Evaluating the Accessibility of Healthcare Facilities Using an Integrated Catchment Area Approach

Xiaofang Pan, Mei-Po Kwan, Lin Yang, Shunping Zhou, Zejun Zuo and Bo Wan
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Xiaofang Pan: Faculty of Information Engineering, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China
Mei-Po Kwan: Department of Geography and Geographic Information Science, University of Illinois at Urbana-Champaign, Natural History Building, MC-150, 1301 W Green Street, Urbana, IL 61801, USA
Lin Yang: Faculty of Information Engineering, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China
Shunping Zhou: Faculty of Information Engineering, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China
Zejun Zuo: Faculty of Information Engineering, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China
Bo Wan: Faculty of Information Engineering, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China

IJERPH, 2018, vol. 15, issue 9, 1-21

Abstract: Accessibility is a major method for evaluating the distribution of service facilities and identifying areas in shortage of service. Traditional accessibility methods, however, are largely model-based and do not consider the actual utilization of services, which may lead to results that are different from those obtained when people’s actual behaviors are taken into account. Based on taxi GPS trajectory data, this paper proposed a novel integrated catchment area (ICA) that integrates actual human travel behavior to evaluate the accessibility to healthcare facilities in Shenzhen, China, using the enhanced two-step floating catchment area (E2SFCA) method. This method is called the E2SFCA-ICA method. First, access probability is proposed to depict the probability of visiting a healthcare facility. Then, integrated access probability (IAP), which integrates model-based access probability (MAP) and data-based access probability (DAP), is presented. Under the constraint of IAP, ICA is generated and divided into distinct subzones. Finally, the ICA and subzones are incorporated into the E2SFCA method to evaluate the accessibility of the top-tier hospitals in Shenzhen, China. The results show that the ICA not only reduces the differences between model-based catchment areas and data-based catchment areas, but also distinguishes the core catchment area, stable catchment area, uncertain catchment area and remote catchment area of healthcare facilities. The study also found that the accessibility of Shenzhen’s top-tier hospitals obtained with traditional catchment areas tends to be overestimated and more unequally distributed in space when compared to the accessibility obtained with integrated catchment areas.

Keywords: healthcare accessibility; catchment areas; access probability; taxi GPS trajectories; E2SFCA (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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