ENTIMOS:决策支持工具通过临床情景模拟,强调多发性硬化症非静脉注射疗法对患者护理的潜在影响。

IF 2 Q2 ECONOMICS PharmacoEconomics Open Pub Date : 2024-09-01 Epub Date: 2024-07-11 DOI:10.1007/s41669-024-00493-8
Richard Nicholas, Erik Scalfaro, Rachel Dorsey, Zuzanna Angehrn, Judit Banhazi, Roisin Brennan, Nicholas Adlard
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引用次数: 0

摘要

导言:用于治疗多发性硬化症(MS)的高疗效静脉注射疗法(HETs)给输液中心带来了沉重的资源配置和规划负担,导致治疗延误,并可能增加疾病活动突破的风险。仿真工具可用于系统分析能力情景,识别并更好地理解制约因素,从而使决策者能够优化患者护理。此前,我们曾应用离散事件模拟模型 ENTIMOS,利用伦敦查林十字医院神经科输液室的真实数据输入,评估了患者流量和护理服务的情景。该模型预测,在现有能力和预计需求的情况下,患者将在 30 个月内经历高风险的治疗延迟:这项研究旨在从神经科医生的角度解决多发性硬化症患者护理管理所面临的主要医疗挑战。我们使用 ENTIMOS 预测了几种不同的、临床上可行的情况对同一多发性硬化症输液室患者等待时间的影响,并量化了确保护理连续性所需的缓解策略:我们利用神经科专家的实际经验确定了五种临床情景:(方法:我们利用神经科专家的实际经验确定了五种临床情景:(1) 在同一医院环境中,将患者转为皮下注射(SC)相同治疗药物的 MS 治疗;(2) 将开放时间延长至周末;(3) 减少输液椅数量(模拟 2019 年冠状病毒病 [COVID-19] 大流行期间采用的社会隔离措施);(4) 增加输液需求;(5) 增加排班审批时间。患者等待下一次到期输液的时间和高风险治疗延迟时间(≥ 30 天)是分析模型的主要输出结果。之前公布的基本情况结果被用作参考。所有假设情景均在 3 年期限内运行(情景 1 除外,该情景在 3 年和 5 年期限内运行)。对缓解治疗延迟的策略进行了分析和讨论:结果:将 50%的患者转为在医院使用相同的治疗药物进行 SC 治疗,可将预测的高风险治疗延迟推迟到 3 年模拟时限之后不久(第 38 个月)。周末开放将等候时间从 20 天减少到 4 天,避免了治疗延误,但劳动力成本增加。减少输液椅使等待时间平均增加到 53 天,模拟结束时增加到 86 天,导致 6 个月内出现高风险治疗延误。输液需求的增加使等待时间平均增加到 26 天,模拟结束时增加到 47 天,导致高风险治疗延误 22 个月。延长排期审批时间既没有缩短等待时间,也没有推迟高风险治疗延误:决策者需要透明的能力限制,以便更好地规划输液室的资源配置和多发性硬化治疗。我们的研究结果表明,各种缓解措施,如每年增加输液椅、将患者转至其他输液室等,都有助于防止治疗延误。将患者从静脉注射转为使用相同治疗药物的皮下注射,可适度减少等待时间,并推迟高风险治疗延误。但从长远来看,这不足以防止高风险治疗延误。
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ENTIMOS: Decision Support Tool Highlights Potential Impact of Non-intravenous Therapies for Multiple Sclerosis on Patient Care via Clinical Scenario Simulation.

Introduction: Administration of intravenous (IV), high-efficacy treatments (HETs) for the treatment of multiple sclerosis (MS) poses a high resourcing and planning burden on infusion centres, resulting in treatment delays that may increase the risk of breakthrough disease activity. Simulation tools can be used to systematically analyse capacity scenarios and identify and better understand constraints, therefore enabling decision-makers to optimise patient care. We have previously applied ENTIMOS, a discrete event simulation model, to assess scenarios of patient flow and care delivery using real-life data inputs from the neurology infusion suite at Charing Cross Hospital London. The model predicted that, given current capacity and projected demand, patients would experience high-risk treatment delays within 30 months.

Objective: This study aimed to address key healthcare challenges for MS patient care management as seen from a neurologist's perspective. We used ENTIMOS to predict the impact of several distinct and clinically plausible scenarios on patient waiting times at the same MS infusion suite and to quantify mitigation strategies needed to assure continuity of care.

Methods: We used real-world experience of an expert neurologist to identify five clinical scenarios: (1) switching patients to a subcutaneous (SC) MS treatment of the same therapeutic agent, in the same hospital setting; (2) extending opening times to the weekend; (3) reducing the number of infusion chairs (to simulate social distancing measures applied during the coronavirus disease 2019 [COVID-19] pandemic); (4) increasing demand for infusions; and (5) increasing the scheduling approval time. Patient waiting time for next due infusion and time to high-risk treatment delays (≥ 30 days) were the main analysed model outputs. Previously published base case results were used as reference. All hypothetical scenarios were run over a 3-year horizon (with the exception of scenario 1, which was run over a 3- and 5-year horizon). Strategies to mitigate treatment delays were analysed and discussed.

Results: Switching 50% of patients to SC treatment of the same therapeutic agent administered in hospital postponed the predicted high-risk treatment delays to shortly beyond the 3-year simulation timeframe (month 38). Weekend opening reduced waiting times from 20 days to 4 days and prevented treatment delays, however, at elevated labour costs. Reducing the infusion chairs increased waiting time to 53 days on average and 86 days at the end of the simulation, leading to high-risk treatment delays within 6 months. An increased demand for infusions increased waiting time to 26 days on average and 47 days at the end of the simulation, leading to high-risk treatment delays within 22 months. Prolonged scheduling approval time did not reduce the waiting time, nor postpone the high-risk treatment delays.

Conclusion: Decision makers need transparency on capacity constraints to better plan resourcing at infusion suites and MS treatments. Our results showed that various mitigation measures, such as increasing capacity by additional infusion chairs per year and transferring patients to other infusion suites, may help prevent treatment delays. Switching patients from IV to an SC version of the same therapeutic agent reduced the waiting time moderately and postponed high-risk treatment delays. It was insufficient to prevent high-risk treatment delays in the long term.

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来源期刊
CiteScore
3.50
自引率
0.00%
发文量
64
审稿时长
8 weeks
期刊介绍: PharmacoEconomics - Open focuses on applied research on the economic implications and health outcomes associated with drugs, devices and other healthcare interventions. The journal includes, but is not limited to, the following research areas:Economic analysis of healthcare interventionsHealth outcomes researchCost-of-illness studiesQuality-of-life studiesAdditional digital features (including animated abstracts, video abstracts, slide decks, audio slides, instructional videos, infographics, podcasts and animations) can be published with articles; these are designed to increase the visibility, readership and educational value of the journal’s content. In addition, articles published in PharmacoEconomics -Open may be accompanied by plain language summaries to assist readers who have some knowledge of, but not in-depth expertise in, the area to understand important medical advances.All manuscripts are subject to peer review by international experts. Letters to the Editor are welcomed and will be considered for publication.
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