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Cumulative risk adjusted mortality chart for detecting changes in death rate: observational study of heart surgery

机译:用于检测死亡率变化的累积风险调整死亡率图表:心脏手术的观察性研究

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>Objective: To detect changes in mortality after surgery, with allowance being made for variations in case mix. >Design: Observational study of postoperative mortality from January 1992 to August 1995. >Setting: Regional cardiothoracic unit. >Subjects: 3983 patients aged 16 and over who had open heart operations. >Main outcome measures: Preoperative risk factors and postoperative mortality in hospital within 30 days were recorded for all surgical heart operations. Mortality was adjusted for case mix using a preoperative estimate of risk based on additive Parsonnet factors. The number of operations required for statistical power to detect a doubling of mortality was examined, and control limits at a nominal significance level of P=0.01 for detection of an adverse trend were determined. >Results: Total mortality of 7.0% was 26% below the Parsonnet predictor (P<0.0001). There was a highly significant variation in annual case mix (Parsonnet scores 8.7-10.6, P<0.0001). There was no significant variation in mortality after adjustment for case mix (odds ratio 1-1.5, P=0.18) with monitoring by calendar year. With continuous monitoring, however, nominal 99% control limits based on 16 expected deaths were crossed on two occasions. >Conclusions: Hospital league tables for mortality from heart surgery will be of limited value because year to year differences in death rate can be large (odds ratio 1.5) even when the underlying risk or case mix does not change. Statistical quality control of a single series with adjustment for case mix is the only way to take into account recent performance when informing a patient of the risk of surgery at a particular hospital. If there is an increase in the number of deaths the chances of the next patient surviving surgery can be calculated from the last 16 deaths. Key messages class="unordered" style="list-style-type:disc">Changes in the patient population affect a hospital’s annual death rate Year to year differences in death rate can be large even when there is no change in the underlying risk or case mix It takes surprisingly many operations before an increase in death rate can be distinguished from random fluctuation A formal inquiry should take place in a hospital if the death rate rises above control limits The chances of the next patient surviving surgery should be calculated using the surgeon’s most recent results
机译:>目的:检测手术后死亡率的变化,并考虑病例组合的变化。 >设计: 1992年1月至1995年8月术后死亡率的观察性研究。>设置:区域心胸单元。 >受试者:3983名16岁以上的患者进行了心脏直视手术。 >主要结局指标:记录所有心脏外科手术患者在30天内的术前危险因素和术后死亡率。使用术前基于累加Parsonnet因素的风险估计值来调整病因死亡率。检查了统计能力以检测死亡率增加一倍所需的操作次数,并确定了用于检测不良趋势的标称显着性水平P = 0.01的控制限。 >结果:总死亡率为7.0%,比Parsonnet预测指标低26%(P <0.0001)。年度病例组合差异很大(Parsonnet评分为8.7-10.6,P <0.0001)。在按日历年监测的情况下,对病例组合进行调整(死亡率比为1-1.5,P = 0.18)后,死亡率没有显着变化。但是,通过连续监测,两次超过了基于16个预期死亡的名义99%控制限值。 >结论:由于心脏病的死亡率之间的年度差异可能很大(优势比为1.5),即使基本风险或病例构成没有改变,医院心脏心脏病死亡率表也将具有有限的价值。在告知患者特定医院手术风险的情况下,对单个系列进行统计质量控制并调整病例组合是唯一考虑近期表现的方法。如果死亡人数增加,则可以根据最近的16例死亡来计算下一位患者幸存手术的机会。关键消息 class =“ unordered” style =“ list-style-type:disc”> <!-list-behavior = unordered prefix-word = mark-type = disc max-label-size = 0-> < li>患者人数的变化会影响医院的年死亡率 即使基本风险或病例组合没有变化,每年的死亡率差异也可能很大。 要想将死亡率的增加与随机波动区分开来,就需要进行大量的手术。 如果死亡率超过控制范围,应该在医院进行正式询问。 应使用外科医生的最新结果计算下一个幸存的患者的手术次数

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