Clinical peripherality: development of a peripherality index for rural health services.


Swan, GM; Selvaraj, S; Godden, DJ; (2008) Clinical peripherality: development of a peripherality index for rural health services. BMC Health Serv Res, 8. p. 23. ISSN 1472-6963 DOI: https://doi.org/10.1186/1472-6963-8-23

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Abstract

BACKGROUND: The configuration of rural health services is influenced by geography. Rural health practitioners provide a broader range of services to smaller populations scattered over wider areas or more difficult terrain than their urban counterparts. This has implications for training and quality assurance of outcomes. This exploratory study describes the development of a "clinical peripherality" indicator that has potential application to remote and rural general practice communities for planning and research purposes. METHODS: Profiles of general practice communities in Scotland were created from a variety of public data sources. Four candidate variables were chosen that described demographic and geographic characteristics of each practice: population density, number of patients on the practice list, travel time to nearest specialist led hospital and travel time to Health Board administrative headquarters. A clinical peripherality index, based on these variables, was derived using factor analysis. Relationships between the clinical peripherality index and services offered by the practices and the staff profile of the practices were explored in a series of univariate analyses. RESULTS: Factor analysis on the four candidate variables yielded a robust one-factor solution explaining 75% variance with factor loadings ranging from 0.83 to 0.89. Rural and remote areas had higher median values and a greater scatter of clinical peripherality indices among their practices than an urban comparison area. The range of services offered and the profile of staffing of practices was associated with the peripherality index. CONCLUSION: Clinical peripherality is determined by the nature of the practice and its location relative to secondary care and administrative and educational facilities. It has features of both gravity model-based and travel time/accessibility indicators and has the potential to be applied to training of staff for rural and remote locations and to other aspects of health policy and planning. It may assist planners in conceptualising the effects on general practices of centralising specialist clinical services or administrative and educational facilities.

Item Type: Article
Faculty and Department: Faculty of Infectious and Tropical Diseases > Dept of Clinical Research
PubMed ID: 18221533
Web of Science ID: 253539700001
URI: http://researchonline.lshtm.ac.uk/id/eprint/7739

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