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利用行政健康记录识别心血管死亡的算法的有效性:一项基于多数据库的人群队列研究。

Validity of an algorithm to identify cardiovascular deaths from administrative health records: a multi-database population-based cohort study.

机构信息

Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.

Center for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, Quebec, Canada.

出版信息

BMC Health Serv Res. 2021 Jul 31;21(1):758. doi: 10.1186/s12913-021-06762-0.

Abstract

BACKGROUND

Cardiovascular death is a common outcome in population-based studies about new healthcare interventions or treatments, such as new prescription medications. Vital statistics registration systems are often the preferred source of information about cause-specific mortality because they capture verified information about the deceased, but they may not always be accessible for linkage with other sources of population-based data. We assessed the validity of an algorithm applied to administrative health records for identifying cardiovascular deaths in population-based data.

METHODS

Administrative health records were from an existing multi-database cohort study about sodium-glucose cotransporter-2 (SGLT2) inhibitors, a new class of antidiabetic medications. Data were from 2013 to 2018 for five Canadian provinces (Alberta, British Columbia, Manitoba, Ontario, Quebec) and the United Kingdom (UK) Clinical Practice Research Datalink (CPRD). The cardiovascular mortality algorithm was based on in-hospital cardiovascular deaths identified from diagnosis codes and select out-of-hospital deaths. Sensitivity, specificity, and positive and negative predictive values (PPV, NPV) were calculated for the cardiovascular mortality algorithm using vital statistics registrations as the reference standard. Overall and stratified estimates and 95% confidence intervals (CIs) were computed; the latter were produced by site, location of death, sex, and age.

RESULTS

The cohort included 20,607 individuals (58.3% male; 77.2% ≥70 years). When compared to vital statistics registrations, the cardiovascular mortality algorithm had overall sensitivity of 64.8% (95% CI 63.6, 66.0); site-specific estimates ranged from 54.8 to 87.3%. Overall specificity was 74.9% (95% CI 74.1, 75.6) and overall PPV was 54.5% (95% CI 53.7, 55.3), while site-specific PPV ranged from 33.9 to 72.8%. The cardiovascular mortality algorithm had sensitivity of 57.1% (95% CI 55.4, 58.8) for in-hospital deaths and 72.3% (95% CI 70.8, 73.9) for out-of-hospital deaths; specificity was 88.8% (95% CI 88.1, 89.5) for in-hospital deaths and 58.5% (95% CI 57.3, 59.7) for out-of-hospital deaths.

CONCLUSIONS

A cardiovascular mortality algorithm applied to administrative health records had moderate validity when compared to vital statistics data. Substantial variation existed across study sites representing different geographic locations and two healthcare systems. These variations may reflect different diagnostic coding practices and healthcare utilization patterns.

摘要

背景

心血管死亡是基于人群的新医疗干预或治疗研究(如新型处方药物)中的常见结局。生命统计登记系统通常是特定原因死亡率信息的首选来源,因为它们可以获取关于死者的经过核实的信息,但它们可能并非始终可用于与其他人群数据来源进行链接。我们评估了应用于基于人群数据的行政健康记录以识别心血管死亡的算法的有效性。

方法

行政健康记录来自关于钠-葡萄糖共转运蛋白 2(SGLT2)抑制剂的现有多数据库队列研究,这是一类新型抗糖尿病药物。数据来自加拿大五个省份(艾伯塔省、不列颠哥伦比亚省、马尼托巴省、安大略省、魁北克省)和英国临床实践研究数据链接(CPRD)的 2013 年至 2018 年期间。心血管死亡率算法基于从诊断代码和特定的院外死亡中识别的院内心血管死亡。使用生命统计登记作为参考标准,计算心血管死亡率算法的敏感性、特异性、阳性预测值(PPV)和阴性预测值(NPV)。计算了总体和分层估计值及其 95%置信区间(CI);后者是根据地点、死亡地点、性别和年龄得出的。

结果

该队列纳入了 20607 名患者(58.3%为男性;77.2%≥70 岁)。与生命统计登记相比,心血管死亡率算法的总体敏感性为 64.8%(95%CI 63.6,66.0);特定地点的估计值范围为 54.8%至 87.3%。总体特异性为 74.9%(95%CI 74.1,75.6),总体阳性预测值为 54.5%(95%CI 53.7,55.3),而特定地点的阳性预测值范围为 33.9%至 72.8%。心血管死亡率算法的院内死亡敏感性为 57.1%(95%CI 55.4,58.8),院外死亡敏感性为 72.3%(95%CI 70.8,73.9);特异性分别为 88.8%(95%CI 88.1,89.5)和 58.5%(95%CI 57.3,59.7)。

结论

与生命统计数据相比,应用于行政健康记录的心血管死亡率算法具有中等有效性。来自不同地理位置和两个医疗保健系统的研究地点存在显著差异。这些差异可能反映了不同的诊断编码实践和医疗保健利用模式。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6968/8325284/cd1ff7386fe0/12913_2021_6762_Fig1_HTML.jpg

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