Healthcare Consequences Associated With Non-Compliance in a Managed Care Population Ethel S. Siris, M.D. 1, Ankita Modi, Ph.D. 2, Jackson Tang, M.Sc. 3, Shuvayu Sen, Ph.D. 2 1 Columbia University Medical Center, NY Presbyterian Hospital, 2 Global Health Outcomes, Merck & Co., NJ, 3 AsclepiusJT LLC, NY Healthcare Consequences Associated With Non-Compliance in a Managed Care Population Ethel S. Siris, M.D. 1, Ankita Modi, Ph.D. 2, Jackson Tang, M.Sc. 3, Shuvayu Sen, Ph.D. 2 1 Columbia University Medical Center, NY Presbyterian Hospital, 2 Global Health Outcomes, Merck & Co., NJ, 3 AsclepiusJT LLC, NY Table 1. Baseline patient characteristics by non-compliance Conclusions Rate of non-compliance was found to be as high as 60% in a managed care population with osteoporosis. Non-compliant patients were 19% more likely to experience a higher risk of OP-related fracture The inpatient cost in osteoporosis is the single largest contributor for total osteoporosis related medical costs. In non-compliant patients, all-cause hospitalization risk was 16.4% higher, hospitalization episodes were 26.0% higher, and OP-related hospitalization episodes were 10.7% higher. The results emphasize the importance of good treatment compliance in order to achieve a treatment benefit. Improving medication compliance in patients with osteoporosis may lead to a greater reduction in fracture and related hospitalization risk. Introduction More than 40 million people in the US have osteoporosis (OP) or are at risk of developing OP, placing them at greater risk of osteoporotic fractures. Poor compliance with OP treatment regimens is a well-recognized problem, and the risk of having OP-related fractures may increase among patients with poor compliance. 1 Higher medical utilization and costs is a consequence of poor compliance. 2 Objective To examine consequences associated with non-compliance with OP medications in terms of fracture rates and healthcare resource uses in a US managed care population. Methods Study design A retrospective cohort study was conducted using i3 Invision Datamart; a large U.S. claims database records from January 1, 2001 to December 31, 2010 (study window). Disease diagnoses and comorbidities were identified based on ICD-9 codes, medications were identified based on NDC codes. Index date: The initiation date of the first OP medication (alendronate, ibandronate, risedronate, zoledronic acid, raloxifene, calcitonin, teriparatide) during the study window. Time periods: Three 1-year time periods were considered (Figure 1):  Baseline period: 1 year before the index date.  Compliance period: Year 1 after index date, during which medication possession ratio (MPR) was calculated and treatment non-compliance with OP treatment was determined.  Study period: Year 2 after index date, during which OP-related fractures and healthcare resource uses were measured. Non-compliance: Patients with MPR<80% were considered non-compliant.  MPR was defined as the total number of days’ supply of all OP medications received in the compliance period, divided by 365 days. For IV therapy, 1 prescription of zoledronic acid was assumed to be equivalent to 365 days of supply, while IV ibandronate was equivalent to 90 days of supply.  A sensitivity analysis with MPR<60% as non-compliant was also conducted. Outcomes studied: 1.OP-related fractures. Included fractures occurred at the hip, vertebral, and non- vertebral sites, during the study period. 2.Healthcare resource uses. Included all-cause and OP-related healthcare resource uses by service type (inpatient, emergency room (ER), outpatient and other), during the study period.  All-cause: All healthcare services incurred during the study period.  OP-related: Healthcare services associated with a primary or secondary diagnosis of OP or OP-related fractures during the study period.  An inpatient/ER episode consists of inpatient/ER services on consecutive days. Two distinct episodes are at least 1-day apart. Descriptive analysis Comparisons between non-compliant and compliant patients. χ 2 (chi-squared) tests for binary/categorical variables, t-tests for continuous variables. Baseline period:  Baseline patient characteristics included age, Charlson comorbidity index (CCI), baseline fractures and concomitant medication use (Table 1). Study period:  OP-related fractures (Table 2) o Fracture rates (the percentage of patients with fractures), overall and by fracture sites. Regression analysis To assess and quantify the association between non-compliance and all-cause/OP- related healthcare resource use and OP fractures, adjusted for baseline patient characteristics. Key independent variable: non-compliance (MPR < 0.8) Covariates: age, CCI, baseline presence of gastrointestinal (GI) symptoms, OP-related fractures and other comorbid conditions. Regression model:  Logistic regression to model fracture rates (Table 3) and rates of all-cause/OP-related resource utilization (Yes/No) (Table 4).  