Geographic information systems (GIS): an emerging method to assess demand and provision for rehabilitation services

Abstract

GIS provides a set of tools for describing and understanding the spatial organization of the health of populations and the distribution of health services that can aid the development of health policy and answer key research questions with respect to rehabilitation health services delivery. Implications for Rehabilitation It is important to seek out alternative and innovative methods to examine rehabilitation service delivery. GIS is a computer-based program that takes any data linked to a geographically referenced location and processes it through a software system that manages, analyses and displays the data in the form of a map, allowing for an alternative level of analysis. GIS provides a set of tools for describing and understanding the spatial organization of population health and health services that can aid the development of health policy and answer key research questions with respect to rehabilitation health services delivery.

Hospital distribution in a metropolitan city: assessment by a geographical information system grid modelling approach

“…It allows researchers to analyse data in map format at various levels of geographical detail (Murad, 2008;Passalent et al, 2013). GIS is therefore a powerful tool for the assessment and analysis of health data and it affords researchers the opportunity to visualise, explore and model health issues (Graves, 2008).…”

“…GIS is therefore a powerful tool for the assessment and analysis of health data and it affords researchers the opportunity to visualise, explore and model health issues (Graves, 2008). GIS has been widely applied for analysing location issues in health services research (Walsh et al, 1997;Rosero-Bixby, 2004;Mitropoulos et al, 2006;Schuurman et al, 2008;Passalent et al, 2013) not only enabling access to information from traditional administrative boundaries, but also allowing the collection of data from areas defined by researchers.…”

Variations in demand and provision for publicly funded outpatient musculoskeletal physiotherapy services across Quebec, Canada

“…The provision of publicly funded services differed greatly from one health region to another, as shown by the large variations in the number of clinicians per population in our study. Wide variations in the density of physiotherapists were also found in other provinces, ranging approximately between 10 and 90 physiotherapists per 100 000 in Saskatchewan and between around 20 and 80 physiotherapists per 100 000 population in Ontario . Another study conducted in Ontario indicates that the density of physiotherapists working in not‐for‐profit hospitals per 100 000 population in 2005 ranged from 0.6 to 37.5, with a provincial average of 15.1.…”

Comparing geographical distribution of community‐based physiotherapists and family physicians across Saskatchewan

“…The second group is based on the spatial interaction processes (e.g., distance decay) that manipulate supply and demand data at local scales using gravity models and kernel density estimations (Joseph and Phillips ; Luo and Wang ; Guagliardo ; Schuurman et al ; Cromley and McLafferty ; McGrail ; Wang ; Neutens ). The 3SFCA method applied in this research is a gravity model that is grounded in the use of GIS technologies to enhance research in medical geography by integrating spatial and non‐spatial attribute information in one system to analyze relationships and conduct complex computational tasks related to spatial data (Wang and Luo ; Bissonnette et al ; McGrail ; Delamater ; Passalent et al ; Fransen et al ; Wang and Onega ). The 3SFCA method was applied to examine geographic distribution of PT and FP services (i.e., supply) with respect to the population (i.e., demand).…”

“…Wang 2012;Neutens 2015). The 3SFCA method applied in this research is a gravity model that is grounded in the use of GIS technologies to enhance research in medical geography by integrating spatial and non-spatial attribute information in one system to analyze relationships and conduct complex computational tasks related to spatial data (Wang and Luo 2005;Bissonnette et al 2012;McGrail 2012;Delamater 2013;Passalent et al 2013;Fransen et al 2015;Wang and Onega 2015). The 3SFCA method was applied to examine geographic distribution of PT and FP services (i.e., supply) with respect to the population (i.e., demand).…”