Literature DB >> 22193828

A spatial decision support tool for estimating population catchments to aid rural and remote health service allocation planning.

Nadine Schuurman1, Ellen Randall, Myriam Berube.   

Abstract

There is mounting pressure on healthcare planners to manage and contain costs. In rural regions, there is a particular need to rationalize health service allocation to ensure the best possible coverage for a dispersed population. Rural health administrators need to be able to quantify the population affected by their allocation decisions and, therefore, need the capacity to incorporate spatial analyses into their decision-making process. Spatial decision support systems (SDSS) can provide this capability. In this article, we combine geographical information systems (GIS) with a web-based graphical user interface (webGUI) in a SDSS tool that enables rural decision-makers charged with service allocation, to estimate population catchments around specific health services in rural and remote areas. Using this tool, health-care planners can model multiple scenarios to determine the optimal location for health services, as well as the number of people served in each instance.

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Mesh:

Year:  2011        PMID: 22193828     DOI: 10.1177/1460458211409806

Source DB:  PubMed          Journal:  Health Informatics J        ISSN: 1460-4582            Impact factor:   2.681


  4 in total

Review 1.  Mobile technologies and geographic information systems to improve health care systems: a literature review.

Authors:  José António Nhavoto; Ake Grönlund
Journal:  JMIR Mhealth Uhealth       Date:  2014-05-08       Impact factor: 4.773

2.  Community readiness and momentum: identifying and including community-driven variables in a mixed-method rural palliative care service siting model.

Authors:  V A Crooks; M Giesbrecht; H Castleden; N Schuurman; M Skinner; A Williams
Journal:  BMC Palliat Care       Date:  2018-04-06       Impact factor: 3.234

3.  Distance sampling for epidemiology: an interactive tool for estimating under-reporting of cases from clinic data.

Authors:  Luca Nelli; Moussa Guelbeogo; Heather M Ferguson; Daouda Ouattara; Alfred Tiono; Sagnon N'Fale; Jason Matthiopoulos
Journal:  Int J Health Geogr       Date:  2020-04-20       Impact factor: 3.918

Review 4.  A review of rural and remote health service indexes: are they relevant for the development of an Australian rural birth index?

Authors:  Jennifer Pilcher; Sue Kruske; Lesley Barclay
Journal:  BMC Health Serv Res       Date:  2014-12-10       Impact factor: 2.655

  4 in total

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