Pharmacy Department, Hospital Santa Creu i Sant Pau. Institut de Recerca Sant Pau (IR SANT PAU), Barcelona, Spain.
Catalan Health Service. Digitalization for the Sustainability of the Healthcare System (DS3). Institut d'Investigacions Biomèdiques de Bellvitge (IDIBELL), Barcelona, Spain.
BMC Emerg Med. 2024 Feb 14;24(1):23. doi: 10.1186/s12873-024-00946-7.
During the last decade, the progressive increase in age and associated chronic comorbidities and polypharmacy. However, assessments of the risk of emergency department (ED) revisiting published to date often neglect patients' pharmacotherapy plans, thus overseeing the Drug-related problems (DRP) risks associated with the therapy burden. The aim of this study is to develop a predictive model for ED revisit, hospital admission, and mortality based on patient's characteristics and pharmacotherapy.
Retrospective cohort study including adult patients visited in the ED (triage 1, 2, or 3) of multiple hospitals in Catalonia (Spain) during 2019. The primary endpoint was a composite of ED visits, hospital admission, or mortality 30 days after ED discharge. The study population was randomly split into a model development (60%) and validation (40%) datasets. The model included age, sex, income level, comorbidity burden, measured with the Adjusted Morbidity Groups (GMA), and number of medications. Forty-four medication groups, associated with medication-related health problems, were assessed using ATC codes. To assess the performance of the different variables, logistic regression was used to build multivariate models for ED revisits. The models were created using a "stepwise-forward" approach based on the Bayesian Information Criterion (BIC). Area under the curve of the receiving operating characteristics (AUCROC) curve for the primary endpoint was calculated.
851.649 patients were included; 134.560 (15.8%) revisited the ED within 30 days from discharge, 15.2% were hospitalized and 9.1% died within 30 days from discharge. Four factors (sex, age, GMA, and income level) and 30 ATC groups were identified as risk factors and combined into a final score. The model showed an AUCROC values of 0.720 (95%CI:0.718-0.721) in the development cohort and 0.719 (95%CI.0.717-0.721) in the validation cohort. Three risk categories were generated, with the following scores and estimated risks: low risk: 18.3%; intermediate risk: 40.0%; and high risk: 62.6%.
The DICER score allows identifying patients at high risk for ED revisit within 30 days based on sociodemographic, clinical, and pharmacotherapeutic characteristics, being a valuable tool to prioritize interventions on discharge.
在过去十年中,年龄的逐渐增长以及随之而来的慢性合并症和多种药物治疗。然而,迄今为止发表的关于急诊科(ED)复诊风险的评估往往忽略了患者的药物治疗方案,从而忽视了与治疗负担相关的药物相关问题(DRP)风险。本研究的目的是基于患者的特征和药物治疗,建立一个预测 ED 复诊、住院和死亡的模型。
这是一项回顾性队列研究,纳入了 2019 年在加泰罗尼亚(西班牙)多家医院就诊的 ED(分诊 1、2 或 3)的成年患者。主要终点是 ED 出院后 30 天内的 ED 就诊、住院或死亡的复合终点。研究人群随机分为模型建立(60%)和验证(40%)数据集。该模型包括年龄、性别、收入水平、用调整后的发病群组(GMA)衡量的合并症负担以及用药数量。使用 ATC 代码评估了 44 种与药物相关的健康问题相关的药物组。为了评估不同变量的性能,使用逻辑回归为 ED 复诊建立了多变量模型。这些模型是使用基于贝叶斯信息准则(BIC)的“逐步向前”方法创建的。计算主要终点的接收者操作特征(ROC)曲线下面积(AUCROC)。
共纳入 851649 名患者;134560 名(15.8%)患者在出院后 30 天内再次就诊 ED,15.2%住院,9.1%出院后 30 天内死亡。4 个因素(性别、年龄、GMA 和收入水平)和 30 个 ATC 组被确定为危险因素,并组合成一个最终评分。该模型在开发队列中的 AUCROC 值为 0.720(95%CI:0.718-0.721),在验证队列中的 AUCROC 值为 0.719(95%CI.0.717-0.721)。生成了三个风险类别,其分数和估计风险如下:低风险:18.3%;中风险:40.0%;高风险:62.6%。
DICER 评分可根据社会人口统计学、临床和药物治疗特征识别出 30 天内 ED 复诊风险较高的患者,是一种在出院时优先进行干预的有价值的工具。