Comparisons of Health Service Utilization, Medical Costs, and Risks of Medication Noncompliance and Suicidal Behavior among Patients with Depressive Disorders Using Different Antidepressants

According to the World Health Organization (WHO), depression is a common serious mental disorder, and it ranks fourth on the list of theWHO global burden of disease (GBD) measures. Suicide accounts for million deaths worldwide each year, and depression is one of the most important risk factors. To evaluate an effective antidepressant treatment in medical research, researchers tend to use outcome measures of reducing the risk of mortality or improving health status. In addition to mortality and morbidity, depression has profound impacts upon health care resources and medical costs. Hence, this two-year research project will provide insight information and comprehensive evaluation on understanding: (1). health service utilization and direct medical costs of patients with depressive disorders using different antidepressants; (2). the risk of medication noncompliance of those patients pertaining to types of antidepressants; and (3). the odds of suicidal behavior (attempted and completed suicide) of those patients. In this empirical research, the study population will comprise patients with a diagnosis of depressive disorders (ICD-9-CM codes: 296.2X-296.3X, 300.4, and 311.X). Antidepressants will be classified as the following sub-types: Selective serotonin reuptake inhibitors (SSRIs), Serotonin antagonists and reuptake inhibitors (SARIs), Tricyclic antidepressants (TCAs), Serotoninnorepinephrine reuptake inhibitors (SNRIs) and others. Data used in this study will be collected for the period 2010-2016 from the Health and Welfare Data Science Center (HWDC), Ministry of Health and Welfare, Taiwan. Data files in the National Health Insurance Research Database (NHIRD) and the Death Certification Registry will be linked by unique national identification numbers of the study subjects. Lastly, statistical methods will include the followings: Two-part model; Propensity score analysis; Chi-squared test or Fisher’s exact test; One-way ANOVA; Negative binomial regression model or Two-part negative binomial regression model; Ordinary least squares regression model; Cox proportional hazards model; Competing risk analysis; and Sensitivity analysis.