An integrated opioid prescription optimization framework for total joint replacement surgery patients

IF 1.5 Q3 HEALTH CARE SCIENCES & SERVICES

IISE Transactions on Healthcare Systems Engineering Pub Date : 2021-02-01 DOI:10.1080/24725579.2021.1873878

Sujee Lee, Philip A. Bain, Albert J. Musa, C. Baker, Jingshan Li

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引用次数: 0

Abstract

Abstract Opioid overdose, addiction, and death have become a nationwide crisis in recent years. Opioid leftover due to over-prescription at hospitals to treat chronic or surgical pains is one of the main contributors to the epidemic. To reduce leftovers, opioid prescriptions should be adjusted and tailored to patients’ needs. However, insufficient prescription may result in frequent refills for patients with high opioid-use levels, which can lead to inefficiency to patients, physicians, and pharmacists. Therefore, developing an optimal opioid prescription model to provide the necessary and patient-specific amount of opioids with minimal refills has a significant importance. In this paper, we introduce an integrated analytical framework, which intends to optimize both opioid prescription and number of refills based on stratification of patients’ opioid usage levels and corresponding stochastic programming. A case study for total joint replacement surgery patients at a community hospital is then introduced to illustrate the applicability and benefits of the framework.

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全关节置换术患者综合阿片类药物处方优化框架

近年来，阿片类药物过量、成瘾和死亡已成为一个全国性的危机。医院为治疗慢性疼痛或手术疼痛而过度开处方导致的阿片类药物残留是导致这种流行病的主要原因之一。为了减少剩菜剩菜，阿片类药物处方应该根据患者的需求进行调整和定制。然而，处方不足可能导致阿片类药物使用水平高的患者频繁重新配药，这可能导致患者、医生和药剂师效率低下。因此，开发一个最佳的阿片类药物处方模型，以提供必要的和患者特异性的阿片类药物量，并以最少的再填充具有重要意义。在本文中，我们引入了一个集成的分析框架，该框架旨在基于患者阿片类药物使用水平的分层和相应的随机规划来优化阿片类药物处方和再填充次数。然后介绍了一个社区医院全关节置换手术患者的案例研究，以说明该框架的适用性和益处。

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

IISE Transactions on Healthcare Systems Engineering Social Sciences-Safety Research

CiteScore

3.10

自引率

0.00%

发文量

期刊介绍： IISE Transactions on Healthcare Systems Engineering aims to foster the healthcare systems community by publishing high quality papers that have a strong methodological focus and direct applicability to healthcare systems. Published quarterly, the journal supports research that explores: · Healthcare Operations Management · Medical Decision Making · Socio-Technical Systems Analysis related to healthcare · Quality Engineering · Healthcare Informatics · Healthcare Policy We are looking forward to accepting submissions that document the development and use of industrial and systems engineering tools and techniques including: · Healthcare operations research · Healthcare statistics · Healthcare information systems · Healthcare work measurement · Human factors/ergonomics applied to healthcare systems Research that explores the integration of these tools and techniques with those from other engineering and medical disciplines are also featured. We encourage the submission of clinical notes, or practice notes, to show the impact of contributions that will be published. We also encourage authors to collect an impact statement from their clinical partners to show the impact of research in the clinical practices.