PMH19: RISK OF HOSPITALIZATION FOR PATIENTS WITH BIPOLAR DISORDER

Abstract

OBJECTIVES: Health care utilization for patients with bipolar disorder has received limited attention. This study utilizes medical and prescription claims data from the 1998 to mid-2000 MarketScan Databases to examine the risks of hospitalization, a major cost driver in treating bipolar patients. Hospitalizations are associated with a relapse of bipolar symptoms (often due to treatment ineffectiveness or discontinuation). METHODS: Bipolar patients are identified using diagnosis codes and prescription drug claims. An ?intent-to-treat? framework for classifying drug cohorts by initial bipolar prescription is used. Prescription claims are studied over a minimum of a six-month time period to analyze drug use patterns (e.g., switching and augmenting treatment). Descriptive profiles of the bipolar patients are presented. Cox proportional hazard models are used to examine the relationships among observable patient characteristics, drug choice, drug use patterns, and hospitalizations. This method accounts for the potential bias in parameter estimates due to data censoring. RESULTS: Among patients with at least 6-months of follow-up data (n = 6,536), the mean age is 43 years old and 63.3% are female. The majority of patients are initially observed on antimanic medications, with lesser percentages on other common pharmacological therapies (typical and atypical antipsychotics, and antiepileptics). During the 6-month follow-up, 14.5% of patients have at least one hospitalization and 7.2% have at least one bipolar-related hospitalization. During a 12-month follow-up, 23.3% have at least one hospitalization of any type and 11.5% have at least one bipolar-related hospitalization. The unadjusted risk of hospitalization increases over time, at a decreasing rate. CONCLUSION: The high incidence of hospitalization demonstrates the need for effective treatment options. This study also illustrates the importance of accounting for censored data to obtain unbiased estimates of factors associated with the risk of hospitalization.