An Automated Strategy to Calculate Medication Regimen Complexity.

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2024-01-11 eCollection Date: 2023-01-01
Yuzhi Lu, Ariel R Green, Rosalphie Quiles, Casey Overby Taylor
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Abstract

Understanding medication regimen complexity is important to understand what patients may benefit from pharmacist interventions. Medication Regimen Complexity Index (MRCI), a 65-item tool to quantify the complexity by incorporating the count, dosage form, frequency, and additional administration instructions of prescription medicines, provides a more nuanced way of assessing complexity. The goal of this study was to construct and validate a computational strategy to automate the calculation of MRCI. The performance of our strategy was evaluated by comparing our calculated MRCI values with gold-standard values, using correlation coefficients and population distributions. The results revealed satisfactory performance to calculate the sub-score of MRCI that includes dosage form and frequency (76 to 80% match with gold standard), and fair performance for sub-score related to additional direction (52% match with gold standard). Our automated strategy shows potential to help reduce the effort for manually calculating MRCI and highlights areas for future development efforts.

自动计算用药方案复杂性的策略。
了解用药方案的复杂性对于了解哪些患者可能受益于药剂师的干预非常重要。药物治疗方案复杂性指数(MRCI)是一种包含 65 个项目的工具,通过纳入处方药的数量、剂型、频率和附加给药说明来量化药物治疗方案的复杂性。本研究的目标是构建并验证一种自动计算 MRCI 的计算策略。通过使用相关系数和人群分布将计算出的 MRCI 值与黄金标准值进行比较,评估了我们策略的性能。结果显示,计算包括剂型和频率在内的 MRCI 子分数的性能令人满意(与黄金标准的匹配率为 76% 至 80%),而计算与额外方向相关的子分数的性能尚可(与黄金标准的匹配率为 52%)。我们的自动化策略显示出了帮助减少人工计算 MRCI 的潜力,并突出了未来的发展方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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