Predicting high utilization of emergency department services among patients with a diagnosis of psychosis in a Medicaid managed care organization

Studies have demonstrated increased utilization of medical services for patients with behavioral health diagnoses. Medicaid managed care organizations (MMCOs) that operate under behavioral health carve-outs face the challenge of effectively targeting disease management initiatives in the absence of information on behavioral diagnoses. This study sought to develop a predictive model of emergency department (ED) utilization for patients where a diagnosis of psychosis could be identified from a claim associated with a medical service provider visit. A retrospective cohort analysis was performed using medical and pharmacy claims from an MMCO in Philadelphia, Pennsylvania, to identify patients known to have a diagnosis of psychosis and to develop the predictive model. Demographics, comorbidities, medical utilization, and medications were assessed as predictor variables. Within the MMCO, 764 members were identified with at least one medical claim having a psychosis diagnosis. Ordinary least squares multiple regression analysis was performed to measure the correlation between independent variables and ED visits. Variables with significant F ratios in the regression analysis were retained as factors in a risk model to evaluate their additive and cumulative effects. Four variables were significant predictors of high ED utilization: prior number of ED visits, prior number of hospitalizations, history of alcohol abuse, and history of depression. ED utilization increased as the number of risk factors increased: With no risk factors, mean ED use was 0.58 visits (per 6 months), while the cumulative effects of all four factors equated to 8.5 ED visits. The model may be useful to other MMCOs, or similar organizations, seeking to risk-stratify their ED-related disease management activities for patients identified with psychosis

39 THE ROLE OF PHARMACEUTICALS IN MENTAL HEALTH CARE OUTCOMES

This chapter discusses the role of pharmaceutical outcome evaluations in mental health care. The first section discusses the importance of pharmaceutical outcome evaluations. The second section describes techniques used in economic evaluations of pharmaceuticals (i.e., pharmacoeconomic methods). The final section discusses how mental health care outcomes data may be used in practice. WHY OUTCOMES? The idea that outcomes associated with the provision of health care are important is not new. In the 1960s Avedis Donabedian (1) presented health outcomes as changes in health status that were attributable to antecedent health care. For many years, however, evaluations of health care focused on the structure or process of care. As health care moves into the new millennium, financing of health care is evolving from individual providers being solely responsible for patient outcomes to an environment where payers, institutions, and providers are being held accountable for quality and cost of care. As financing of health care has moved to a more centralized locus of control, evaluation of outcomes has become more feasible and desirable. In a book titled Who Shall Live, Victor Fuchs (2) discussed three factors that can be balanced in our health care system: costs, quality, and access. Over time the pendulum swings from one to another of these dimensions. If costs containment goes too far, then quality or access may suffer. Likewise, i

Outcomes and Costs of Risperidone versus Olanzapine in Patients with Chronic Schizophrenia or Schizoaffective Disorders: A Markov Model

AbstractObjectiveTo compare expected outcomes and costs of care in patients with chronic schizophrenia or schizoaffective disorders who are treated with risperidone versus olanzapine.MethodsA Markov model was developed to examine outcomes and costs of care in patients with chronic schizophrenia or schizoaffective disorders receiving risperidone or olanzapine. The time frame of interest was 1 year. The model focused particular attention on the likelihood of therapy switching and discontinuation as a result of treatment-emergent side effects, as the efficacy of these two agents is similar. Measures of interest included the incidence of relapse and selected side effects including extrapyramidal symptoms (EPS), prolactin-related disorders and diabetes, expected change in body weight, and the percentage of patients remaining on initial therapy at the end of 1 year. Costs of antipsychotic therapy and psychiatric and nonpsychiatric services also were examined.ResultsAt 1 year, the rate of EPS was estimated to be slightly higher for risperidone, as was the incidence of symptomatic prolactin-related disorders. The expected incidence of diabetes mellitus, while low, was slightly higher for olanzapine. Approximately 25% and 4% of olanzapine and risperidone patients, respectively, were projected to experience an increase in body weight ≥ 7%. The estimated percentage of patients remaining on initial therapy at the end of 1 year was higher for risperidone than olanzapine (76.9% vs. 45.6%, respectively). Expected mean total costs of care per month of therapy were $2163 for risperidone and$2316 for olanzapine. Results from sensitivity analyses suggest that the probability of therapy discontinuation following weight gain > 5 kg would have to be lower than 0.1 for the number of patients remaining on therapy at the end of 1 year to be the same for risperidone and olanzapine.ConclusionsCompared with risperidone, treatment with olanzapine may result in greater increases in body weight, higher rates of therapy discontinuation, and higher costs of medical-care services