Modelling Accessibility to General Hospitals in Ireland

Transcription

1 Modelling Accessibility to General Hospitals in Ireland Stamatis Kalogirou 1,*, Ronan Foley 2 1. National Centre for Geocomputation, John Hume Building, NUI Maynooth, Maynooth, Co. Kildare, Ireland, Tel: , Fax: , Stamatis.Kalogirou@may.ie, Web: 2. Department of Geography, National University of Ireland Maynooth, Maynooth, Co. Kildare, Ireland, Ronan.Foley@may.ie 1. Introduction The Irish Government is currently in the process of planning the strategic reformation of the existing structure of general hospital services across the country. This process has been developed through a series of government reports, mostly notably the Hanly Report of 2003 (Department of Health and Children, 2003). The essential thrust of the Hanly Report is to suggest planned efficiency changes in current general hospital provision based around expanding existing large regional centres (Major Hospitals) while downgrading some subregional hospitals centres (Local Hospitals). To date, virtually no geographical modelling has been carried out at a national level in Ireland with regard to the existing system of general hospital provision. It is imperative therefore, that spatial models of geographical access are developed and form the foundation of subsequent modelling of the proposed new structure. From a policy perspective, this may also prove valuable in the light of considerable local resistance to the proposed hospital changes, a factor common in most change environments (Brownell et. al, 2001; Luo and Wang, 2003). As an exemplar of this process, this paper aims to model existing access to general hospital services (using the elderly population as a sample sub-group) and to then model some scenarios as to how the planned changes may affect accessibility. 2. Literature Review There is a considerable literature on the measurement and modelling of accessibility to health care facilities in different parts of the developed world with a variety of methods used. These range from the original seminal work of Joseph and Phillips (1984) to recent studies in the UK, South Africa, the US and Australasia (Bhana and Pillay, 1998; O Dwyer and Burton, 1998; Rushton, 1999; Phillips et. al. 2000, Lovett et. al., 2002). The work of Brabyn and Skelly (2002) in New Zealand is of a particular relevance to an Irish case study. This is because it identifies rural/urban issues in a country of similar size, geography and demographic structure. The issues of physical distance, travel time and the distribution of the existing primary and secondary services are all identified as key variables in any GIS modelling (Rushton, 1999; Phillips et. al, 2000; Haynes et. al, 2003). While these different GIS based approaches have been widely used elsewhere, data and information restrictions have prevented its extensive use in Ireland. To date, virtually no spatial modelling has been presented or published, at least in the area of health care planning. Such basic modelling is required to stimulate GIS use within Ireland. However, the need for small area geographical analysis, including measurements of access to health services has been explicitly identified in the new strategic document on health information in Ireland (Department of Health and Children, 2004). This represents a valuable opportunity for GIS analysts to work explicitly in a series of applied health planning settings.

2 3. Methodology and Data The initial data sets chosen for the modelling were drawn from a number of sources. The data on the distributions of elderly populations were collected from the 2001 Census. The choice of the elderly is based on the fact that they as a population sub-group are the highest users of acute services and account for a significant proportion of demand for health services (Hirshorn and Stewart, 2001). Demographic data used at both Health Board/Authority and Electoral Division (ED) geographical level. The location of all 40 General Hospitals in the country was mapped incorporating data on bed size to give an indication of the relative size of the hospitals (Figure 1). Additional data on the major road network for the country were also incorporated into the GIS. A simple straight-distance model to measure access to services for people aged 65 and over has been developed. Initially, a distance grid was created which classified each 100m cell in terms of their distance to a general hospital. This was overlaid with a map showing the proportion of the local population aged 65 and over represented by ED centroids. By breaking down the distance units into 5 kilometre bands, the proportion of elderly population falling within each band was calculated. The modelling initially took 30 kilometres (approximately 30 minutes travel time) as an appropriate cut-off point for access to general hospitals and mapped the proportion and location of elderly populations who lived in less accessible areas. As a second phase to the modelling, the planned revisions suggested in the Hanly Report, which re-classified the existing 40 hospitals into their new Major and Local hospital status were also modelled and the results compared. 4. Results The results of the initial modelling phase identified significant gaps along the rural western seaboard as well as in remoter rural areas in the mid-west, west and central Munster and, most surprisingly, in south east Leinster. While many of these areas were mountainous and sparsely populated, they were also the places where elderly population were perceived to be more generally vulnerable (Figure 2). As this initial modelling was used to identify the existing situation pre-hanly, this methodology was also used to postulate some accessibility models through the reclassification of several of the existing general hospitals. These subsequent iterations identified reduced accessibility, particularly in the Mid-West region.

