Analysis of healthcare utilization patterns and adherence in patients receiving typical and atypical antipsychotic medications.

OBJECTIVE: To examine the effects of typical and atypical antipsychotics on medication adherence and healthcare resource utilization. RESEARCH DESIGN AND METHODS: This was a retrospective observational cohort analysis of pharmacy and medical health insurance reimbursement data of patients from a southeastern United States health plan. Pharmacy data of subjects between 6 and 65 years of age were identified. Inclusion criteria included initiation of a single antipsychotic agent between July 1, 1999 and September 30, 2000; no antipsychotic medication usage 6 months prior to the index prescription date; and continuous health plan enrollment for the 18-month study period. Multivariable methods were utilized to analyze healthcare resource utilizations between groups. OUTCOME MEASURES: Primary outcome measures included: (1) adherence and persistence with antipsychotic therapy; (2) healthcare utilization for outpatient office and hospital visits, inpatient hospital visits, and emergency room visits; and (3) therapy modifications and concomitant medications. RESULTS: A total of 469 patients met initial study criteria. Atypical and typical antipsychotics were prescribed to 384 and 85 patients, respectively. Length of therapy (days) for the atypical cohort was significantly longer (136 vs 80; p < 0.001). As defined using medication possession ratio (MPR), the atypical cohort was significantly more adherent to therapy than the typical cohort (mean MPR, 0.53 vs 0.24; p < 0.001). After adjusting for differences in demographics, baseline utilization, MPR, and length of therapy (n = 377), the atypical cohort experienced significantly fewer office visits (2,635 vs 4,249 per 1000 patients per month [P1000PPM]; p = 0.005), fewer inpatient admissions (197 vs 511 P1000PPM; p = 0.032), and fewer emergency room visits (125 vs 354 P1000PPM; p = 0.002). CONCLUSIONS: Atypical antipsychotic users were significantly more adherent to therapy, and had lower rates of office, hospital and emergency room utilization. Within the context of inherent limitations associated with health insurance claims databases, this study suggests that a relationship exists across cohorts between medication adherence and use of healthcare resources.

Gender bias in lipid assessment and treatment following percutaneous coronary intervention.

OBJECTIVE: To identify a possible gender bias in lipid assessment and treatment of patients following percutaneous coronary intervention (PCI). METHODS: Following PCI, patients were identified from a cardiology practice database, with retrospective follow-up achieved through medical record review in a private cardiology practice and in primary care physician practices. Patients were assessed for lipid measurement of total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides, and for changes in these measures. RESULTS: A total of 356 patients were identified for analysis: 221 men (62%) and 135 women (38%). Mean post-PCI follow-up was 2.2 +/- 1.6 years. Among females, 80% had lipids measured, as compared with 87% of males (P = 0.07). At pre- and post-PCI, all fractions were significantly higher (P < 0.05) in women, except pre-PCI triglycerides, which were significantly lower in women. From pre- to post-PCI, HDL-C and triglycerides improved significantly more in males, while LDL-C improved significantly more in females. Target LDL-C levels (< 100 mg/dL) were achieved in 46.4% of the overall group. There were no significant gender-related differences in the number of patients treated with dyslipidemic medications or in patients achieving an LDL-C of < 100 mg/dL (P = 0.081). CONCLUSION: Following PCI, a gender bias did not exist for lipid assessment, number of patients treated with pharmacotherapy, or achievement of target LDL-C (< 100 mg/dL). However, in terms of absolute levels achieved, women were treated less aggressively than men for all lipid fractions.