Unitat de Coordinació i Estratègia del Medicament (UCEM), Institut Català de la Salut, Barcelona, Spain.
Departament de Farmacologia, Terapèutica i Toxicologia, Universitat Autònoma de Barcelona, Barcelona, Spain.
BMC Med Inform Decis Mak. 2021 Dec 15;21(1):349. doi: 10.1186/s12911-021-01710-8.
In 2008, the Institut Català de la Salut (ICS, Catalan Health Institute) implemented a prescription decision support system in its electronic clinical workstation (ECW), which automatically generates online alerts for general practitioners when a possible medication-related problem (MRP) is detected. This tool is known as PREFASEG, and at the time of beginning a new treatment, it automatically assesses the suitability of the treatment for the individual patient. This analysis is based on ongoing treatments, demographic characteristics, existing pathologies, and patient biochemical variables. As a result of the assessment, therapeutic recommendations are provided. The objective of this study is to present the PREFASEG tool, analyse the main alerts that it generates, and determine the degree of alert acceptance.
A cross-sectional descriptive study was carried out to analyse the generation of MRP-related alerts detected by PREFASEG during 2016, 2017, and 2018 in primary care (PC) in Catalonia. The number of MRP alerts generated, the drugs involved, and the acceptance/rejection of the alerts were analysed. An alert was considered "accepted" when the medication that generated the alert was not prescribed, thereby following the recommendation given by the tool. The MRP alerts studied were therapeutic duplications, safety alerts issued by the Spanish Medicines Agency, and drugs not recommended for use in geriatrics. The prescriptions issued by 6411 ICS PC physicians who use the ECW and provide their services to 5.8 million Catalans through 288 PC teams were analysed.
During the 3 years examined, 67.2 million new prescriptions were analysed, for which PREFASEG generated 4,379,866 alerts (1 for every 15 new treatments). A total of 1,222,159 alerts (28%) were accepted. Pharmacological interactions and therapeutic duplications were the most detected alerts, representing 40 and 30% of the total alerts, respectively. The main pharmacological groups involved in the safety alerts were nonsteroidal anti-inflammatory drugs and renin-angiotensin system inhibitors.
During the period analysed, 28% of the prescriptions wherein a toxicity-related PREFASEG alert was generated led to treatment modification, thereby helping to prevent the generation of potential safety MRPs. However, the tool should be further improved to increase alert acceptance and thereby improve patient safety.
2008 年，加泰罗尼亚卫生研究所（ICS）在其电子临床工作站（ECW）中实施了处方决策支持系统，当检测到可能与药物相关的问题（MRP）时，该系统会自动为全科医生生成在线警报。该工具称为 PREFASEG，在开始新的治疗时，它会自动评估治疗方案对个体患者的适宜性。这种分析基于正在进行的治疗、人口统计学特征、现有病理和患者生化变量。根据评估结果，提供治疗建议。本研究的目的是介绍 PREFASEG 工具，分析其生成的主要警报，并确定警报接受程度。
我们进行了一项横断面描述性研究，以分析 2016 年、2017 年和 2018 年在加泰罗尼亚初级保健（PC）中 PREFASEG 检测到的与药物相关问题警报的生成情况。分析生成的药物相关问题警报数量、涉及的药物以及对警报的接受/拒绝情况。当生成警报的药物未开处方，从而遵循工具给出的建议时，该警报被视为“接受”。所研究的药物相关问题警报包括治疗性重复用药、西班牙药品管理局发布的安全性警报以及不建议在老年患者中使用的药物。分析了使用 ECW 并通过 288 个 PC 团队为 580 万加泰罗尼亚人提供服务的 6411 名 ICS PC 医生开出的 6720 万张新处方。
在研究的 3 年中，共分析了 6720 万张新处方，其中 PREFASEG 生成了 4379866 个警报（每 15 个新处方就有 1 个警报）。共接受了 1222159 个警报（28%）。药物相互作用和治疗性重复用药是检测到的最多的警报，分别占总警报的 40%和 30%。涉及安全性警报的主要药物类别是非甾体抗炎药和肾素-血管紧张素系统抑制剂。
在所分析的时间段内，有 28%的处方在生成毒性相关的 PREFASEG 警报后进行了治疗调整，从而有助于防止潜在的安全药物相关问题的发生。然而，该工具应进一步改进，以提高警报接受率，从而提高患者安全性。
