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英国国家医疗服务体系候诊名单的起伏:招募和入院如何影响基于事件的“入院时间”长度衡量指标?

The ebb and flow of the NHS waiting list: how do recruitment and admission affect event-based measures of the length of 'time-to-admission'?

作者信息

Armstrong Paul W

机构信息

School of Health Sciences, University of East London, Romford Road, UK.

出版信息

Stat Med. 2002 Oct 30;21(20):2991-3009. doi: 10.1002/sim.1254.

Abstract

The likelihood of admission is reported in England as the percentage of elective episodes occurring within a certain time, for example, within three months of the date of enrollment on the waiting list. This event-based measure is calculated from cross-sectional data: the denominator is the number of elective episodes occurring in a specified calendar period, and the numerator is the number found to have enrolled on the waiting list less than three months previously. Now the number of elective episodes occurring within three months reflects the likelihood of admission and the numbers eligible to be admitted. If there is any increase in the likelihood of admission or in the number of people exposed to that likelihood then there will be an increase in the number of elective episodes found to have enrolled on the waiting list less than three months previously. Thus the numerator used by the Government Statistical Service accurately reflects conditions during the calendar period and within the enrollment cohorts of interest. The Government Statistical Service also needs a denominator so the episodes observed 0-2, 3-5, 6-8, 9-11 etc. months after enrollment are added as an indication of the number of people that could have been admitted within three months. This denominator implies that the number of people eligible for admission from the 3-5 month waiting time category is the same as the number surviving admission from the 0-2 month waiting time category but, during the period of interest, these two groups of people belong to cohorts that were recruited to the waiting list quite independently. As a result, this denominator will be too big if the number surviving to the end of one waiting time category is bigger than the number eligible for admission from the next and it will be too small if the number surviving to the end of one waiting time category is smaller than the number eligible for admission from the next. The event-based measure assumes that the waiting list is stationary and closed and only gives unbiased estimates under these conditions. This paper describes three alternative measures which recognize that the number of people recruited or admitted may vary from one quarter to the next. It uses Department of Health data to assess the size of the error if the event-based measure is used in these circumstances.

摘要

在英格兰,入院可能性的报告方式是将特定时间段内(例如,在等候名单登记日期后的三个月内)发生的择期诊疗次数的百分比作为指标。这种基于事件的衡量方法是根据横断面数据计算得出的:分母是在指定日历期间发生的择期诊疗次数,分子是在不到三个月前被列入等候名单的诊疗次数。现在,三个月内发生的择期诊疗次数既反映了入院可能性,也反映了有资格入院的人数。如果入院可能性或面临该可能性的人数有所增加,那么在不到三个月前被列入等候名单的择期诊疗次数就会增加。因此,政府统计局使用的分子准确反映了日历期间以及感兴趣的登记队列中的情况。政府统计局还需要一个分母,所以要将登记后0至2个月、3至5个月、6至8个月、9至11个月等时间段内观察到的诊疗次数相加,以此作为在三个月内可能入院人数的一个指标。这个分母意味着,从3至5个月等候时间类别中有资格入院的人数与从0至2个月等候时间类别中存活到入院的人数相同,但在感兴趣的时间段内,这两组人属于完全独立被列入等候名单的队列。结果是,如果一个等候时间类别的存活人数大于下一个等候时间类别中有资格入院的人数,这个分母就会太大;反之,如果一个等候时间类别的存活人数小于下一个等候时间类别中有资格入院的人数,这个分母就会太小。基于事件的衡量方法假定等候名单是固定且封闭的,并且只有在这些条件下才能给出无偏估计。本文描述了三种替代衡量方法,这些方法认识到招募或入院的人数可能每个季度都有所不同。本文利用卫生部的数据来评估在这些情况下使用基于事件的衡量方法时误差的大小。

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