Abstract

This Correspondence is accompanied by the following article: Dexter F. Hours of cases to schedule to rarely have overrun. Eur J Anaesthesiol 2012; 29:108. Editor, We thank Dexter1 for the interest shown in our article2 and, particularly, we agree with the author's observations on modelling gap times. In our article, we acknowledged the role of the author's previous work3 in developing the model. However, it was not clear to us that the two further articles quoted in the author's letter4,5 were of direct relevance to the problem, so we are grateful for the clarification. Yet, even on re-reading these two articles with some care, it remains difficult for us to see their direct utility. For example, the first of the articles4 appears to compare actual anaesthesia times with those of expert estimates. We need something different for our purposes which is a simple graph showing that a novel scheduling system yields fewer over-runs or under-runs than any current system, but such a plot is absent from the article by Dexter et al.4 The second article by Dexter et al.5 appears to investigate the optimal scheduling of certain milestones in a patient pathway and coordinate these better with other appointments on the same date. Dexter states in his letter that ‘the maximum probability of list over-run was set at 20%’, but we cannot find specific reference to this cut-off in the article by Dexter et al.5 Again, we can find no explicit data presented in the article to indicate that any models described reduced the occurrence of under-runs or over-runs. Undoubtedly, these two additional articles are interesting and helpful,4,5 but we think there may be additional reasons for their limited application to the problems we describe in the National Health Service (NHS).2 Generally, these articles by Dexter et al. address situations in which patients arrive for surgery at staggered intervals throughout the day and each surgical team has a variable allocation of theatre time from day to day, or week to week. Potential surgical capacity outstrips actual demand, so efficiency is best achieved by tailoring actual capacity to current demand. In the NHS, actual capacity is fixed and always overwhelmed by demand.6 Patients generally all arrive at the same time in the morning and patiently wait all day until their surgery. Each surgical team has a fixed allocation of theatre time. The problem of achieving efficiency is a much simpler one of ensuring that the demand on any given day (i.e. the number of patients brought in for surgery) best matches the fixed capacity available.7,8 None of the tables of results or graphs in the articles quoted by Dexter help us directly to address this last problem, so work such as ours is essential to make progress for our situation.2

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