A Digital Software Support Platform for Hyperthyroidism Management in South Korea: Markov Simulation Model-Based Cost-Effectiveness Analysis.

IF 6.2 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Jung Hyun Kim, Jaeyong Shin, Man S Kim, Jae Hoon Moon
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引用次数: 0

Abstract

Background: The integration of wearable technology for heart rate monitoring offers potential advancements in managing hyperthyroidism by providing a feasible way to track thyroid function. Although digital health solutions are gaining traction in various chronic conditions, their cost-effectiveness in hyperthyroidism management requires deeper investigation.

Objective: This study aimed to evaluate the cost-effectiveness of a wearable or mobile-based thyroid function digital monitoring solution for hyperthyroidism management and to make a comparison with the existing standard approach within the South Korean health care context.

Methods: We developed a decision-analytic Markov microsimulation model to simulate the cost and effectiveness of digital monitoring in a cohort of 10,000 hypothetical hyperthyroidism patients aged 40 years. The analysis was conducted from the perspective of the health care system, with a 4.5% annual discount rate applied to costs and effectiveness and an inflation adjustment to 2022 values. Model inputs were sourced from clinical studies, publicly available datasets, and expert input, with outcomes measured in quality-adjusted life years (QALYs). Cost-effectiveness was evaluated through incremental cost-effectiveness ratios (ICERs) and net monetary benefits (NMB), with additional deterministic and probabilistic sensitivity analyses performed to address input uncertainties.

Results: Integrating digital monitoring yielded an additional 0.32 QALYs per patient at an incremental cost of US $3143, resulting in an ICER of US $9804.30 per QALY, significantly below the South Korean willingness-to-pay threshold of US $32,255/QALY. The digitally supported group exhibited improved rates of long-term remission (22.68%, 2268/10,000) and reduced postremission relapse (17.87%, 1787/10,000) compared to standard care (17.48%, 1748/10,000 and 26.37%, 2637/10,000, respectively). Probabilistic sensitivity analysis showed that digital intervention was the preferred cost-effective strategy in 64.4% (6440/10,000) of iterations. Subscription costs of the digital platform and the utility weight for thyroid-associated orbitopathy emerged as key factors affecting the ICER in sensitivity analyses.

Conclusions: The findings suggest that digital monitoring provides a cost-effective strategy for enhancing hyperthyroidism management, supporting sustained remission, and reducing relapse rates. As such, digital solutions could serve as a valuable adjunct to traditional care, with the cost-effectiveness analysis providing an economic basis for determining pricing and value-based reimbursement in health care systems. The study underscores the importance of integrating digital solutions in chronic disease management and suggests that further research should include societal costs, such as productivity, to capture economic benefits fully.

韩国甲状腺机能亢进管理的数字软件支持平台:基于马尔可夫模拟模型的成本-效果分析。
背景:可穿戴式心率监测技术的集成提供了一种跟踪甲状腺功能的可行方法,为甲状腺功能亢进的治疗提供了潜在的进步。尽管数字健康解决方案在各种慢性疾病中越来越受欢迎,但其在甲状腺功能亢进管理中的成本效益需要更深入的研究。目的:本研究旨在评估可穿戴或基于移动的甲状腺功能数字监测解决方案用于甲状腺功能亢进管理的成本效益,并与韩国医疗保健背景下现有的标准方法进行比较。方法:我们建立了一个决策分析马尔可夫微观模拟模型,以模拟1万名40岁甲亢患者的数字监测成本和效果。该分析是从医疗保健系统的角度进行的,对成本和有效性采用4.5%的年贴现率,并将通货膨胀调整为2022年的价值。模型输入来自临床研究、公开数据集和专家输入,结果以质量调整生命年(QALYs)衡量。通过增量成本效益比(ICERs)和净货币效益(NMB)评估成本效益,并进行额外的确定性和概率敏感性分析以解决输入的不确定性。结果:整合数字监测使每位患者额外获得0.32个QALY,增量成本为3143美元,导致每个QALY的ICER为9804.30美元,显著低于韩国的支付意愿阈值32,255美元/QALY。与标准治疗(分别为17.48%,1748/10,000和26.37%,2637/10,000)相比,数字支持组的长期缓解率(22.68%,2268/10,000)和缓解后复发率(17.87%,1787/10,000)均有所提高。概率敏感性分析表明,在64.4%(6440/ 10000)的迭代中,数字干预是首选的成本效益策略。在敏感性分析中,数字平台的订阅费用和甲状腺相关眼病的效用权重成为影响ICER的关键因素。结论:研究结果表明,数字监测为加强甲状腺功能亢进管理、支持持续缓解和降低复发率提供了一种具有成本效益的策略。因此,数字解决方案可以作为传统护理的一种有价值的辅助手段,成本效益分析为确定医疗保健系统的定价和基于价值的报销提供了经济基础。该研究强调了将数字解决方案整合到慢性病管理中的重要性,并建议进一步的研究应包括生产力等社会成本,以充分获取经济效益。
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
JMIR mHealth and uHealth
JMIR mHealth and uHealth Medicine-Health Informatics
CiteScore
12.60
自引率
4.00%
发文量
159
审稿时长
10 weeks
期刊介绍: JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a spin-off journal of JMIR, the leading eHealth journal (Impact Factor 2016: 5.175). JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, and Science Citation Index Expanded (SCIE), and in June 2017 received a stunning inaugural Impact Factor of 4.636. The journal focusses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics. JMIR mHealth and uHealth publishes since 2013 and was the first mhealth journal in Pubmed. It publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research.
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