1. 1 EPI235: Epi Methods in HSR April 24, 2007 L7 Program Evaluation with Longitudinal Data 3: Two case studies (Dr. Schneeweiss) Dr. Schneeweiss will illustrate a time series approach to evaluate health care cost- containment programs with longitudinal claims databases using the example of a Reference Drug Program in British Columbia. Using a formulary restriction for respiratory drugs he will illustrate the design and analytic issues of a randomized versus an observational analysis based on longitudinal data. Background reading: Schneeweiss S, Walker AM, Glynn RJ, Maclure M, Dormuth C, Soumerai SB: Outcomes of reference drug pricing for angiotensin-converting enzyme inhibitors in British Columbia, Canada. N Engl J Med, 2002; 346:822-829. Schneeweiss S, Maclure M, Carleton BC, Glynn RJ, Avorn J. Clinical and economic consequences of a reimbursement restriction of nebulised respiratory therapy in adults: direct comparison of randomised and observational evaluations. Br Med J 2004;328:560-4.

2. 2 Case Study 1 Evaluating a Reference Drug Program

3. 3 Reference Drug Pricing in British Columbia Reference price (dhp CCBs: $31 per 30 days supply) Paid by drug benefits program Out-of-pocket contribution Total drug price Better name: Therapeutic MAC (maximum allowable cost) $0 $31 $50 RP is not a pricing policy but a reimbursement policy

4. 4 Reference Pricing in British Columbia  RP for ACEI also in 1997  Captopril, Quinapril, and Ramipril fully covered  Enalapril required cost-sharing by patients  RP for dhp-CCBs in 1997  Felodipine fully covered  Nifedipine, amlodipine, nicardipine required cost-sharing by patients

5. 5 RP in BC and other jurisdictions?  Reference Pricing was suggested to contain cost for a Medicare drug benefits program. Huskamp HA, Rosenthal MB, Frank RG, Newhouse JP. Health Affairs 2000;19:8-23. Kanavos P, Reinhardt U. Health Affairs 2003;22(3).  Germany was the first jurisdiction with RP. However, there were no evaluations of clinical consequences and net savings. Schneeweiss S, Schoffski O, Selke GW. Health Policy 1998;44(3):253-60.

6. 6 Study Population  All residents of British Columbia >65 covered by Pharmacare plan A, the state wide pharmaceutical benefits program (1/2 million). Study Question  Clinical and economic consequences?

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11. 11 Things that can go wrong

12. 12 Things that can go wrong

13. 13 Things that can go wrong

14. 14 Things that can go wrong

15. 15 Things that can go wrong

16. 16 Things that can go wrong

17. 17 Changes in ACE inhibitor Utilization Schneeweiss et al. J Can Med Assoc, 2002

18. 18 Expenditures for additional visits in prevalent ACEI users Baseline level Additional expenditures for visits: $700,000 Schneeweiss et al. N Engl J Med 2002 Schneeweiss et al. J Clin Epi 2002

19. 19 Reduced time between visits in patients who switched ACE inhibitors Schneeweiss et al. J Am Geriatr Assoc 2002

20. 20 No increase in Emergency Hospitalizations due to RP Schneeweiss et al. N Engl J Med 2002

21. 21 No effect on other health services  We concluded in earlier work that there is no increase in the incidence of hospital admissions or emergency room hospitalizations.  No effect on admissions to long-term care facilities.  No effect on mortality. Schneeweiss et al. N Engl J Med 2002

22. 22 Key Conclusions (Safety)  Reference pricing is a confusing name.  Better: “Therapeutic MAC”  A safe implementation of RP requires  to identify clusters of therapeutically equivalent drugs (“T-MAC cluster”) according to the best available evidence  to allow for generous exemptions for clinical reasons  There is increasing evidence that Reference pricing is safe:  No substitution  No severe adverse health outcomes  No increased discontinuation rates

23. 23 Reduced spending for Antihypertensives after RP for ACEI users 12 month savings: $6,700,000 Schneeweiss et al. J Can Med Assoc, 2002

24. 24 Pharmacy savings in incident ACEI users 12 month savings: $200,000 24 month savings: $800,000

25. 25 Administrative costs

26. 26 ACE-I prices after Reference Pricing Schneeweiss et al. Med Care 2004

27. 27 Net health care savings Schneeweiss et al. Med Care, 2004

28. 28 Net Health Plan Savings Schneeweiss et al. Med Care 2004

29. 29 Key Conclusions ($$)  All savings from the perspective of a comprehensive health insurance  RP for ACE inhibitors provided $5.8 million net savings during the first year (6%)  RP for dhp CCBs provided net savings of $1.6 million Schneeweiss et al. Med Care, in press

30. 30 Case Study 2 Presenting results of a PPI therapeutic substitution policy to health plan managers

31. 31 Tele-Briefing for Pharmacare & COMPUS  For chit-chat, networking, call in 5 min early  1pm (East): Chair greeting, announcemt (1 min)  Speaker(s) introduce self, topic (1-2 min)  Main take-home message & advice (1-2 min)  Observations, results (2-5 min)  What we did, project, methods (2-5 min)  Context, background (1-4 min)  Questions, discussion: please state your name  Session is recorded for limited-access by Web Slide 1

