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使用单一机构与全州范围的入院、出院、转院数据筛选高需求人群。

Screening for the High-Need Population Using Single Institution Versus State-Wide Admissions Discharge Transfer Feed.

作者信息

Balucan Francis Salvador, French Benjamin, Shi Yaping, Kripalani Sunil, Vasilevskis Eduard E

机构信息

Vanderbilt University Medical Center.

Vanderbilt University.

出版信息

Res Sq. 2023 Mar 16:rs.3.rs-2565761. doi: 10.21203/rs.3.rs-2565761/v1.

Abstract

BACKGROUND

Access to programs for high-needs patients depending on single-institution electronic health record data (EHR) carries risks of biased sampling. We investigate a statewide admissions, discharge, transfer feed (ADT), in assessing equity in access to these programs.

METHODS

This is a retrospective cross-sectional study. We included high-need patients at Vanderbilt University Medical Center (VUMC), who were 18 years or older, with minimum three emergency visits (ED) or hospitalizations in Tennessee from January 1 to June 30, 2021, including at least one at VUMC. We used the Tennessee ADT database to identify high-need patients with at least one VUMC ED/hospitalization, then compared this population with high-need patients identified using VUMC's Epic EHR database. The primary outcome was the sensitivity of VUMC-only criteria for identifying high-need patient when compared to statewide ADT reference standard.

RESULTS

We identified 2549 patients that had at least one ED/hospitalization and were assessed to be high-need based on the statewide ADT. Of those, 2100 had VUMC-only visits, and 449 had VUMC and non-VUMC visits. VUMC-only visit screening criteria showed high sensitivity (99.1%, 95% CI: 98.7% - 99.5%), indicating that the high-needs patients admitted to VUMC infrequently access alternative systems. Results demonstrated no meaningful difference in sensitivity when stratified by patient's race or insurance.

CONCLUSIONS

ADT allows examination for potential selection bias when relying upon single-institution utilization. In VUMC's high-need patients, there's minimal selection bias when relying upon same-site utilization. Further research needs to understand how biases may vary by site, and durability over time.

摘要

背景

依赖单机构电子健康记录数据(EHR)为高需求患者提供服务项目存在抽样偏差风险。我们调查了全州范围的入院、出院、转院信息(ADT),以评估获取这些服务项目的公平性。

方法

这是一项回顾性横断面研究。我们纳入了范德比尔特大学医学中心(VUMC)的高需求患者,这些患者年龄在18岁及以上,在2021年1月1日至6月30日期间在田纳西州至少有3次急诊就诊(ED)或住院治疗,其中至少有1次在VUMC。我们使用田纳西州的ADT数据库来识别至少有1次VUMC急诊/住院治疗的高需求患者,然后将该人群与使用VUMC的Epic EHR数据库识别出的高需求患者进行比较。主要结局是与全州ADT参考标准相比,仅基于VUMC标准识别高需求患者的敏感性。

结果

我们确定了2549名至少有1次急诊/住院治疗且根据全州ADT被评估为高需求的患者。其中,2100名仅在VUMC就诊,449名在VUMC和非VUMC均有就诊。仅VUMC就诊筛查标准显示出高敏感性(99.1%,95%CI:98.7% - 99.5%),表明入住VUMC的高需求患者很少使用其他系统。结果表明,按患者种族或保险分层时,敏感性没有显著差异。

结论

ADT可用于检查依赖单机构利用率时潜在的选择偏差。在VUMC的高需求患者中,依赖同一地点的利用率时选择偏差最小。需要进一步研究以了解偏差如何因地点而异以及随时间的持续性。

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