Jae Jin An, Ph.D. Michael B. Nichol, Ph.D.

Transcription

1 IMPACT OF MULTIPLE MEDICATION COMPLIANCE ON CARDIOVASCULAR OUTCOMES IN PATIENTS WITH TYPE II DIABETES AND COMORBID HYPERTENSION CONTROLLING FOR ENDOGENEITY BIAS Jae Jin An, Ph.D. Michael B. Nichol, Ph.D. Clinical Pharmacy and Pharmaceutical Economics & Policy Department of Pharmacy University of Southern California ISPOR 16 th Annual International Meeting

2 Outline Background Objective Methods Data Study Population Statistical Methods Results Conclusions Limitations 2

3 Background Diabetes (DM) is an extremely common and costly chronic disease, affecting nearly 8% of the total population in the U.S. Besides the diabetes related complications, 75% of adults had hypertension (HTN) (American Diabetes Association, 2007). Patients with both DM and HTN conditions are required to use multiple medications. The presence of the two diseases and their treatments are associated with a significantly increased risk of cardiovascular mortality and morbidity. 3

4 Background The impact of medication compliance on health outcomes can be investigated using retrospective claims data. However, parameter estimates are likely to be biased in the presence of potential endogeneity. Severe patients would be more compliant with their medications, and then the impact of compliance may be underestimated. Health service seeking patients would be more compliant with their medications, and then the impact of compliance may be overestimated. Endogeneity bias can be controlled using instrumental variables. 4

5 Objective To investigate the impact of multiple medication compliance on the occurrence of cardiovascular complications using instrumental variables (IV) to control for endogeneity bias. 5

6 Methods: Data Source Administrative Claims Data from a Large Physician Group in Southern California Eligibility and Enrollment History Medical Service Claims Pharmacy Claims Electronic Medical Records Clinical Lab Test Values 6

7 Methods: Study Population Inclusion Criteria Index date: First prescription date of either DM or HTN meds during 7/1/2006 6/30/2007 Pre-index period (6 months) Post-index period (33 months) Group 1 (New DM) Group 2 (New HTN) Group 3 (New DM and HTN) Pre-existing Hypertension (Pharmacy Claim) New Diabetes (Pharmacy Claim) New Hypertension Pre-existing Diabetes New Hypertension New Diabetes 7

8 Methods: Study Population Inclusion Criteria 18 years of age or older Continuous eligibility during the study period At least two prescription fills during the post-index period Exclusion Criteria Insulin or inhaler users at baseline and/or post-index period Presence of cardiovascular complications during the preindex period 8

9 Methods: Study Variables Dependent Variable (Binary) Occurrence of major cardiovascular complications using ICD- 9 and CPT codes (=1) Multiple Medication Compliance (Continuous) Proportional Days Covered (PDC) for both simultaneously available oral DM and HTN medications for 33 months of post-index period Covariates Patient demographics: age, gender, health plan, pre-existing condition Severity related factors: number of DM and HTN medications, clinical measures (HbA1C, Blood Pressure, Lipid level), Elixhauser comorbidity 9

10 Methods: Statistical Analyses Descriptive Statistics T-test and Chi-square Tests Probit Model Controlling for observable characteristics Instrumental Variables (IV) - Probit Model Controlling for both observable and unobservable characteristics applying IVs which satisfies relevancy and exogeneity conditions 10

11 Methods: Instrumental Variables Physician related instrumental variables were constructed assuming that patients select their physicians independently of their practice pattern and a physician's practice pattern is unrelated to their use of other medical interventions that might directly influence the outcome. Relevancy and Exogeneity Tests First Stage F statistics (Stock-Yogo table) Shea s R square (p<0.05) Hansen J statistics overidentification test (p>0.05) Wald test of exogeneity (p<0.05) Durbin-Wu-Hausman test (p<0.05) 11

12 Methods: Instrumental Variables IV1: The proportion of follow-up visit per index physician (j) IV2: The proportion of statin prescription during 6 months preindex and 3 months of post-index period per index physician (j) IV3: Dummy for the same prescribers for both disease medications at baseline 12

