谵妄
检查表
医学
新生儿重症监护室
镇静
质量管理
文档
急诊医学
病历
重症监护医学
医疗急救
儿科
心理学
麻醉
管理制度
管理
计算机科学
经济
认知心理学
放射科
程序设计语言
作者
M.G. Karmarkar,Mark Speziale,Willough Jenkins,Deborah M. Heath,Jiunn‐Horng Kang,Julia Suvak,Paul C. Grimm,Laurel Moyer
标识
DOI:10.1097/pq9.0000000000000752
摘要
Introduction: Delirium is not commonly diagnosed in neonatal intensive care units and can adversely impact patient outcomes in the ICU setting. Recognition of delirium in the NICU is a necessary first step to address the potential impact on neonatal outcomes. Methods: We conducted a quality improvement initiative implementing screening for neonatal delirium. We aimed to increase screening in NICU patients from 0% to 85% by March 2022. Interdisciplinary meetings were held with key stakeholders to develop a clinical algorithm. We used standardized tools for delirium screening. Our process measures included weekly nursing compliance with Richmond Agitation Sedation Scale/Cornell Assessment of Pediatric Delirium/ scoring documentation (Fig. 1) and patients referred to psychiatry. Outcome measures included the percentage of patients screened for delirium before discharge. We conducted Plan-Do-Study Act cycles to optimize the screening process in the electronic medical record (EMR). This included creating an order set, documentation flowsheets, and prompts in the EMR for patients. Results: After initial implementation, we achieved an average weekly screening compliance of 76% (Fig. 1). Inclusion criteria expansion resulted in a downward compliance shift to 59%. Subsequently, the addition of the EMR checklist resulted in a center-line shift to a sustained average weekly screening compliance of 77%. An average of 82% of all eligible NICU patients received delirium screening before discharge (Fig. 2). Conclusions: Using quality improvement methodology, there was increased screening and recognition of delirium in our NICU. Future research efforts could focus on assessing preventive measures and the impact of neonatal delirium on patient outcomes.
科研通智能强力驱动
Strongly Powered by AbleSci AI