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从现有的数据源、概率链接和多重插补构建一个从 9-1-1 到 1 年的纵向队列:一项验证研究。

Building A Longitudinal Cohort From 9-1-1 to 1-Year Using Existing Data Sources, Probabilistic Linkage, and Multiple Imputation: A Validation Study.

机构信息

Center for Policy and Research in Emergency Medicine, Department of Emergency Medicine, Oregon Health & Science University, Portland, OR.

出版信息

Acad Emerg Med. 2018 Nov;25(11):1268-1283. doi: 10.1111/acem.13512. Epub 2018 Jul 31.

Abstract

OBJECTIVE

The objective was to describe and validate construction of a population-based, longitudinal cohort of injured older adults from 9-1-1 call to 1-year follow-up using existing data sources, probabilistic linkage, and multiple imputation.

METHODS

This was a descriptive cohort study conducted in seven counties in Oregon and Washington from January 1, 2011, through December 31, 2011, with follow-up through December 31, 2012. The primary cohort included all injured adults ≥ 65 years served by 44 emergency medical services (EMS) agencies. We used nine existing databases to assemble the cohort, including EMS data, two state trauma registries, two state discharge databases, two state vital statistics databases, the Oregon Physician Order for Life-Sustaining Treatment registry, and Medicare claims data. We matched data files using probabilistic linkage and handled missing values with multiple imputation. We independently validated data processes using 1,350 randomly sampled records for probabilistic linkage and 3,140 randomly sampled records for variables created from existing data sources.

RESULTS

There were 15,649 injured older adults in the primary cohort, with 13,661 (87.3%) total matched records and 9,337 (59.7%) matches to the index ED/hospital visit. The sensitivity of linkage was 99.9% (95% confidence interval [CI] = 99.3%-100%) for any match and 98.3% (95% CI = 96.2%-99.4%) for index event matches. The specificity of linkage was 95.7% (95% CI = 93.7%-97.2%) for any match and 100% (95% CI = 99.2%-100%) for index event matches. Name, date of birth, home zip code, age, and hospital had the highest yield for linkage. Patients with matched records tended to be higher acuity than unmatched patients, suggesting selection bias if unmatched patients were excluded. Compared to hand-abstracted values, the sensitivity of electronically derived variables ranged from 18.2% (abdominal-pelvic Abbreviated Injury Scale score ≥ 3) to 97.4% (in-hospital mortality), with specificity of 88.0% to 99.8%.

CONCLUSIONS

A population-based emergency care cohort with long-term outcomes can be constructed from existing data sources with high accuracy and reasonable validity of resulting variables.

摘要

目的

描述并验证使用现有数据源、概率链接和多重插补,从 9-1-1 呼叫到 1 年随访构建基于人群的受伤老年人纵向队列。

方法

这是一项描述性队列研究,于 2011 年 1 月 1 日至 2011 年 12 月 31 日在俄勒冈州和华盛顿州的七个县进行,随访至 2012 年 12 月 31 日。主要队列包括由 44 个紧急医疗服务 (EMS) 机构提供服务的所有≥65 岁的受伤成年人。我们使用了九个现有数据库来组建队列,包括 EMS 数据、两个州创伤登记处、两个州出院数据库、两个州生命统计数据库、俄勒冈州医生维持生命治疗医嘱登记处和医疗保险索赔数据。我们使用概率链接匹配数据文件,并使用多重插补处理缺失值。我们使用 1350 份随机抽样记录独立验证概率链接数据流程,并使用 3140 份从现有数据源创建的变量的随机抽样记录进行验证。

结果

主要队列中有 15649 名受伤老年人,共有 13661 份(87.3%)总匹配记录和 9337 份(59.7%)与索引 ED/医院就诊的匹配记录。链接的灵敏度为 99.9%(95%置信区间 [CI] 99.3%-100%),任何匹配的特异性为 95.7%(95% CI 93.7%-97.2%),索引事件匹配的特异性为 100%(95% CI 99.2%-100%)。链接的特异性为 95.7%(95% CI 93.7%-97.2%),索引事件匹配的特异性为 100%(95% CI 99.2%-100%)。姓名、出生日期、家庭邮政编码、年龄和医院对链接的产生具有最高的效果。有匹配记录的患者比无匹配记录的患者病情更严重,这表明如果排除无匹配记录的患者,则存在选择偏倚。与手动提取的值相比,电子派生变量的灵敏度范围为 18.2%(腹部-骨盆损伤严重度评分≥3)至 97.4%(住院死亡率),特异性为 88.0%至 99.8%。

结论

可以从现有数据源中构建具有高准确性和合理有效性的基于人群的急诊护理队列,并具有长期结果。

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