistical Methods Costs • Cost adjusted to FY03 • Complete not imputated • Estimated regressions with index and follow-up costs • Pre-study cost • Patient case-mix Health Economics Resource Center

  21. Patient Characteristics by Setting Where Enrolled * significant at 5%; ** significant at 1% Health Economics Resource Center

  22. Patient Characteristics by Setting Where Enrolled * significant at 5%; ** significant at 1% Health Economics Resource Center

  23. Challenge • Selection bias • Influence of unobserved covariates correlated with treatment • Some medical centers make greater use of inpatient setting • Program-level error terms • Patients from same program correlated Health Economics Resource Center

  24. Why use Instrumental Variables (IV)? • To take advantage of VA administrative data on facility level variation in the use of inpatient treatment Health Economics Resource Center

  25. Instrumental Variables (IV) • Facility-Level Index • Percentage of the facility's patients who received their substance abuse treatment in the inpatient setting Count of patients who had an inpatient substance use stay Total number of patients who received any type of substance use service inpatient or outpatient Health Economics Resource Center

  26. Instrumental Variables (IV) • Instrumental Treatment • variable(s) variable(s) • Other Outcome • variables measure • (Adapted from Newhouse and McClellan, 1998) Health Economics Resource Center

  27. Instrumental Variables (IV) Relevance • Treatment is correlated with error term • Patients with severe co-morbidities in inpatient programs • Some sites make greater use of residential and inpatient settings • IV captures policy • “natural experiment” caused by policy Health Economics Resource Center

  28. Characteristics of Patients by Type of Facility Where They Enrolled * significant at 5%; ** significant at 1% Health Economics Resource Center

  29. Two Stage Least Square Regression • Stage 1: T=α0 + α1Z + α2X + ε • T=Treatment (inpatient treatment 0/1) • Z=Instrumental variable (percent of inpatient substance use treatment) • X=Covariates (baseline substance use and psychiatric co-morbidities) • ε=Error term Health Economics Resource Center

  30. Instrumental Variable Estimation: 1st Stage Regression Parameters * significant at 5%; ** significant at 1% Health Economics Resource Center

  31. Testing Assumptions • Correlated with treatment • First stage regression treatment significantly predicted by IV • No direct effect on outcomes • Construction/Assumption • Outpatient treatment observed at sites with propensity to treat inpatient Health Economics Resource Center

  32. Two Stage Least Square Regression • ^ • Stage 2: Y=β0 + β1T + β2X + υ • Y=Outcome (improvement in substance use and abstinence) • T=Treatment (inpatient treatment 0/1-instrumented) • X=Covariates (baseline substance use and psychiatric co-morbidity) • υ =Error term Health Economics Resource Center

  33. Instrumental Variable Estimation: 2nd Stage Regression Coefficients * significant at 5%; ** significant at 1% Health Economics Resource Center

  34. Instrumental Variable Estimation: 2nd Stage Regression Coefficients * significant at 5%; ** significant at 1% Health Economics Resource Center

  35. Estimation of Effect of Setting While Controlling for Baseline Case-mix • Used regression parameters to simulate outcomes and cost of typical patient • Estimated mean value for setting while controlling for baseline substance use and case-mix variables • Estimated value of outcomes and cost at the mean of the covariates Health Economics Resource Center

  36. Estimation of Effect of Setting While Controlling for Baseline Case-mix • Summarized findings from 5 outcome regressions and 6 cost regressions • Mean change in substance use for the average patient treated in inpatient and outpatient setting • Mean costs of care for the average patient treated in inpatient and outpatient setting Health Economics Resource Center

  37. Evaluation of Parameter at the Mean: Effect of Treatment Setting on Outcomes * significant at 5%; ** significant at 1% Health Economics Resource Center

  38. Evaluation of Parameter at the Mean: Effect of Treatment Setting on Cost * significant at 5%; ** significant at 1% Health Economics Resource Center

  39. Results • Improvement • Greater for inpatients than outpatients • Change in days intoxicated with alcohol • -5.45 vs. -3.96 • Change in days with drug problems greater • -5.23 vs. -3.87 Health Economics Resource Center