3 Figure 1. Location of Hospitals and Health Boards

4 Figure 2. Access Buffer Zones and Elderly Populations

5 5. Discussion and Conclusion Based on these models, the limited accessibility was spatially identified as being not hugely dissimilar to the simplistic initial model. There were a number of problems with these types of modelling and drawing from the existing literature these are rooted in firstly, the technical issues associated with modelling point and areal vector data and secondly, the difficulties of representing the complexities of population health need and demand (Weber and Kwan, 2002; McLafferty, 2003). By modelling the accessibility of those aged 65 and over, some valuable information will be gleaned on the spatial implications of the Hanly Report, which could in time be extended to other population groups such as young children, or those at high risk of degenerative disease. As a third iteration, greater sophistication could also be introduced to the model by taking into account hospital size (based on number of beds) and additional district and community hospital provision. However, we would argue that without even this initial simplistic modelling, that the spatial implications of major strategic decisions in acute service delivery are inadequately developed and that even to carry out such modelling provides the planners with some plausible and realistic outcomes with which to refine their planning in the face of general public resistance. 6. References BHANA, A. and PILLAY, Y.G., Use of the Geographical Information System (GIS) to determine potential access and allocation of public mental health resources in KwaZulu-Natal. South African Journal of Psychology, 28, 4, pp BRABYN, L. and SKELLY, C., Modelling population access to New Zealand public hospitals. International Journal of Health Geography, 1, 1, pp BROWNELL, M., ROOS, N. and ROOS, L., Monitoring health reform: a report card approach. Social Science & Medicine, 52, 5, pp DEPARTMENT of HEALTH and CHILDREN, Report of the National Task Force on Medical Staffing (Hanly Report). Dublin, Government Publications Office. DEPARTMENT of HEALTH and CHILDREN, Health Information: A National Strategy. Dublin, Government Publications Office. HAYNES, R, LOVETT, A. and SUENNENBERG, G., Potential accessibility, travel time and consumer choice: geographical variations in general medical practice registrations in Eastern England. Environment and Planning A, 35, pp HIRSHORN, B.A. and STEWART, J.E., Use of GIS for planning and service delivery to at-risk older populations. Gerontologist, 41, SI 1, p JOSEPH, A. E. and PHILLIPS, D. R., Accessibility and utilization: Geographical perspectives on health care delivery. New York, Harper & Row. LOVETT, A., HAYNES, R., SUENNENBERG, G. and GALE, S., Car travel time and accessibility by bus to general practitioner services: a study using patient registers and GIS. Social Science & Medicine, 55, 1, pp LUO, W. and WANG, F., Measures of spatial accessibility to health care in a GIS environment: synthesis and a case study in the Chicago region. Environment and Planning B, 30, pp MCLAFFERTY, S.L., GIS and health care. Annual Review of Public Health, 24, pp O'DWYER, L. and BURTON, D., Potential meets reality: GIS and public health research in Australia. Australian and New Zealand Journal of Public Health, 22, 7, pp PHILLIPS, R.L., KINMAN, E.L., SCHNITZER, P.G., LINDBLOOM, E.J. and EWIGMAN, B., Using geographic information systems to understand health care access. Archives Of Family Medicine, 9, 10, pp

6 RUSHTON, G., Methods to evaluate geographic access to health services. Journal of Public Health Management and Practice, 5, 2, pp WEBER, J. & KWAN, M.P., Bringing time back in: A study on the influence of travel time variations and facility opening hours on individual accessibility. Professional Geographer, 54, 2, pp Biography Dr Kalogirou is a research associate in the National Centre for Geomputation, NUI Maynooth, Ireland. He has a computing and geography background. His research areas are spatial analysis, migration modelling, population ageing and GIS. He is currently doing research for policy making mainly in population geography.