医院治疗酒精戒断综合征的电子病历订单集指南一致性。

Shawn M Cohen, Nitu Kashyap, Tessa L Steel, E Jennifer Edelman, David A Fiellin, Paul J Joudrey
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引用次数: 0

摘要

背景:医院对酒精戒断综合征(AWS)的治疗并不一致。电子病历(EHR)的医嘱设置规范了治疗:我们研究了不同医院机构的戒酒综合症治疗指令集的差异及其与戒酒综合症指南的一致性:我们对从 2021 年 12 月 Epic® 用户网络社区库中提取的医院组织用户创建的 AWS 电子病历医嘱集进行了横断面研究。我们纳入了拥有一家急症护理医院且≥ $\ge $ 1 AWS 订单集的医院组织。我们测量了四个类别中与指南一致的护理实践的比例:(1)实验室评估;(2)严重AWS的风险评估及相关管理变化;(3)AWS的症状评估和治疗,以及并发症的识别和管理;(4)不健康饮酒和AUD的筛查、诊断和治疗,包括酒精使用障碍(MAUD)的药物治疗:结果:共纳入了 95 家机构的 289 套医嘱。实验室评估与指南一致的机构比例包括电解质检测(83%)、肝功能检测(75%)、药物使用检测(83%)和感染筛查(33%)。评估重症 AWS 风险(34%)和护理升级指征(63%)的指南使用了不一致的定义。使用与指南一致的药物治疗 AWS(99%)和 AWS 症状评分(91%)几乎是普遍现象。有两家机构(2%)纳入了 MAUD。26%的机构在 EHR 订单集中使用了通用模板订单集:我们观察到各机构经常纳入与指南一致的药物和症状评分,但很少纳入和/或定义不清的评估严重 AWS 风险、护理升级和 MAUD 的指南。
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Guideline concordance of electronic health record order sets for hospital-based treatment of alcohol withdrawal syndrome.

Background: Treatment of alcohol withdrawal syndrome (AWS) in hospitals is inconsistent. Electronic health record (EHR) order sets protocolize care.

Objective: We examined variation in AWS order sets across hospital organizations and their concordance with AWS guidelines.

Methods: We conducted a cross-sectional study of hospital organization user-created EHR order sets for AWS extracted from the December 2021 Epic® userweb community library. Hospital organizations with an acute care hospital and $\ge $ 1 AWS order set were included. We measured the proportion of guideline-concordant care practices within four categories: (1) laboratory assessment, (2) risk assessment for severe AWS and associated management changes, (3) symptom assessment and treatment of AWS, and identification and management of complications and (4) screening, diagnosis, and treatment of unhealthy alcohol use and AUD including medications for alcohol use disorder (MAUD).

Results: Ninety-five organizations with 289 order sets were included. The proportion of organizations with guideline-concordant laboratory assessments included testing of electrolytes (83%), hepatic function (75%), substance use (83%), and screening for infections (33%). Guidance for assessing risk of severe AWS (34%) and indications for care escalation (63%) used inconsistent definitions. Use of guideline-concordant medications for AWS (99%) and AWS symptom scores (91%) were nearly universal. MAUD was included by two organizations (2%). A common templated order set was used by 26% of organizations in EHR order sets.

Conclusions: We observed frequent organizational inclusion of guideline-concordant medications and symptom scores but rare and/or poorly defined guidance for evaluating risk of severe AWS, escalation of care, and MAUD.

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Assessing the impact of workload and clinician experience on patient throughput: A multicenter study. Guideline concordance of electronic health record order sets for hospital-based treatment of alcohol withdrawal syndrome. Methodological progress note: Purposeful sampling in qualitative research. Streamlining diuresis: A quality improvement approach to implementing a sodium-based predictive diuresis protocol. From rounds to retweets: A digital media fellowship perspective.
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