S. Fagiuoli, L. Pasulo, F. Maggiolo, R. Spinella, P. Poggio, R. Boldizzoni, M. D. Marco, A. Aronica, C. Benedetti, P. Correale, C. Garavaglia, C. Nicora
{"title":"不同组织模式对丙型肝炎患者管理的经济评价","authors":"S. Fagiuoli, L. Pasulo, F. Maggiolo, R. Spinella, P. Poggio, R. Boldizzoni, M. D. Marco, A. Aronica, C. Benedetti, P. Correale, C. Garavaglia, C. Nicora","doi":"10.7175/FE.V20I1.1374","DOIUrl":null,"url":null,"abstract":"BACKGROUND: Access to Directly Acting Antivirals (DAAs) for Hepatitis C Virus (HCV) treatment in Italy was initially restricted to severe patients. In 2017, AIFA expanded access to all patients, to achieve elimination by 2030.AIM: To investigate the impact of different hospitals’ organizational models on elimination timing, treatment capacity and direct costs.METHODS: Most Regional healthcare systems in Italy deploy a Center of Excellence (CoE) organizational model, where patients are referred to a single major hospital in the area, which is the only one that can prescribe and deliver DAAs. The study was conducted at Bergamo’s (Lombardy, Italy) Papa Giovanni XXIII hospital (PG-23), which deploys a Hub&Spoke model: the Hub (PG-23) prescribes and delivers DAAs while Spokes (four smaller hospitals) can only prescribe them. The study compares the two models (CoE vs. H&S). Patient journey and workloads were mapped and quantified through interviews with hospital stakeholders. Cost data were collected through the hospital’s IT system; the sample comprised 2,277 HCV patients, over one year.RESULTS: The study calculated the average cost to treat HCV patients (~ € 1,470 per patient). Key cost drivers are lab tests (60%) and specialist visits (30%). Over one year, H&S can treat 68% more patients than CoE. 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引用次数: 1
摘要
背景:在意大利,用于丙型肝炎病毒(HCV)治疗的直接作用抗病毒药物(DAAs)最初仅限于重症患者。2017年,AIFA扩大了对所有患者的覆盖,目标是到2030年实现消除。目的:探讨不同医院组织模式对消除时间、治疗能力和直接成本的影响。方法:意大利大多数区域医疗保健系统采用卓越中心(CoE)组织模式,患者被转介到该地区的一家大医院,这是唯一一家可以开处方和提供daa的医院。这项研究是在贝加莫(意大利伦巴第)Papa Giovanni XXIII医院(PG-23)进行的,该医院采用Hub和spoke模式:Hub (PG-23)开处方并提供daa,而Spokes(四家较小的医院)只能开处方。该研究比较了两种模型(CoE与H&S)。通过与医院利益相关者的访谈,绘制和量化了患者的旅程和工作量。成本数据通过医院的IT系统收集;该样本包括2277名HCV患者,持续时间超过一年。结果:该研究计算了治疗HCV患者的平均成本(每名患者约1470欧元)。主要的成本驱动因素是实验室检测(60%)和专家就诊(30%)。在一年的时间里,H&S比CoE多治疗68%的患者。由于延迟就诊的患者占总费用的40%,“优化”模式通过简化专家就诊并在随访期间让全科医生参与来设计。与CoE相比,“优化”模型提高了治疗能力,并将延迟患者的成本降低了72%。结论:研究表明组织模式对有效实现2030年消除的重要性。
Economic Evaluation of Different Organizational Models for the Management of Patients with Hepatitis C
BACKGROUND: Access to Directly Acting Antivirals (DAAs) for Hepatitis C Virus (HCV) treatment in Italy was initially restricted to severe patients. In 2017, AIFA expanded access to all patients, to achieve elimination by 2030.AIM: To investigate the impact of different hospitals’ organizational models on elimination timing, treatment capacity and direct costs.METHODS: Most Regional healthcare systems in Italy deploy a Center of Excellence (CoE) organizational model, where patients are referred to a single major hospital in the area, which is the only one that can prescribe and deliver DAAs. The study was conducted at Bergamo’s (Lombardy, Italy) Papa Giovanni XXIII hospital (PG-23), which deploys a Hub&Spoke model: the Hub (PG-23) prescribes and delivers DAAs while Spokes (four smaller hospitals) can only prescribe them. The study compares the two models (CoE vs. H&S). Patient journey and workloads were mapped and quantified through interviews with hospital stakeholders. Cost data were collected through the hospital’s IT system; the sample comprised 2,277 HCV patients, over one year.RESULTS: The study calculated the average cost to treat HCV patients (~ € 1,470 per patient). Key cost drivers are lab tests (60%) and specialist visits (30%). Over one year, H&S can treat 68% more patients than CoE. As deferred patients absorb up to 40% of total costs, the “Optimized” model was designed by streamlining specialists’ visits and involving general practitioners during follow-up. “Optimized” model increases treatment capacity and reduces costs of deferred patients by 72% vs CoE.CONCLUSION: The study demonstrates the importance of organizational models in efficiently achieving 2030 elimination.