Altshuler Diana, Yu Kenny, Papadopoulos John, Dabestani Arash
NYU Langone Health, New York City, NY, USA.
Hosp Pharm. 2021 Oct;56(5):430-435. doi: 10.1177/0018578720918341. Epub 2020 May 17.
The intent of this article is to evaluate a novel approach, using rapid cycle analytics and real world evidence, to optimize and improve the medication evaluation process to help the formulary decision making process, while reducing time for clinicians. The Pharmacy and Therapeutics (P&T) Committee within each health system is responsible for evaluating medication requests for formulary addition. Members of the pharmacy staff prepare the drug monograph or a medication use evaluation (MUE) and allocate precious clinical resources to review patient charts to assess efficacy and value. We explored a novel approach to evaluate the value of our intravenous acetaminophen (IV APAP) formulary admittance. This new methodology, called rapid cycle analytics, can assist hospitals in meeting and/or exceeding the minimum criteria of formulary maintenance as defined by the Joint Commission Standards. In this particular study, we assessed the effectiveness of IV APAP in total hip arthroplasty (THA) and total knee arthroplasty (TKA) procedures. We assessed the correlation to same-stay opioid utilization, average length of inpatient stay and post anesthesia care unit (PACU) time. We were able to explore and improve our organization's approach in evaluating medications by partnering with an external analytics expert to help organize and normalize our data in a more robust, yet time efficient manner. Additionally, we were able to use a significantly larger external data set as a point of reference. Being able to perform this detailed analytical exercise for thousands of encounters internally and using a data warehouse of over 130 million patients as a point of reference in a short time has improved the depth of our assessment, as well as reducing valuable clinical resources allocated to MUEs to allow for more direct patient care. This clinically real-world and data-rich analytics model is the necessary foundation for using Artificial or Augmented Intelligence (AI) to make real-time formulary and drug selection decisions.
本文旨在评估一种新方法，即利用快速循环分析和真实世界证据，优化和改进药物评估流程，以辅助处方集决策过程，同时为临床医生节省时间。每个医疗系统内的药学与治疗学（P&T）委员会负责评估添加到处方集的药物申请。药房工作人员编写药品专论或药物使用评估（MUE），并分配宝贵的临床资源来审查患者病历，以评估疗效和价值。我们探索了一种新方法来评估静脉注射对乙酰氨基酚（IV APAP）纳入处方集的价值。这种名为快速循环分析的新方法可以帮助医院达到和/或超越联合委员会标准所定义的处方集维护最低标准。在这项具体研究中，我们评估了IV APAP在全髋关节置换术（THA）和全膝关节置换术（TKA）中的有效性。我们评估了其与同住院期间阿片类药物使用、平均住院时间和麻醉后护理单元（PACU）时间的相关性。通过与外部分析专家合作，我们能够以更强大且高效的方式整理和规范数据，从而探索并改进我们组织评估药物的方法。此外，我们能够使用一个大得多的外部数据集作为参考。能够在短时间内对数千例病例进行这种详细的分析，并以超过1.3亿患者的数据库作为参考，不仅提高了我们评估的深度，还减少了分配给MUE的宝贵临床资源，以便能提供更直接的患者护理。这种临床真实且数据丰富的分析模型是使用人工智能或增强智能（AI）进行实时处方集和药物选择决策的必要基础。