Poisson regression to model frequencies of all-cause/OP-related healthcare events (i.e. number of episodes/events) (Table 5). Poster Session I ID: SA0393 Results Descriptive analysis Among 57,913 women who met eligibility criteria, 34,483 (59.5%) were non- compliant with OP therapy in the compliance period (mean [SD] age, 64.2 [8.9] years). [Table 1] A significant higher proportion of non-compliant patients developed OP-related fractures of any type (3.14% vs. 2.24%); vertebral (0.79% vs. 0.48%), hip (0.42% vs. 0.25%) and non-vertebral (1.93% vs.1.52%) than compliant patients in the study period. [Table 3] Sensitivity analysis using MPR<0.6 as non-compliance showed comparable results, with 26,340 (45.5%) being non-compliant to OP therapy Regression analysis Non-compliance was associated with higher risk of OP-related fractures.  19.1%, 42.9%, and 46.6% more likely to experience any fractures, vertebral, and hip fractures, respectively [Table 3]. Non-compliance was associated with higher risk of all-cause hospitalizations.  All-cause hospitalization risk was 16.4% higher in non-compliant vs. compliant patients ( [Table 4] OR: 1.164; 95% CI: [1.10, 1.23]; p< 0.01) Non-compliance was associated with higher number of all-cause and OP-related hospitalization episodes.  All cause hospitalization episodes were 26.0% higher in non-compliant vs. compliant patients ( [Table 5] IRR:1.260; 95% CI: [1.19, 1.34]; p< 0.01).  OP-related hospitalization episodes were 10.7% higher in non-compliant vs. compliant patients ( [Table 5] IRR:1.107; 95% CI: [0.97, 1.26]; p= 0.12). N = 686,505 Patients initiating OP treatment Index date was defined as the initiation date of the first OP medication N= 488,361 Women 55 years of age or older as of index date N = 87,235 With > 12-months continuous eligibility before and > 24-months continuous eligibility after the index date N = 57,913 Exclude patients with malignant neoplasm or Paget’s disease of bone TOTAL SAMPLE = 57,913 Non-compliant (N = 34,483) [59.5%] Compliant (N = 23,430) [40.5%] P-value BaselineN%N% Age at index date (mean, std) <0.01 Charlson comorbidity index (mean, std) <0.01 Baseline fractures1,5664.5% %<0.01 Vertebral (dorsal/lumbar) % % 0.01 Hip (femur neck) % % 0.06 Other (non-vertebral)1,0213.0% %<0.01 Baseline medication use Gastro-protective agents6, %3, %<0.01 Estrogen use7, %6, %<0.01 Non-steroid anti-inflammatory drugs use 9, %5, %<0.01 Table 2. Unadjusted association of fracture rates and non-compliance Non-compliant (N = 34,483) [59.5%] Compliant (N = 23,430) [40.5%] P-value Number of patients with OP- related fractures N%N% Any OP-related fractures1, <0.01 Vertebral (dorsal/lumbar) <0.01 Hip (femur neck) Other (non-vertebral) <0.01 Table 3. Adjusted association of fracture rates and non-compliance Table 4. Adjusted association of healthcare utilization and non-compliance Table 5. Adjusted association of healthcare events and non-compliance Disclosure Dr. Ethel Siris: Scientific expert and consultant to Merck. Ankita Modi: Employee – Merck & Co. Jackson Tang: Consultant – Received research funding from Merck & Co. Shuvayu Sen: Employee – Merck & Co. Presented at The American Society for Bone and Mineral Research (ASBMR) 2013 Annual Meeting, Baltimore, MD, October 4 – 7, 2013 MPR calculated Study period (12-months) Baseline period (12-months) Compliance period (12-months) OP-related fractures and resource utilization assessment Index Date Initiation of OP medication Naive to all OP treatment Figure 1. Study Timeframe Sample selection Limitations Noncompliance was determined by pharmacy dispense data, which may not accurately reflect a patient’s actual compliance with the prescribed OP treatment. Healthcare services that were 100% covered by Medicare were not captured due to nature of the claim data. Unadjusted analysis comparing compliant and non-compliant groups may be confounded by the differences in baseline patient characteristics. However, the confounding was mitigated by multivariate regression analysis. OP-related fractures Effects of treatment non-compliance on fracture rate OR95% CIP-value Any OP-related fractures 1.191(1.06, 1.34)<0.01 Vertebral (dorsal/lumbar) 1.429(1.14, 1.79)<0.01 Hip (femur neck) 1.466(1.07, 2.00) 0.02 Other (non-vertebral) 1.147(1.01, 1.31) 0.04 Healthcare utilization Effects of treatment non-compliance on utilization rate OR95% CIP-value All-cause healthcare utilization Inpatient1.164(1.10, 1.23)<0.01 Emergency room0.991(0.94, 1.05) 0.74 Outpatient services0.614(0.56, 0.67)<0.01 Other medical services0.935(0.90, 0.97)<0.01 OP-related healthcare utilization Inpatient1.005(0.89, 1.14) 0.94 Emergency room0.799(0.66, 0.97) 0.03 Outpatient services0.730(0.70, 0.76)<0.01 Other medical Services0.834(0.78, 0.89)<0.01 Healthcare events Effects of treatment non-compliance on usage rate IRR95% CIP-value All-cause healthcare event Inpatient1.260(1.19, 1.34)<0.01 Emergency room1.030(0.96, 1.11) 0.43 Outpatient services0.966(0.95, 0.98)<0.01 Other medical services1.099(1.06, 1.13)<0.01 OP-related healthcare event Inpatient1.107(0.97, 1.26) 0.12 Emergency room0.900(0.68, 1.18) 0.45 Outpatient services0.821(0.78, 0.86)<0.01 Other medical Services0.862(0.76, 0.97) 0.02 References 1.AnOlsen KR, Hansen C, Abrahamsen B. 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