Calandra Feather, Nicholas Appelbaum, Jonathan Clarke, Ara Darzi, Bryony Dean Franklin
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Methods\nA simulated, randomised, cross-over exploratory study was conducted at a London NHS Trust. Participants completed five simulated prescribing tasks with, and five without, the intervention. Data collection methods comprised direct observation of prescribing tasks, self-reported task load and semi-structured interviews. A concurrent triangulation design combined quantitative and qualitative data. Results\n24 participants completed a total of 240 medication orders. The intervention was associated with fewer prescribing errors (6.6% of 120 medications) compared to standard practice (28.3%; relative risk reduction 76.5% p < 0.01), a shorter TTP and lower overall NASA TLX scores (p < 0.01). Control arm workflow vulnerabilities included failures in identifying correct doses, applying maximum dose limits, and calculating patient-specific dosages. Intervention arm errors primarily stemmed from misidentifying patient-specific information from the medication scenario. Thematic analysis of participant interviews identified six themes: Navigating trust and familiarity, addressing challenges and suggestions for improvement, integration of local guidelines and existing CDSS, intervention endorsement, search by indication and targeting specific patient and staff groups. Conclusion\nThe intervention represents a promising advancement in medication safety, with implications for enhancing patient safety and efficiency. Further real-world evaluation and development of the system to meet the needs of more diverse patient groups, users and healthcare settings is now required.","PeriodicalId":501556,"journal":{"name":"medRxiv - Health Systems and Quality Improvement","volume":"59 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparing safety, performance and user perceptions of a patient-specific indication-based prescribing tool with current practice: A mixed-methods randomised user testing study\",\"authors\":\"Calandra Feather, Nicholas Appelbaum, Jonathan Clarke, Ara Darzi, Bryony Dean Franklin\",\"doi\":\"10.1101/2024.07.01.24309757\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background\\nMedication errors are the leading cause of preventable harm in healthcare. Despite proliferation of medication-related clinical decision support systems (CDSS), current systems have limitations. We therefore developed an indication-based prescribing tool. This performs dose calculations using an underlying formulary and provides patient-specific dosing recommendations. Objectives were to compare the incidence and types of erroneous medication orders, time to prescribe (TTP), and perceived workload using the NASA task load index (TLX), in simulated prescribing tasks with and without this intervention. We also sought to identify workflow steps most vulnerable to error and gain participant feedback. Methods\\nA simulated, randomised, cross-over exploratory study was conducted at a London NHS Trust. Participants completed five simulated prescribing tasks with, and five without, the intervention. Data collection methods comprised direct observation of prescribing tasks, self-reported task load and semi-structured interviews. 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引用次数: 0
摘要
背景用药错误是医疗保健领域可预防伤害的主要原因。尽管与用药相关的临床决策支持系统(CDSS)不断涌现,但目前的系统仍存在局限性。因此,我们开发了一种基于适应症的处方工具。该工具使用基础处方集进行剂量计算,并提供针对患者的剂量建议。我们的目标是比较错误处方的发生率和类型、处方时间 (TTP) 以及使用 NASA 任务负荷指数 (TLX) 在有和没有该干预措施的模拟处方任务中感知到的工作量。我们还试图找出最容易出错的工作流程步骤,并获得参与者的反馈意见。方法 在伦敦一家 NHS 信托公司进行了一项模拟、随机、交叉探索性研究。参与者分别完成了五次有干预措施和五次无干预措施的模拟处方任务。数据收集方法包括直接观察处方任务、自我报告任务负荷和半结构化访谈。同时进行的三角测量设计结合了定量和定性数据。结果 24 名参与者共完成了 240 份处方。与标准实践(28.3%;相对风险降低 76.5% p < 0.01)相比,干预措施减少了处方错误(120 种药物中的 6.6%),缩短了 TTP,降低了 NASA TLX 总分(p < 0.01)。对照组工作流程的漏洞包括未能识别正确剂量、应用最大剂量限制和计算患者特定剂量。干预组的错误主要源于错误识别用药情景中的患者特定信息。对参与者访谈的主题分析确定了六个主题:信任和熟悉度导航、应对挑战和改进建议、整合当地指南和现有 CDSS、干预认可、按适应症搜索以及针对特定患者和员工群体。结论:该干预措施是用药安全领域的一项有希望的进步,对提高患者安全和效率具有重要意义。现在需要对该系统进行进一步的实际评估和开发,以满足更多不同患者群体、用户和医疗机构的需求。
Comparing safety, performance and user perceptions of a patient-specific indication-based prescribing tool with current practice: A mixed-methods randomised user testing study
Background
Medication errors are the leading cause of preventable harm in healthcare. Despite proliferation of medication-related clinical decision support systems (CDSS), current systems have limitations. We therefore developed an indication-based prescribing tool. This performs dose calculations using an underlying formulary and provides patient-specific dosing recommendations. Objectives were to compare the incidence and types of erroneous medication orders, time to prescribe (TTP), and perceived workload using the NASA task load index (TLX), in simulated prescribing tasks with and without this intervention. We also sought to identify workflow steps most vulnerable to error and gain participant feedback. Methods
A simulated, randomised, cross-over exploratory study was conducted at a London NHS Trust. Participants completed five simulated prescribing tasks with, and five without, the intervention. Data collection methods comprised direct observation of prescribing tasks, self-reported task load and semi-structured interviews. A concurrent triangulation design combined quantitative and qualitative data. Results
24 participants completed a total of 240 medication orders. The intervention was associated with fewer prescribing errors (6.6% of 120 medications) compared to standard practice (28.3%; relative risk reduction 76.5% p < 0.01), a shorter TTP and lower overall NASA TLX scores (p < 0.01). Control arm workflow vulnerabilities included failures in identifying correct doses, applying maximum dose limits, and calculating patient-specific dosages. Intervention arm errors primarily stemmed from misidentifying patient-specific information from the medication scenario. Thematic analysis of participant interviews identified six themes: Navigating trust and familiarity, addressing challenges and suggestions for improvement, integration of local guidelines and existing CDSS, intervention endorsement, search by indication and targeting specific patient and staff groups. Conclusion
The intervention represents a promising advancement in medication safety, with implications for enhancing patient safety and efficiency. Further real-world evaluation and development of the system to meet the needs of more diverse patient groups, users and healthcare settings is now required.