Econometric methods for secondary data in health research

Abstract

This dissertation integrates econometric methods into the multidisciplinary field of health research. Applied econometric methods commonly used in academic economic research are powerful tools that can optimize the use of secondary data. This dissertation applies these tools in four independent chapters that are specifically targeted to government policy decision makers. The first chapter applies the instrumental variable regression models to study the relationship between Canadian Obesity and income and finds evidence of inequity in the context of public health. The second chapter studies the relationship between vitamin D and various mental health indicators while expanding ordered logistic regression models with margin effects. The results from this chapter can be used as a promotional tool as an interim solution for vitamin D deficiencies in Canada. The third chapter studies the acute myocardial infarction key performance indicator that has been mandated by the Alberta Ministry of Health and Wellness government department through an economic lens. The final chapter validates the CMG+ costing estimate of acute myocardial infarction for the province of Alberta. Each chapter incorporates a unique use-case for government decision makers as well as incorporates applied econometrics to optimize secondary data for health research targeted to these decision makers.