使用药物列表-问题列表不匹配作为潜在错误的标记。

Proceedings. AMIA Symposium Pub Date : 2002-01-01
James D Carpenter, Paul N Gorman
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引用次数: 0

摘要

该项目的目标是指定和开发一种算法,用于检查电子医疗记录(EMR)中的药物和问题列表不匹配。该算法的前提是患者的问题清单和药物清单应该一致,不匹配可能表明用药错误。该算法的成功开发可能意味着可以检测到一些错误,例如输入错误患者记录的药物处方,或药物治疗遗漏,这些错误是通过自动化手段无法检测到的。此外,不匹配可以识别改进问题列表完整性的机会。为了评估这个概念的可行性,本研究比较了药房信息系统中列出的药物与在线护理成人入院评估的结果,作为问题清单的代理。如果发现药物和问题清单不匹配,检查患者记录确认不匹配,并确定任何潜在的原因。该算法在糖尿病治疗中的评估表明,它成功地检测到潜在的用药错误和提高问题列表完整性的机会。这种算法,一旦完全开发和部署,可以证明是一种有价值的方法来改善病人的问题清单,并可以降低用药错误的风险。
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Using medication list--problem list mismatches as markers of potential error.

The goal of this project was to specify and develop an algorithm that will check for drug and problem list mismatches in an electronic medical record (EMR). The algorithm is based on the premise that a patient's problem list and medication list should agree, and a mismatch may indicate medication error. Successful development of this algorithm could mean detection of some errors, such as medication orders entered into a wrong patient record, or drug therapy omissions, that are not otherwise detected via automated means. Additionally, mismatches may identify opportunities to improve problem list integrity. To assess the concept's feasibility, this study compared medications listed in a pharmacy information system with findings in an online nursing adult admission assessment, serving as a proxy for the problem list. Where drug and problem list mismatches were discovered, examination of the patient record confirmed the mismatch, and identified any potential causes. Evaluation of the algorithm in diabetes treatment indicates that it successfully detects both potential medication error and opportunities to improve problem list completeness. This algorithm, once fully developed and deployed, could prove a valuable way to improve the patient problem list, and could decrease the risk of medication error.

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