DTA

Digital Theses Archive

 

Tesi etd-10112017-104145

Type of thesis
Perfezionamento
Author
CALOVI, MARTINA
URN
etd-10112017-104145
Title
Healthcare and disaster management. A geographical approach
Scientific disciplinary sector
SECS-P/08
Course
SCIENZE ECONOMICHE E MANAGERIALI - Management
Committee
relatore Dott.ssa SEGHIERI, CHIARA
Keywords
  • Nessuna parola chiave trovata
Exam session start date
;
Availability
completa
Abstract
The thesis focuses on the role of geography and the geographical instruments in the healthcare and disaster management. The aim of each papers presented is to descend the concepts of health, healthcare and disaster management through the geography's lenses and instruments. The main concept that links all the three research papers is accessibility, accessibility to health care services and to services devote to help people during extreme weather events. The first paper presents the two step floating catchment area method used to calculate an accessibility index to the outpatient services in Tuscany. The index has been used then to simulate the closure or the fusion of clinics in order to simulate a reorganization of the entire outpatient service system. The second paper, rethink the accessibility in terms of patients’ choice, investigating the role of proximity. The dataset used is the 2015 individual-level administrative care outpatient, from which it has been extracted the first elective non-emergency cardiological visits data, characterizing each patient by age, sex, migrant status and level of income. The accessibility index calculated in the first paper has been proposed as a choice variable. . With this study, we want to rationally analyze the choices of the patients in order to put their needs to the center of the entire health care system. Moreover, this analysis can be used to optimize the allocation of resources, reduce inequities in access care services and increase the responsiveness and quality of outpatient systems. The third paper, look at the accessibility to the so called cooling centers, opened when an extreme heat wave occurs in Manhattan, New York City. The first important step of this research was to use a revised Analog Ensemble algorithm downscaling the temperature and the relative humidity at a higher spatial and temporal resolution. The created high resolution maps have been compared with socio-economic data, in order to identify neighbors and people that are more at risk. The output is combined with socioeconomic and healthcare data to better understand population vulnerability patterns, health risks related to exposure to extreme heat conditions, and address the knowledge gap in urban vulnerability. An accessibility simulation to the cooling centers has been run, in order to understand the spatial distribution pattern of these services in the area of Manhattan. This understanding will allow to support and improve current operational risk management techniques, and propose new practical solutions to better prepare for extreme heat events.
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