{"title":"Electronic Health Record-Derived Measures of Sleep After Surgical Aortic Valve Replacement.","authors":"Mark A Oldham, Lisa Pink, Sullafa Kadura","doi":"10.4037/ajcc2026195","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Postoperative sleep disturbances, often due to overnight patient-staff interactions (PSIs), are common. Electronic health record (EHR) data were used to derive proxy measures of sleep opportunity and interruptions to characterize patients' sleep.</p><p><strong>Methods: </strong>A total of 208 eligible patient-nights in adults having surgical aortic valve replacement were analyzed. Patients completed the Richards-Campbell Sleep Questionnaire daily after surgery. Any PSIs expected to disrupt sleep were retrieved from the EHR and aggregated into interruptive episodes. Nightly PSIs and periods of uninterrupted sleep opportunity were characterized. Associations between EHR-derived measures of sleep opportunity and self-reports of sleep were examined.</p><p><strong>Results: </strong>Fifty-three patients (mean age, 66.6 years; 64% male) had a median of 7 PSIs (4 interruptive episodes) per night. Median PSIs declined from 21 (7 interruptive episodes) on postoperative night 1 to 4 (3 interruptive episodes) on postoperative night 5. Every patient-night had at least 1 PSI/interruptive episode. The EHR-derived measure most strongly correlated with Richards-Campbell Sleep Questionnaire mean score was total uninterrupted sleep opportunity (Pearson r = 0.39, P < .001).</p><p><strong>Discussion: </strong>Electronic health record-derived measures of sleep opportunity, especially total uninterrupted sleep opportunity, correlated with patients' perceptions of sleep quality and captured changes across the postoperative period. These findings indicate that EHR data can be used to monitor sleep opportunity and that improved sleep opportunities can be an outcome measure for sleep-focused quality improvement projects.</p><p><strong>Conclusions: </strong>Measures of sleep opportunity derived from the EHR may be objective, scalable proxies for self-rated sleep.</p>","PeriodicalId":7607,"journal":{"name":"American Journal of Critical Care","volume":"35 3","pages":"205-213"},"PeriodicalIF":2.6000,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Critical Care","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.4037/ajcc2026195","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CRITICAL CARE MEDICINE","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Postoperative sleep disturbances, often due to overnight patient-staff interactions (PSIs), are common. Electronic health record (EHR) data were used to derive proxy measures of sleep opportunity and interruptions to characterize patients' sleep.
Methods: A total of 208 eligible patient-nights in adults having surgical aortic valve replacement were analyzed. Patients completed the Richards-Campbell Sleep Questionnaire daily after surgery. Any PSIs expected to disrupt sleep were retrieved from the EHR and aggregated into interruptive episodes. Nightly PSIs and periods of uninterrupted sleep opportunity were characterized. Associations between EHR-derived measures of sleep opportunity and self-reports of sleep were examined.
Results: Fifty-three patients (mean age, 66.6 years; 64% male) had a median of 7 PSIs (4 interruptive episodes) per night. Median PSIs declined from 21 (7 interruptive episodes) on postoperative night 1 to 4 (3 interruptive episodes) on postoperative night 5. Every patient-night had at least 1 PSI/interruptive episode. The EHR-derived measure most strongly correlated with Richards-Campbell Sleep Questionnaire mean score was total uninterrupted sleep opportunity (Pearson r = 0.39, P < .001).
Discussion: Electronic health record-derived measures of sleep opportunity, especially total uninterrupted sleep opportunity, correlated with patients' perceptions of sleep quality and captured changes across the postoperative period. These findings indicate that EHR data can be used to monitor sleep opportunity and that improved sleep opportunities can be an outcome measure for sleep-focused quality improvement projects.
Conclusions: Measures of sleep opportunity derived from the EHR may be objective, scalable proxies for self-rated sleep.
背景:术后睡眠障碍是常见的,通常是由于夜间医患互动(psi)。电子健康记录(EHR)数据用于获得睡眠机会和中断的代理测量,以表征患者的睡眠。方法:对成人主动脉瓣置换术中208例符合条件的患者夜进行分析。术后患者每天完成Richards-Campbell睡眠问卷。从电子病历中检索到任何可能干扰睡眠的PSIs,并将其汇总为中断性发作。每晚psi和不间断睡眠时间的特征。研究了ehr衍生的睡眠机会测量与自我睡眠报告之间的关联。结果:53例患者(平均年龄66.6岁,64%为男性)平均每晚有7次PSIs(4次间断发作)。中位psi从术后第1晚的21(7次间断发作)下降到术后第5晚的4(3次间断发作)。每个病人每晚至少有1次PSI/间断发作。与Richards-Campbell睡眠问卷平均得分相关性最强的是总不间断睡眠机会(Pearson r = 0.39, P < 0.001)。讨论:电子健康记录衍生的睡眠机会测量,特别是总不间断睡眠机会,与患者对睡眠质量的感知和术后期间捕获的变化相关。这些发现表明,电子病历数据可以用来监测睡眠机会,改善睡眠机会可以作为睡眠质量改善项目的结果衡量标准。结论:来自电子病历的睡眠机会测量可能是客观的,可扩展的自评睡眠代理。
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