不具代表性、无效及误导:选择性入院的轮候时间是否计算错误?

P W Armstrong
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引用次数: 0

摘要

论文:英国政府统计局报告了在英国,病人被列入NHS等候名单后3个月内,选择性“入院”的百分比。该百分比是根据横断面数据计算得出的,使用指定日历期间内的可选事件总数作为分母,将在等待名单上登记的少于3个月的事件数作为分子。这种方法假设NHS的等待名单是封闭和固定的人口,并被英国和其他地方的政府和非政府研究人员广泛使用。反题:很少有人注意到当等候名单既不固定也不关闭时所带来的偏见。本文确定了被排除在政府统计局使用的分母之外的四组患者,并批评了忽略左和右审查观察的既定方法。综合:我们描述了两个可供选择的公式,如果轮候名单是封闭和平稳的,它们将给出与政府统计服务方法相同的结果,但当轮候名单是开放和非平稳的,它们也会给出公正的结果。他们需要有限数量的额外横断面数据来对所列人员的累积录取可能性进行上限和下限估计。我们建议通过将周期生命表技术应用于完整和一致的“自入组以来的时间”来产生无偏估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unrepresentative, invalid and misleading: are waiting times for elective admission wrongly calculated?

Thesis: The UK Government Statistical Service reports the percentage of elective 'admissions' that took place in England within 3 months of a patient being added to NHS waiting lists. This percentage is calculated from cross-sectional data using the total number of elective episodes within a specified calendar period as denominator and the number of these enrolled on the waiting list less than 3 months previously as numerator. This approach assumes that NHS waiting lists are closed and stationary populations, and has been widely used by government and non-government researchers in the UK and elsewhere.

Antithesis: Little attention has been given to the bias introduced when waiting lists are neither stationary nor closed. This paper identifies four groups of patients which are excluded from the denominator used by the Government Statistical Service and criticises the established method of ignoring left and right censored observations.

Synthesis: We describe two alternative formulae that would give the same results as the Government Statistical Service method if waiting lists were closed and stationary, but that also give unbiased results when waiting lists are open and non-stationary. They require a limited amount of additional cross-sectional data to produce upper and lower estimates of the cumulative likelihood of admission among those listed. We recommend the production of unbiased estimates by applying period life-table techniques to a complete and consistent set of 'times since enrolment'.

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