=Paper=
{{Paper
|id=Vol-1598/paper20
|storemode=property
|title=An integrated geo-spatial approach of access to public healthcare services and socio-economic analyses
|pdfUrl=https://ceur-ws.org/Vol-1598/paper20.pdf
|volume=Vol-1598
|authors=Pablo Cabrera-Barona
|dblpUrl=https://dblp.org/rec/conf/agile/Cabrera-Barona15
}}
==An integrated geo-spatial approach of access to public healthcare services and socio-economic analyses==
https://ceur-ws.org/Vol-1598/paper20.pdf
An integrated geo-spatial approach of access
to public healthcare services and socio-
economic analyses
Pablo Cabrera-Barona
Interfaculty Department of Geoinformatics - Z_GIS, University of Salzburg
Introduction
Access to health services requires a multidimensional analysis inside a holis-
tic perspective. Such a multidimensional analysis responds to the needs of a
more pluralist health geography framework and to the “cultural turn” that
studies of health accessibility are experiencing nowadays (Hawthorne &
Kwan 2012). This cultural turn needs to be reflected through a clear well-
being conceptual framework, which should combine deprivation/satisfaction
indicators with spatial accessibility measures. When considering healthcare
accessibility as a multidimensional concept, taking into consideration the per-
ceptions of patients can be a useful approach to understanding healthcare ac-
cess inequalities (Comber et al., 2011). This PhD research will fill different
gaps between qualitative and quantitative studies in order to present new
mixed-method approaches to the scientific community and to support
healthcare and urban planning. The main objective of this PhD are: (a) de-
veloping a spatial composite deprivation index related to health issues; (b)
developing composite indices related to healthcare accessibility and
healthcare satisfaction, and (c) developing a model of accessibility to
healthcare services.
Copyright (c) by the paper's authors. Copying permitted for private and academic purposes. In: A.
Comber, B. Bucher, S. Ivanovic (eds.): Proceedings of the 3rd AGILE Phd School, Champs sur
Marne, France, 15-17-September-2015, published at http://ceur-ws.org
2
Methods
The study area is the capital city of Ecuador, Quito. Quito is located around
2800 meters above sea level and is home to more than 1.5 million inhabitants.
A deprivation index was developed using indicators extracted from the 2010
Ecuadorian Population and Housing Census (Cabrera Barona et al., 2015).
The criteria used to choose the different indicators follow a rights-based per-
spective (Ramírez, 2012, Mideros, 2012). Different deprivation scenarios
were then created by applying the Ordered Weighted Averaging (OWA)
method with linguistic quantifiers’ integration (Malczewski 2006). The sec-
ond stage of this research was the creation of two indices: a composite
healthcare accessibility (CHCA) index and a composite healthcare satisfac-
tion (CHCS) index. To calculate the CHCA index, three indicators were used:
healthcare availability, healthcare acceptability, and general healthcare acces-
sibility (Cavalieri 2013). To calculate the CHCS index, three indicators were
used: the waiting time after the patient arrives at the healthcare service, the
quality of the healthcare, and the healthcare service supply. The CHCA and
CHCS indices were validated using factors of people´s behaviour related to
healthcare, namely predisposing, enabling, and need factors (Andersen 1995,
Arcury et. al 2005), by applying three kinds of regressions: Linear Least
Squares, Ordinal Logistic, and Random Forests regressions. The third stage of
this research will be the creation of a gravity-based measure of accessibility to
healthcare services (Crooks and Schuurman, 2012). The results of this meas-
ure of accessibility will be linked to the different scenarios of deprivation
through multidimensional analyses.
Preliminary Results
Results have indicated medium and high levels of deprivation only in specific
zones of the study area while most of Quito shows low values of deprivation.
The OWA deprivation scenarios represent various decision strategies that of-
fer different options when dealing with socio-economic deprivation. The
composite indices of healthcare accessibility and healthcare satisfaction iden-
tified healthcare inequalities in the study area. Regression results showed
that some social factors influence accessibility and satisfaction related to
healthcare. The use of perceptions in healthcare accessibility analyses impact-
ed the calculated measures.
3
Conclusions and Outlook
The developed indices have the potential to explain socio-economic depriva-
tion and multidimensional healthcare accessibility. This research could also
evaluate the influence of access to healthcare and socio-economic deprivation
on specific health problems or illnesses. I consider important the incorpora-
tion of more detailed information of human transit between the household and
healthcare services to improve the representation of the complex phenomenon
of healthcare accessibility. The healthcare satisfaction index and healthcare
accessibility index use information of health services supply. The health ser-
vice supply was represented by the range of services, giving higher scores to
specific health services such as specialized hospitals. However, the healthcare
supply indicator may be represented by other indicators, such as the number
of physicians in the health service. The next steps in my research will be: i)
Developing an integral analyses of health-related inequalities by using indices
of deprivation and healthcare accessibility and ii) Evaluating the scale effects
of the different measures developed.
References
Andersen, R.M. (1995) Revisiting the Behavioral Model and Access to Medical
Care: Does It Matter? Journal of Health and Social Behavior, 36, 1-10.
Arcury, T.A., Gesler, W.M., Preisser, J.S., Sherman, J., Spencer , J. & Perin, J.
(2005) The Effects of Geography and Spatial Behavior on Health Care Utilization
among the Residents of a Rural Region. Health Services Research, 40(1), 135-155.
Cabrera Barona, P., Murphy, T., Kienberger, S., Blaschke, T. (2015). A multi-
criteria spatial deprivation index to support health inequality analyses. International
Journal of Health Geographics, 14(11).
Cavalieri, M. (2013) Geographical variation of unmet medical needs in Italy: a
multivariate logistic regression analysis. International Journal of Health Geographics,
12(27).
Comber, A.J., Brunsdon, C., Radburn, R. (2011). A spatial analysis of variations in
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4
Crooks, V., Schuurman, N. (2012). Interpreting the results of a modified gravity
model: examining access to primary health care physicians in five Canadian provinces
and territories. BMC Health Services Research 12 (230).
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Mideros, A. (2012). Ecuador: defining and measuring multidimensional poverty,
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