Richard Nicholas, Erik Scalfaro, Rachel Dorsey, Zuzanna Angehrn, Judit Banhazi, Roisin Brennan, Nicholas Adlard
{"title":"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。","authors":"Richard Nicholas, Erik Scalfaro, Rachel Dorsey, Zuzanna Angehrn, Judit Banhazi, Roisin Brennan, Nicholas Adlard","doi":"10.1007/s41669-024-00493-8","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>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.</p><p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":19770,"journal":{"name":"PharmacoEconomics Open","volume":" ","pages":"755-764"},"PeriodicalIF":2.0000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11362419/pdf/","citationCount":"0","resultStr":"{\"title\":\"ENTIMOS: Decision Support Tool Highlights Potential Impact of Non-intravenous Therapies for Multiple Sclerosis on Patient Care via Clinical Scenario Simulation.\",\"authors\":\"Richard Nicholas, Erik Scalfaro, Rachel Dorsey, Zuzanna Angehrn, Judit Banhazi, Roisin Brennan, Nicholas Adlard\",\"doi\":\"10.1007/s41669-024-00493-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>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.</p><p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":19770,\"journal\":{\"name\":\"PharmacoEconomics Open\",\"volume\":\" \",\"pages\":\"755-764\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2024-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11362419/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"PharmacoEconomics Open\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s41669-024-00493-8\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/7/11 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"PharmacoEconomics Open","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s41669-024-00493-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/11 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
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.
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.