A Validated Electronic Medical Record-Based Algorithm to Identify Hospitalized Patients with Serious Illness.

IF 2.2 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES
Laura A Schoenherr, Yuika Goto, Joanna Sharpless, David L O'Riordan, Steven Z Pantilat
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Abstract

Background: Population-based methods to identify patients with serious illness are necessary to provide equitable and efficient access to palliative care services. Aim: Create a validated algorithm embedded in the electronic medical record (EMR) to identify hospitalized patients with serious illness. Design: An initial algorithm, developed from literature review and clinical experience, was twice adjusted based on gaps identified from chart review. Each iteration was validated by comparing the algorithm's results for a subset of patients (approximately 10% of the populations screened in and screened out on a given day) with the expert consensus of two independent palliative care physicians. Settings/Subjects: The final algorithm was run daily for nine months to screen all hospitalized adults at our academic medical center in the United States. Results: Compared with the gold standard of expert consensus, the final algorithm for identifying hospitalized patients with serious illness was found to have a sensitivity of 89%, specificity of 82%, positive predictive value of 80%, and negative predictive value of 90%. At our hospital, an average of 284 patients a day (54%) screened positive for at least one criterion, with an average of 38 patients newly screening positive daily. Conclusions: Data from the EMR can identify hospitalized patients with serious illness who may benefit from palliative care services, an important first step in moving to a system in which palliative care is provided proactively and systematically to all who could benefit.

基于电子病历的验证算法,用于识别重症住院病人。
背景:为提供公平有效的姑息关怀服务,有必要采用基于人群的方法来识别重病患者。目的:创建一种嵌入电子病历(EMR)的有效算法,以识别住院重症患者。设计:根据文献综述和临床经验开发的初始算法,根据病历审查中发现的差距进行了两次调整。每次迭代都会将算法对患者子集(约占特定日期筛查入院和筛查出院人数的 10%)的结果与两名独立姑息治疗医生的专家共识进行比较,从而对算法进行验证。设置/受试者:在为期九个月的时间里,我们每天都对美国学术医疗中心的所有住院成人患者进行筛查。结果:与专家共识的黄金标准相比,识别重症住院患者的最终算法灵敏度为 89%,特异度为 82%,阳性预测值为 80%,阴性预测值为 90%。在我们医院,平均每天有 284 名病人(54%)在至少一项标准上筛查出阳性,平均每天有 38 名病人新筛查出阳性。结论:从电子病历(EMR)中获取的数据可以识别出可能受益于姑息关怀服务的重症住院病人,这是向主动、系统地为所有可能受益者提供姑息关怀服务的系统迈出的重要的第一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of palliative medicine
Journal of palliative medicine 医学-卫生保健
CiteScore
3.90
自引率
10.70%
发文量
345
审稿时长
2 months
期刊介绍: Journal of Palliative Medicine is the premier peer-reviewed journal covering medical, psychosocial, policy, and legal issues in end-of-life care and relief of suffering for patients with intractable pain. The Journal presents essential information for professionals in hospice/palliative medicine, focusing on improving quality of life for patients and their families, and the latest developments in drug and non-drug treatments. The companion biweekly eNewsletter, Briefings in Palliative Medicine, delivers the latest breaking news and information to keep clinicians and health care providers continuously updated.
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