13 Results: Baseline Characteristics Variables (mean, sd) New DM (N=1,246) New HTN (N=727) New DM and HTN (N=378) Total (N=2,351) Age 63.7 (0.4) 58.7 (0.5) 57.5 (0.7) 61.2 (0.3) Male (%) 45.3% 52.1% 55.9% 49.1% Health care plan (%) Commercial 45.9% 56.0% 58.7% 51.1% Medicare 46.9% 35.5% 34.4% 41.3% Health severity during pre-index Number of Elixhauser comorbidity 1.6 (0.03) 1.5 (0.04) 1.3 (0.05) 1.50 (0.02) HbA1C controlled (%) 41.3% 39.5% 33.6% 39.5% Blood pressure controlled (%) 12.1% 11.3% 6.6% 11.0% Low Density Lipoprotein controlled (%) 29.2% 30.0% 23.3% 28.5% High Density Lipoprotein controlled (%) 37.2% 39.2% 29.6% 36.6% Triglyceride controlled (%) 33.9% 36.7% 32.5% 34.6% Healthcare utilization during pre-index Pharmacy cost ($) 680 (1031) 547 (1050) 124 (673) 550 (1007) Outpatient cost ($) 42 (107) 33 (70) 21 (52) 36 (90) Hospital length of stay 0.2 (0.9) 0.1 (0.7) 0.2 (0.1) 0.2 (0.9) Clinical outcomes during post-index Cardiovascular complication rate (%) 26.4% 23.7% 25.4% 25.4% First cardiovascular complication date 475 (306) 472 (324) 412 (350) 464 (319) 13

14 Results: Medication Compliance Mean Proportion of Days Covered for the 33 Months Post Index Period Patients were more compliant with their pre-existing condition s medications when they had both diabetes and hypertension (p<0.001). When both medications were taken at the same time, the differences in compliance between the two conditions were not significant (p<0.001)

15 Results: Medication Compliance Quarterly Medication Compliance by Group New DM (N=1,246) New HTN (N=727) New DM and HTN (N=378) Compliance with newly started medications dropped significantly in the first quarter (p<0.001) and compliance levels were maintained

16 Results: Probit vs IV-Probit Dependent Variable: Occurrence of cardiovascular complications Models Covariates Compliance Coefficient Standard error p-value Probit None Age Age, gender, health plan, preexisting conditions Severity (clinical measure) IV-Probit +Severity (clinical measure) <0.001 After controlling for observable characteristics, the impact of compliance was statistically insignificant (-0.001±0.10, p=0.990). However, after controlling for both observable and unobservable characteristics, compliance was associated with a significant reduction of cardiovascular complication rates (-1.90±0.53, p<0.001). 16

17 Results: Different Sets of IVs IV Compliance First stage Shea R Durbin-Wu- Hansen J Wald test Coeff. SE F-statisticǂ squareǂ Hausmanǂ statisticǂ exogeneity IV1-2.84*** ** ** IV IV3-2.18*** ** ** IV1, IV2-2.22*** ** * IV1, IV3-2.41*** *** *** IV2, IV3-1.90*** ** ** IV1, IV2, IV3-2.10*** ** ** * p-value <0.05, ** p-value <0.01, *** p-value <0.001, ǂ Statistics were from linear model, SE=Standard error. The results were robust by choosing any combination of three IVs. Final model included IV2 and IV3 as IV1 was redundant. IVs were satisfied identification test criteria. 17

18 Results: Probability of Outcome Compliance Probability of Cardiovascular Complications At Mean Covariates 50% 0.31*** (0.03) 60% 0.26*** (0.01) 70% 0.21*** (0.01) 80% 0.17*** (0.02) 90% 0.13*** (0.02) 100% 0.10** (0.03) ** p-value <0.01, *** p-value <0.001, ( ) are standard errors. Multiple medication compliance was associated with the reduction of probability of cardiovascular complications. The probability of cardiovascular complications was reduced from 0.31 (±0.03) to 0.17 (±0.02) as compliance increased from 50% to 80%

19 Conclusions Compliance with medications for DM and HTN differed when the patient had both conditions at the same time, and patients were more compliant with medications for their pre-existing condition. After controlling for observable and unobservable characteristics, medication compliance was associated with the reduction of cardiovascular complication rates. The magnitude of the compliance impact was greater after controlling for unobservables, which implies that without controlling for endogeneity, the compliance effect would be underestimated. 19

20 Limitations Medication Compliance Compliance with medications were only considered at each disease level, and composite measure of multiple medication compliance was investigated. Medication specific effects, polypharmacy issues within the disease, and compliance with other comorbid conditions have not considered. Instrumental Variables Estimates are unbiased only using valid instruments. Generalizability Study population is only from one physician group in southern California. 20