Validation of a novel Artificial Pharmacology Intelligence (API) system for the management of patients with polypharmacy

IF 3.7 3区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Research in Social & Administrative Pharmacy Pub Date : 2024-04-10 DOI:10.1016/j.sapharm.2024.04.003

Dorit Dil-Nahlieli , Arie Ben-Yehuda , Daniel Souroujon , Eytan Hyam , Sigal Shafran-Tikvah

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引用次数: 0

Abstract

Objective

Medication management of patients with polypharmacy is highly complex. We aimed to validate a novel Artificial Pharmacology Intelligence (API) algorithm to optimize the medication review process in a comprehensive, personalized, and scalable way.

Materials and methods

The study was conducted on anonymized retrospective electronic health records (EHR) of 49 patients. Each patient's file was reviewed by the API system, a clinical pharmacist, and a judging committee. Validation was assessed by comparing the overall agreement of the judging committee (as the gold standard, blinded to the identity of the analyzer) to both the API system and clinical pharmacists' conclusions. Five medication-related problem (MRP) categories were assessed: duplication of therapy, age-related issues, incorrect dose, current side effects and future side effects' risk. For each category the overall validity parameters, agreement, positive predictive value (PPV), negative predictive value (NPV), sensitivity and specificity were analyzed.

Results

The agreement between the API system and the judging committee was 93.5 % (95 % CI 92.7–94.4), while the agreement between the clinical pharmacists and the judging committee was 73.9 % (95 % CI 72.5–75.3). The PPV was 92.2 % (90.9–93.5) and NPV was 94.2 % (93.1–95.2) for the API system and 76.3 % (69.8–82.8) and 73.5 % (72.3–74.8) respectively for the clinical pharmacists.

Discussion

AI systems can equip clinicians with sophisticated tools and scale manual processes such as comprehensive medication reviews, thus reducing MRPs and drug-related hospitalizations related to multidrug treatments. The API system validated in this study provided comprehensive, multidrug, multilayered analysis intended to bridge the innate complexity of personalized polypharmacy treatment.

Conclusions

The API system was validated as a tool for providing actionable clinical insights non-inferior to a manual clinical review of a clinical pharmacist. The API system showed promising results in reducing MRPs.

查看原文本刊更多论文

验证新型人工药理学智能（API）系统，用于管理多重用药患者。

目的对使用多种药物的患者进行用药管理非常复杂。我们旨在验证一种新型人工药理学智能（API）算法，以全面、个性化和可扩展的方式优化用药审查流程。API 系统、临床药剂师和评审委员会对每位患者的档案进行了审查。通过比较评审委员会（作为金标准，对分析者身份保密）与 API 系统和临床药剂师结论的总体一致性来评估有效性。评估了五个药物相关问题 (MRP) 类别：重复治疗、年龄相关问题、剂量不正确、当前副作用和未来副作用风险。结果 API 系统与评审委员会之间的一致性为 93.5 %（95 % CI 92.7-94.4），而临床药师与评审委员会之间的一致性为 73.9 %（95 % CI 72.5-75.3）。API系统的PPV为92.2%（90.9-93.5），NPV为94.2%（93.1-95.2）；临床药师的PPV为76.3%（69.8-82.8），NPV为73.5%（72.3-74.8）。本研究中验证的 API 系统提供了全面、多药物、多层次的分析，旨在消除个性化多药治疗的固有复杂性。结论 API 系统经验证是一种提供可操作临床见解的工具，其效果不亚于临床药师的人工临床审查。API 系统在减少 MRP 方面显示出良好的效果。

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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来源期刊

Research in Social & Administrative Pharmacy PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-

CiteScore

7.20

自引率

10.30%

发文量

225

审稿时长

47 days

期刊介绍： Research in Social and Administrative Pharmacy (RSAP) is a quarterly publication featuring original scientific reports and comprehensive review articles in the social and administrative pharmaceutical sciences. Topics of interest include outcomes evaluation of products, programs, or services; pharmacoepidemiology; medication adherence; direct-to-consumer advertising of prescription medications; disease state management; health systems reform; drug marketing; medication distribution systems such as e-prescribing; web-based pharmaceutical/medical services; drug commerce and re-importation; and health professions workforce issues.