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Evidence on NHS waiting lists – Needs cautious interpretation
- Padmanabhan Badrinath (26 January 2003)
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The NHS is still lacking in capacity
- Onisillos Sekkides (28 January 2003)
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Icy times for the NHS?
- Andrew G Thompson (29 January 2003)
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An economic perspective on NHS waiting times
- Stephen D Martin, Peter C Smith (13 February 2003)
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Padmanabhan Badrinath, Specialist Registrar in Public Health Medicine Suffolk Public Health Network & Coastal PCT, Ipswich IP3 8LS
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Dear Editor, Martin et al(1)have to be commended for their efforts to identify the factors associated with prolonged waiting by NHS patients. They have produced interesting descriptive analysis of prolonged waiting across the country by various characteristics of the trusts, which was unavailable before. How ever, as the authors have used routinely available data at institutional level and performed correlation analysis the results could be used to generate hypothesis and not to prove causality. The design could be considered as ecological. In this design as the data are not analysed at individual level for example the number of anaesthetists and not their characteristics in the analysis this could lead to ecological fallacy. An ecological fallacy may be committed when the characteristics of groups are held to convey information about individuals within groups(2). It has been shown(3)that the grade of anaesthetist influenced the duration of maxillofacial surgery. While performing dentoalvelar surgery the 'total time' for each case was increased (by about 10 minutes a patient) when a junior anaesthetist was anaesthetising rather than a consultant(3). Hence grouping all anaesthetists together may not adequately reflect the output under these circumstances. Another variable worth including is the rate of staff turnover, which affects efficiency. There is some evidence to show that external factors, particularly available resources, influence the number of patients on a surgical waiting list. Aiono et al(4) showed that providing more resources in the form of waiting list initiatives reduced both the number of people on the waiting list and the duration. They identified lack of beds and theatre sessions as the factors influencing waiting list at the local level. High risk approach to manage waiting lists as advocated by Martin et al has to be approached with caution as hospital waiting lists in the UK appears to be resistant to shortening because reductions in their length generate increased referrals(5) a form of supply induced demand. References 1)Martin RM, Sterne JAC, Gunnell D, Ebrahim S, Smith GD et al. NHS waiting lists and evidence of national or local failure: analysis of health service data. BMJ 2003;326:188. 2)http://www.radstats.org.uk/no076/spicker.htm Accessed on 26th January 2003. 3)Ogden GR, Kershaw AE, Hussein I. Use of theatre time for dentoalveolar operations under general anaesthesia. Br J Oral Maxillofac Surg 2000 ;38(4):331-4. 4)Aiono S, Faber RG, Galland RB. Surgeons have little control over general surgical waiting lists. Ann R Coll Surg Engl 2000;82(9 Suppl):304- 7. 5)Smethurst DP, Williams HC. Self-regulation in hospital waiting lists. J R Soc Med 2002 Jun;95(6):287-9 Dr.P.Badrinath, Specialist Registrar in Public Health, Suffolk Public Health Network & Coastal PCT, PO Box 170, St Clements Hospital, Foxhall Road, Ipswich IP3 8LA, UK. Competing interests: None declared |
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Onisillos Sekkides, Medical Writer/Editor TW10 6UA
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The article states "Measures of capacity (such as beds, operating theatres, doctors) and independent sector activity are not generally associated with prolonged waiting." This ignores the obvious fact that adequate nursing provision is critical to the running of any hospital. So, the article ignores the true measure of capacity within the NHS. I don't know if this would impact the authors' findings but it appears to be quite an oversight. Competing interests: None declared |
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Andrew G Thompson, Respiratory Medicine Derriford Hospital, Plymouth PL6 8DH
