Patient choice: two essays and new statistical software package

Prior literature has recognized the importance of shedding light on how patients choose their treating provider. The health care context analysed in this work is characterized by regulated price and asymmetric information. At the same time the quality of treatment is crucial for patient's welfare. In the last decades, national health care systems had tried to respond to necessity of maximizing quality of care by enacting policies focused on giving to the patient freedom to choose their preferred providers along with the disclosure of the quality information about hospitals. Indeed, it has been recognized by past literature that freedom of choice and availability of quality information improve quality of care and lead patients to discard low-quality hospitals. The literature, however, have neglected three crucial aspects of patient choice. First, all empirical contributions aimed to understand the mechanisms of patient choice by assuming that hospitals are perceived as similar organizations. However, a recent theoretical contribution hypothesized that patients differently value health care providers and might to tend to elect a "reference hospital" which they perceive as best quality (Levaggi and Levaggi, 2017). Second, earlier research has focused on procedures supplied in a hospital setting (inpatient) or on choice of general practitioners. The outpatient sector has been overlooked, even though it is important for patient welfare and for health cost containment through prevention and early treatment. Third, the largely used econometric specifications in the discrete choice setting are based on logit models and their generalizations. Besides, it begins to be recognized that patients may be influenced by their peers (Berta et al., 2016; Moscone, Tosetti, and Vittadini, 2012) when choosing hospitals or they might be affected also by mechanism be correlated at the spatial level. Although econometric theory has provided tools for performing discrete choice analysis in a spatial framework, the software to do so are still limited. The aim of this work is to fill the above mentioned gaps and they will be approached in the following way. This chapter identifies the extant literature in patient choice and his gaps. Subsequently, Part 2 is aimed to understand whether patients elect reference hospitals by using Italian Hospital Discharge Record Data in three regions and whether the perception of patients of a reference hospital varies between different organizational market approach. Part 3 is aimed at understanding the determinants of outpatient choice and to useful policy implications by simulating a relocation of a provider. Part 4 introduces a novel Stata package, which allows to perform spatial logit analysis.