 Modelling waiting times for elective surgeryStephen Martin and
Peter Smith ()
No 024cheop, Working Papers from Centre for Health Economics, University of York Abstract: Throughout the first 25 years of the NHS there were, at any point in time, about half a million people waiting for hospital treatment in England. Over the next two decades this figure doubled, and waiting times have become a subject of great public concern. Partly in response to this concern, the Government has launched various initiatives to reduce the time that patients have to wait for treatment, most recently in the Patient’s Charter. However, despite considerable political, professional and public interest, our understanding of the determinants of waiting times remains poorly developed (Pope, 1992). In this study, in common with most commentators, we focus on waiting times for elective surgery. These are a complex phenomenon, being a function of numerous interlinked factors. It has rarely been possible to undertake empirical work within a coherent theoretical framework that permits simultaneous modelling of all the major determinants of waiting times. Usually, analysis of the phenomenon has been confined to unrealistically simple models, or of piecemeal examination of variables thought relevant to waiting times. It has hitherto proved impossible to examine the impact of one particular factor on waiting times while holding all other factors constant (see, for example, Yates, 1987). It might reasonably be assumed that the length of waiting time is related to the adequacy of resources for treatment (Sanderson, 1982). Indeed, in comparison with many other industrialised countries, the UK spends a relatively small proportion of its GDP on health (Yates, 1987, pp.30-31). However, claims that there is no straightforward relationship between resource provision and waiting times abound (for example, Frankel, 1989; Buttery and Snaith, 1979). Unfortunately, this view is usually based on simple correlations between some measure of inpatient provision and waiting times. For example, Buttery and Snaith concluded that “waiting lists are not correlated with surgical provision” (Buttery and Snaith, 1980, p.57) and Yates found “…no obvious relationship between a shortage of beds and long waiting time” (Yates, 1987, p.35). Findings such as these can be interpreted as evidence that increased funding would have little impact on waiting times and that more resources would simply induce greater demand (Pope, 1992); Roland and Morris, 1988). Indeed, some studies found no simple relationship between admissions from the waiting list and the length of the list (Goldacre et al., 1987); Henderson et al., 1995), although other studies suggest that the pool of unmet need might be smaller than previous estimates suggested (Williams et al., 1994). The common feature of all these studies is that – usually because of data limitations – they fail to model the system as a whole. Drawing in a comprehensive and previously unavailable dataset, this report seeks to contribute to the debate by modelling the interactions between factors relevant to waiting times. It constructs a model of the determinants of waiting times based on the demand for and supply of NHS inpatient health care. This framework permits us to move towards a more comprehensive analysis, in which the links between resource levels, utilisation rates and delayed access to health care can be modelled (Frankel, 1993, p.45). Although the model we present can be used to analyse the direct impact that an increase in provision is likely to have on waiting times, it can also be used to estimate the magnitude of any indirect demand effect induced by reduced waiting times. Keywords: elective; surgery (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:chy:respap:24cheop Access Statistics for this paper More papers in Working Papers from Centre for Health Economics, University of York Contact information at EDIRC. |
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