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DOI 10.1097/jhq.0000000000000452

Медицинская библиотека · Journal for healthcare quality : official publication of the National Association for Healthcare Quality · 2024

Implementation of an Evidence-Based Treatment Protocol and Order Set for Alcohol Withdrawal Syndrome.

Luzum Nathan Robert, Beckius Anna, Heinrich Thomas W, Stoner Kimberly

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Аннотация

BACKGROUND

Alcohol withdrawal syndrome (AWS) is highly prevalent in hospital inpatients. Recent evidence supports use of phenobarbital and gabapentin in certain patients, and screening tools for severe withdrawal risk can be used to guide care. Inpatients with AWS should also be considered for evidence-based treatment for alcohol use disorder (AUD).

PURPOSE: The purpose of this quality improvement study was to monitor clinical outcomes and prescribing habits after updating an electronic order set for inpatient AWS management at a large, academic hospital.

METHODS

Protocol updates included use of the Prediction of Alcohol Withdrawal Severity Scale, phenobarbital and gabapentin protocols, and linkage to treatment resources. Data were collected for 10 months before and 14 months after implementation.

RESULTS

Intensive care unit (ICU) transfer rate decreased by 2.3%, whereas length of stay and readmissions were not significantly different. In patients treated with the order set, ICU transfer and length of stay outcomes were superior. Patients treated through the order set were more likely to receive evidence-based treatment for AWS and AUD.

CONCLUSIONS

Electronic order sets can promote evidence-based practice for AWS. The updated protocol will remain in place at the study institution, with future efforts focused on education and ease of use to increase order set utilization.

Для цитирования: Luzum Nathan Robert, Beckius Anna, Heinrich Thomas W, Stoner Kimberly. Implementation of an Evidence-Based Treatment Protocol and Order Set for Alcohol Withdrawal Syndrome.. Journal for healthcare quality : official publication of the National Association for Healthcare Quality. 2024. DOI: 10.1097/jhq.0000000000000452.

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