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作为常规收集的电子数据源中住院期间药物不良反应检测指标的药物-事件对

Drug-Event Pairs as Indicators for the Detection of Adverse Drug Reactions during Hospitalization in Routinely Collected Electronic Data Sources.

作者信息

Wermund Anna Maria, Haerdtlein Annette, Fehrmann Wolfgang, Weglage Clara, Dreischulte Tobias, Jaehde Ulrich

机构信息

Department of Clinical Pharmacy, Institute of Pharmacy, University of Bonn, Bonn, Germany.

Institute of General Practice and Family Medicine, LMU University Hospital, LMU Munich, Munich, Germany.

出版信息

Clin Pharmacol Ther. 2025 Jun;117(6):1811-1819. doi: 10.1002/cpt.3635. Epub 2025 Mar 18.

Abstract

Adverse drug reactions (ADRs) are a common cause of morbidity and mortality in hospitalized patients. Identification of ADRs in clinical practice, surveillance and research is essential to prevent further harm. The aim of this study was to assess the likelihood of drugs contributing to clinically important inpatient adverse events, in order to provide a list of drug-event pairs indicating ADRs in electronic health record (EHR) data, referred to as "indicators of ADRs". We conducted a consensus process based on the RAND/UCLA Appropriateness Method for 14 ADRs. Experts were asked to rate the strength of the causal link between adverse events and potentially causative drugs on a 4-point Likert scale. Based on the median rating, drug-event pairs were categorized according to the likelihood of an ADR being present. Drug-event pairs with a median rating of ≥ 3 without disagreement were defined as indicators of certain and probable ADRs. Of the 255 drug-event pairs evaluated, 2 (1%) and 42 (16%) achieved consensus validation that they certainly and probably indicate an ADR. In addition, 137 drug-event pairs were considered as indicators of possible (54%) and 74 drug-event pairs were considered as indicators of unlikely (29%) ADRs. The provided set of content-validated indicators of clinically important inpatient ADRs can be used in clinical practice (e.g., decision support), surveillance (e.g., quality indicators) and research (e.g., outcome measures). They will be implemented in EHR data from German university hospitals to determine the prevalence of ADRs, support efficient use of pharmacist resources, and develop models predicting ADRs.

摘要

药物不良反应(ADR)是住院患者发病和死亡的常见原因。在临床实践、监测和研究中识别ADR对于防止进一步损害至关重要。本研究的目的是评估药物导致临床重要住院不良事件的可能性,以便在电子健康记录(EHR)数据中提供表明ADR的药物-事件对列表,即“ADR指标”。我们基于兰德/加州大学洛杉矶分校适宜性方法对14种ADR进行了共识过程。要求专家在4点李克特量表上对不良事件与潜在致病药物之间因果关系的强度进行评分。根据中位数评分,将药物-事件对根据存在ADR的可能性进行分类。中位数评分≥3且无分歧的药物-事件对被定义为确定和很可能的ADR指标。在评估的255个药物-事件对中,有2个(1%)和42个(16%)获得了共识验证,它们确定和很可能表明存在ADR。此外,137个药物-事件对被认为是可能的ADR指标(54%),74个药物-事件对被认为是不太可能的ADR指标(29%)。所提供的经过内容验证的临床重要住院ADR指标集可用于临床实践(如决策支持)、监测(如质量指标)和研究(如结果测量)。它们将应用于德国大学医院的EHR数据中,以确定ADR的患病率,支持药剂师资源的有效利用,并开发预测ADR的模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a7e/12087692/101c52934d4c/CPT-117-1811-g001.jpg

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