Preventing medication errors due to unsafe electronic prescription transactions with just-in-time feedback

项目总结 尽管电子处方在某些方面提高了患者的安全性，但它们 引入新类型的错误，这些错误可能会对患者造成重大伤害，每年高达439万次。 在电子处方处理过程中，当医生开出的药物是 与药剂师开出的药物不同的成分、强度或剂型。主修 这些不安全的电子处方交易存在的原因包括自由文本药品说明与 国家药品代码(NDC)和处方医生使用的计算机软件中的错误产品选择 药剂师。这些不安全的电子处方交易正在导致危险的药物错误，可能 会对病人造成重大伤害。为了系统地识别不安全的电子处方交易，我们有 开发了一个名为SAVE-Rx的系统，它使用电子处方交易数据来自动识别病例 如果NDC处方与自由文本药物说明不匹配(即，电子处方错误)或 药房配发的药物的NDC。我们的系统匹配国家疾病控制中心和自由文本药物 使用标准化药物的药物成分、强度和剂型的说明 来自国家医学图书馆RxNorm的术语。然后审查不安全的电子处方交易 由安全团队提供，并通过现有的电子处方及时传达给医疗保健组织 工作流程，在它们可能对患者造成伤害之前。我们的长期目标是通过以下途径提高用药安全性 自动化在药物处方和配药工作流程中的战略应用。总的目标是 本研究旨在确定实施及时反馈对预防用药的效果。 医疗保健组织之间的电子处方交易过程中出现错误。Aim 1改进了Just- 及时反馈干预、SAVE-RX及其实施指南，以识别不安全的电子处方 交易记录。目的2评估及时反馈干预措施的实施情况 不安全的电子处方交易。我们的假设是，我们可以提高干预和警报的使用 通过主动停止安全不匹配对的警报来提高性能。目标3确定了 及时反馈干预用药安全结果。我们的假设是及时反馈 对医疗保健组织来说，不安全的电子处方交易将防止临床意义重大 用药安全事件。通过测试一个有能力的工具来实现这些目标将会产生积极的影响 积极监测并向医疗保健组织传达关于不安全电子- 美国每年传输的20多亿份新电子处方的处方交易 各州。在这项研究结束时，我们预计将防止至少6,000起药物安全事件 对4400万份电子处方交易实施SAVE-Rx监控。

PROJECT SUMMARY Although electronic prescriptions (e-prescriptions) have improved patient safety in some ways, they have introduced new types of errors that can lead to significant harm to patients up to 4.39 million times each year. During e-prescription processing, medication errors occur when the medication prescribed by a physician is a different ingredient, strength, or dosage form compared to the medication dispensed by the pharmacist. Major reasons these unsafe e-prescription transactions exist include mismatching free-text drug descriptions with National Drug Codes (NDCs) and erroneous product selection in computer software used by prescribers and pharmacists. These unsafe e-prescription transactions are resulting in dangerous medication errors that may lead to significant patient harm. To systematically identify unsafe e-prescription transactions, we have developed a system, called SAVE-Rx, that uses e-prescription transaction data to automatically identify cases where the NDC prescribed does not match either the free-text drug description (i.e., an e-prescribing error) or the NDC of the medication dispensed by the pharmacy. Our system matches NDCs and free-text drug descriptions on the basis of medication ingredient, strength, and dosage form using standardized drug terminology from National Library of Medicine’s RxNorm. Unsafe e-prescription transactions are then reviewed by a safety team and communicated just-in-time to healthcare organizations, through existing e-prescription workflows, before they can cause harm to patients. Our long-term goal is to improve medication safety through the strategic use of automation in medication prescribing and dispensing workflows. The overall objective of this study is to determine the effect of implementing just-in-time feedback on the prevention of medication errors during e-prescription transactions between healthcare organizations. Aim 1 refines the design of a just- in-time feedback intervention, SAVE-Rx, and its implementation guide to identify unsafe e-prescription transactions. Aim 2 evaluates the implementation of the just-in-time feedback intervention for preventing unsafe e-prescription transactions. Our hypothesis is that we can improve the use of the intervention and alert performance by actively discontinuing alerts for safe mismatching pairs. Aim 3 determines the effects of the just-in-time feedback intervention on medication safety outcomes. Our hypothesis is that just-in-time feedback to healthcare organizations about unsafe e-prescription transactions will prevent clinically significant medication safety events. Accomplishing these aims will have a positive impact by testing a tool that is capable of actively monitoring and communicating useful feedback to healthcare organizations about unsafe e- prescription transactions on the more than 2 billion new e-prescription transmitted each year in the United States. At the end of this study, we expect to prevent at least 6,000 medication safety events as a result of implementing SAVE-Rx monitoring on 44 million e-prescription transactions.