  40. Results • Abstinence • No significant difference observed between settings • Mean Costs • Significantly greater in inpatient setting • Index care ($14,592 vs. $1,964) • Total, index and follow-up care ($25,343 vs. $9,999) Health Economics Resource Center

  41. Conclusion • Inpatient setting treats patients with severe psychiatric, medical, and substance use problems • An analysis that controls for selection bias found inpatient setting yields significantly better outcomes • Setting affects cost Health Economics Resource Center

  42. Implications • Is it worth spending more on treatment for greater outcomes? • Inpatient treatment is ~$8,600 greater than outpatient treatment for an extra 1.5 days reduction in substance use Health Economics Resource Center

  43. Summary • Substance abuse treatment has shifted from inpatient to outpatient setting • Extra cost of inpatient setting • Lack of evidence of inpatient superiority Health Economics Resource Center

  44. Summary • Instrumental variables control for selection bias • Instrumental variables are associated with treatment • Instrumental variables are independent of outcomes Health Economics Resource Center

  45. Summary • Instrumental Treatment • variable(s) variable(s) • Other Outcome • variables measure • (Adapted from Newhouse and McClellan, 1998) Health Economics Resource Center

  46. Summary • VA Outcomes Monitoring Project • IV captures policy • Some sites make greater use of inpatient setting • After controlling for selection bias • Change in substance use severity greater in inpatient care • More costs incurred in inpatient setting Health Economics Resource Center

  47. References • Alterman A, O’Brien C, McLellan T, August D, Snider E, Droba M, Cornish J, Hall C, Raphaelson A, Schrade F. 1994. Effectiveness and costs of inpatient versus day hospital cocaine rehabilitation. J Nerv Ment Dis 182:157-63 • Finney J, Hahn A, Moos R. 1996. The Effectiveness of inpatient and outpatient treatment for alcohol abuse: the need to focus on mediators and moderators of setting effects. Addiction 91(12):1773-96 • Greenwood G, Woods W, Guydish J, Bein E. 2001. Relapse outcomes in a randomized trial of residential and day drug abuse treatment. J Sub Abuse Treatment 20: 15-23 • McKay J, Alterman A, McLellan T, Boardman C, Mulvaney F, O’Brien C. 1998. Random versus nonrandom assignment in the evaluation of treatment for cocaine abusers. J Consulting and Clinical Psychology 66(4):697-701 • McKay J, Donovan D, McLellan T, Krupski A, Geary K, Cecere J. 2002. Evaluation of full vs. partial continuum of care in the treatment of publicly funded substance abusers in washington state. Am J Drug Alcohol 28(2):307-38 Health Economics Resource Center

  48. References • McLellan T, Alterman A, Metzger D, Grissom G, Woody G, Luborsky L, O’Brien C. 1994. Similarity of outcome predictors across opiate, cocaine, and alcohol treatments: role of treatment services. J Consulting and Clinical Psychology 62(6):1141-58 • Mojtabai R, Graff Zavin J. 2003. Effectiveness and cost-effectiveness of four treatment modalities for substance disorders: a propensity score analysis. Health Services Research 38(1):233-59 • Newhouse J, McClellan M. 1998. Econometrics in outcomes research: the use of instrumental variables. Annu. Rev Public Health 19:17-34 • Rychtarik R, Connors G, Wirtz P, Whitney R, McGillicuddy N, Fitterling J. 2000. Treatment settings for persons with alcoholism: evidence for matching clients to inpatient versus outpatient care. J Consulting and Clinical Psychology 68(2):277-89 • Schneider R, Mittelmeier C, Gadish D. 1996. Day versus inpatient treatment for cocaine dependence: an experimental comparison. J Ment Health Admin 23(2):234-45 • Weithmann G, Hoffman. 2005. A randomised clinical trial of in-patient versus combined day hospital treatment of alcoholism: primary and secondary outcome measures. Eur Addict Res 11:197-203 Health Economics Resource Center

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