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I had read with interest Dr Rose’s1 comparison of the NHS with a chronic disease such as COPD (where there is a mismatch of resources and demand) and his beautifully descriptive analogy of such disease as a stone bouncing across the surface of water, where with each successive bounce, the skimmed stone or remission is lower. The extension of this analogy was that it is taking smaller and smaller emergencies for the NHS to decompensate, and soon the failing system will collapse. However perhaps the NHS has not reached such a chronic state of health yet. There is common assumption that all the problems within the NHS are a result of insufficient resources, yet Martins et al 2 have suggested that with regard to waiting lists evidence is scant that the waiting problem arises from a global mismatch between supply and demand, and can be solved either by greater rationing or by increasing NHS capacity. That therefore leaves the alternative and currently preferred method of trying to maximise what we do with the current resources, and targeting specific areas of need. Perhaps to continue Dr Rose’s analogy, the NHS is a stone thrown across an icy lake, where the stone skips for a while and then slides along a sheet of ice. We can alter the method of how the stone is thrown and the length of the ice sheet before the stone needs to sink – lets hope the stone isn’t too heavy. 1) Rose J Analogies in medicine BMJ 2003;326:111. 2)Martin RM, Sterne JAC, Gunnell D, Ebrahim S, Smith GD et al. NHS waiting lists and evidence of national or local failure: analysis of health service data. BMJ 2003;326:188. Competing interests: None declared |
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Stephen D Martin, Research Fellow University of York YO10 5DD, Peter C Smith
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Although highly topical, the paper by Martin and colleagues on NHS waiting lists illustrates the misleading policy signals that can emerge from an inadequate analytic methodology [1]. The paper finds ‘little and inconsistent support … for associations of prolonged waiting times with markers of capacity, independent sector activity, or need in the surgical specialities examined’. The hard-pressed policy maker might therefore infer that increased resources will do little to address the NHS waiting time problem. Yet an emerging economic literature, to which the authors do not refer, is suggesting quite the reverse. The key problem that this literature recognizes is that the waiting phenomenon may be the result of a subtle interaction between the demand for and supply of surgical capacity. As an illustration, one of the local policy responses to a long waiting time might be to increase capacity, at least in the short term. So there might be a positive relationship between waiting time and capacity (rather than the ‘common sense’ negative relationship). In these circumstances, it is simply not satisfactory merely to examine contemporary associations between capacity and waiting time. Such associations will reflect a jumble of demand and supply influences. A model is required that enables the analyst to disentangle demand and supply effects. We have applied these principles to two years’ data from the English Hospital Episode Statistics (HES), and find that supply is indeed strongly influenced by waiting times [2]. These findings have since been replicated on a longer time series of data, and for separate services [3]. The HES results are supported by a time series analysis of waiting list KH7 data (which examines 24 quarters, in contrast to the one quarter examined by Martin et al) [4]. As discussed in Martin and Smith [2], the implication of our work is that a permanent increase in NHS resources will contribute to a reduction in waiting times, other things being equal. It is furthermore important to acknowledge the dynamic nature of the waiting phenomenon. Van Ackere and Smith demonstrate the quite subtle paths that waiting lists and capacity might take over time [5,6]. Unless handled very carefully, cross sectional analysis of the sort used by Martin et al, which fails to distinguish between supply and demand effects, is unlikely to yield useful results. Martin et al are gracious enough to include a long list of limitations of their study in their paper and we, too, acknowledge that our work has its own limitations. However, we feel that simple cross sectional associations between waiting time and various other factors is far too flimsy a basis from which to make policy inferences, particularly when there is clear evidence that the waiting phenomenon reflects both demand side and supply side pressures. Stephen Martin
Peter C. Smith
1. Martin R M, Sterne J A C, Gunnell D, Ebrahim S, Smith G D, Frankel S. NHS waiting lists and evidence of national or local failure: analysis of health service data. BMJ, 2003; 326:188-197. 2. Martin, S. and Smith, P. (1999), “Rationing by waiting lists: an empirical investigation”, Journal of Public Economics, 71, 141-164. 3. Martin, S. and Smith, P. (2003), “Using panel methods to model waiting times for NHS surgery”, Journal of the Royal Statistical Society, Series A, forthcoming. 4. Gravelle, H., Smith, P. and Xavier, A. (2003), “Performance signals in the public sector: the case of health care”, Oxford Economic Papers, 55(1), 81-103. 5. Van Ackere, A. and Smith, P. (1999), “Towards a macro model of National Health Service waiting lists”, System Dynamics Review, 15(3), 225 -252. 6. Smith, P. and van Ackere, A. (2002), “A note on the integration of system dynamics and economic models”, Journal of Economic Dynamics and Control, 26(1), 1-10. Competing interests: Our work on waiting times has been funded by the Department of Health. |
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