32. 32 Division of Pharmacoepidemiology and Pharmacoeconomics Department of Medicine, Brigham and Women’s Hospital Harvard Medical School (Abstract published at: Clin Pharm Ther 2005;77:P1) Slide 2 Clinical and economic consequences of a therapeutic substitution policy for PPIs Sebastian Schneeweiss, MD, ScD Nov. 28, 2005

33. 33 Implications [Conclusions]  Therapeutic substitution for PPIs can play an important role in containing drug costs  Substantial net savings, no adverse health outcomes  Results are likely to vary by drug class Slide 3

34. 34 Results: 1) 50% of PPI users switched to preferred PPI Slide 4 $35/month $61 - $90

35. 35 Results: 2) No increase in stopping of PPIs 3) More starting on preferred PPI Slide 5

36. 36 Results: 4) No increase in adverse GI effects3) Short-term increase in visits Slide 6

37. 37 Safety results in numbers: Slide 7

38. 38 Results: 6) At least $2.9 million net savings in the first 6 months Slide 8

39. 39 Methods: PPI utilization data  Individual level data from all British Columbia seniors  Linking All pharmacy dispensings (PharmaNet) Medical services, hospitalizations, and vital stats  Main outcome variable: GI complications (power to show +-24 cases/m) Drug spending (plan and patients)  Time trend analyses are least prone to bias Slide 9

40. 40 Background: Therapeutic substitution  Logic extension of generic substitution  Is based on therapeutic equivalence of drugs in group  PPIs ideal examples because very homogeneous group of drugs  Similar policies: Reference Drug Programs RDP for ACE, CCB, nitrates, and NSAIDs in British Columbia Slide 10

41. 41 Background: Implementation Issues  Need to be careful establishing therapeutic equivalence  Works only if several alternatives are available  Works best if preferred drug is a lot less costly  Single drug markets:  Combine with PA programs  Aim to ensure that patients with specific indications receive drugs Slide 11

42. 42 Summary & Questions  Substantial and rapid change in utilization  No increase in discontinuations  No increase in adverse GI outcomes  Substantial savings  Homogeneous groups like PPI are ideal  Careful expansion to more groups Slide 12

43. 43 Case Study 3 Randomized policy trial vs. quasi- experimental time trend analyses

44. 44 … or randomization? Time Intervention Intervention group Control group R Assumptions for causal inference: 1. Subjects comply with their assigned ‘treatment’ = policy

45. 45 Research question  Will we observe the same effects of a formulary restriction using  A) a randomized trial design vs.  B) a state-of-the-art observational design recommended and used by policy evaluation researchers? Soumerai et al. Milbank, 1993

46. 46 Case study: A Formulary restriction for nebulized respiratory drugs  Nebulized drugs were no longer covered by PharmaCare, B.C., after March 1,1999 but were fully covered before  10% of physicians were randomized to be exempted from the restriction for 6 months (=randomized controls)  10% of physicians who were subject to the restriction were matched by location and volume (=intervention group) Schneeweiss, BMJ under review

47. 47 Figure 1: Pairs of smaller more remote communities from which one was randomly selected to be a control

48. 48 Figure 2: A pair of urban physician addresses (marked +) from which one was randomly selected to be a control

49. 49 Evaluation  Study subjects  Patients with at least 2 nebulizer dispensings from same study physician before the formulary restriction  386 control patients; 449 intervention patients  Longitudinal claims data for entire province:  Rate of physician visits  Rate of ER hospitalizations  $$ for nebulized drugs  $$ for inhalers Outcome measures

50. 50 Design

51. 51 Randomized analysis Intervention group Control group Difference  $10

52. 52 Observational analysis: 4,625 patients not involved in randomized design Historical controls Intervention group Difference  $20

53. 53 Randomized analysis: 60% of control patient were non-compliant! Intervention group Control group

54. 54 Physician visit rate

55. 55 ER hospitalization rate

56. 56 Key results Outcomes per month Randomized analysis Observational analysis Corrected for non- compliance $$ for nebulizer-$8.2-$24 **-$21 1 $$ for inhaler$1.1$2.8 ** ER hospitalization-0.4/1000.4/100 Visits6.2/1002.6/100 ** p < 0.0001 (bootstrap estimate) 1 Zelen, Biometrics 1991

57. 57 Figure 7: Comparison of Treatment and Control Group Quality of Life

58. 58 Weighing the benefits of randomized and non-randomized drug policy research Randomization Observation Upfront investment for planning and implementation Must overcome resistance Shows commitment for ongoing evaluation Easy and fast to analyze ‘Convincing’ results No upfront investment necessary Provides valid results if carefully done Complex statistical adjustment necessary Harder to communicate results Easy to communicate results Therefore often criticized for being biased

59. 59 This is all much better than this: Time Intervention

60. 60