Cost of diabetes: comparison of disease-attributable and matched cohort cost estimation methods.

OBJECTIVE: To estimate and compare the annual direct healthcare cost among Type 1 (T1DM) and Type 2 (T2DM) diabetes patients using two cost estimation methods: (1) DM-attributable cost and (2) all cause case-control cost. RESEARCH DESIGN AND METHODS: An administrative claims cohort study using the HealthCore Integrated Research Database (HIRD(R)) identified T1DM and T2DM patients age >or=18 and <65 years between 1/1/2006 - 12/31/2006. DM patients (cases) were matched 1:1 with non-DM patients (controls) by age, gender, state, and commercial plan type (HMO, PPO, POS). All patients had continuous eligibility for calendar years 2006-07. DM-attributable cost was assessed by summing medical claims for DM (ICD-9-CM codes 250.xx) and pharmacy claims for anti-hyperglycemic agents, and all cause health care cost was assessed for cases and controls, for the calendar year 2007. RESULTS: A total of 12,096 T1DM and 256,245 T2DM cases and matched controls were identified. T1DM and T2DM cases had significantly higher average baseline comorbidities and Deyo-Charleson Comorbidity scores than controls (2.17 vs. 0.23 and 1.62 vs. 0.39, respectively, p < 0.0001 for both).While DM attributable cost estimation resulted in a mean annual cost of $6247 for T1DM and $3002 for T2DM in 2007, the mean annual (per patient) all-cause total cost estimation using the case-control method resulted in a difference of $10,837 ($14,060 for cases, vs. $3223 for controls) for T1DM; and $4217 ($8070 for cases, vs. $3853 for controls) for T2DM. CONCLUSIONS: The DM-attributable cost method underestimated costs by 42% for T1DM and 29% for T2DM compared to the case-control method. The difference was smaller but still significant (33% for T1DM and 14% for T2DM) when multivariate technique was used. Patients with DM may use a substantial amount of medical and pharmacy services not directly attributable to DM, and attributable cost method may underestimate the total cost of DM. This study has limitations inherent to the retrospective claims data analysis and generalizability of results is limited to those from similar population.

Patient characteristics, drug adherence patterns, and hypoglycemia costs for patients with type 2 diabetes mellitus newly initiated on exenatide or insulin glargine.

OBJECTIVE: Examine real-world effectiveness and hypoglycemia cost burden in patients with type 2 diabetes newly initiated on exenatide or insulin glargine. DESIGN AND METHODS: Retrospective cohort study describing patient characteristics, drug adherence patterns, and 1-year hypoglycemia rates with associated costs using an administrative claims database. Adult subjects with type 2 diabetes had an initial claim for exenatide or insulin glargine between May 1, 2005 and June 30, 2007, and had continuous eligibility for >or= 6 months pre- and >or= 12 months post-initiation. RESULTS: The exenatide cohort (n = 3262) was 53 +/- 10 years (+/-SD); 54% female. The insulin glargine cohort (n = 3038) was 56 +/- 12 years; 41% female. The mean Deyo-Charlson comorbidity index score was 1.45 for exenatide versus 1.82 for insulin glargine (p < 0.001). Baseline OAD use rates for exenatide and insulin glargine, respectively, were 77% versus 69% metformin; 47% versus 65% sulfonylurea; 50% versus 49% thiazolidinedione; 56% versus 60% multiple OAD. For patients with two or more pharmacy claims for exenatide or insulin glargine, the 12-month medication possession ratio (MPR) was 68 +/- 29% for exenatide and 58 +/- 28% for insulin glargine (p < 0.001). MPR >or= 80% was higher for exenatide (p < 0.001) and fewer patients discontinued therapy (p < 0.001). The probability of a hypoglycemic event was significantly lower for exenatide (p < 0.005), resulting in lower associated annual costs. CONCLUSIONS: This study provides the first real-world observational comparison of type 2 diabetes patients newly initiated on exenatide or insulin glargine. Exenatide patients had a lower comorbidity burden, better drug adherence, and a lower rate of hypoglycemic events with associated costs. Retrospective database analyses examine medical care utilization in large populations using a relatively inexpensive and expedient approach. However, data are only representative of a commercial health-care plan with limited information on multiple variables usually collected during clinical trials.