Cost-effectiveness Analysis of a Personalized, Teleretinal-Inclusive Screening Policy for Diabetic Retinopathy via Markov Modeling
Cost-effectiveness Analysis of a Personalized, Teleretinal-Inclusive Screening Policy for Diabetic Retinopathy via Markov Modeling
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DOI：
10.1016/j.oret.2023.01.001
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发表时间：
2023-06-01
影响因子：
4.5
通讯作者：
Lee, Taewoo
中科院分区：
文献类型：
--
作者：
Dorali, Poria;Shahmoradi, Zahed;Lee, Taewoo
目的：尽管电视成像已被证明在增加糖尿病视网膜病变(DR)的人群水平的筛查中是有效的，但对于如何将电视成像纳入现有的筛查指南尚缺乏定量的理解。我们开发了一个数学模型来确定个性化的DR筛查建议，该模型利用远程成像并评估个性化筛查策略的成本-效果。设计：采用部分可观测的马尔可夫决策过程来确定基于患者依从性、支付意愿和A1C水平的个性化筛查建议。采用确定性敏感度分析评价患者特定因素对个体化筛查策略的影响。采用隐马尔可夫链蒙特卡罗模拟对一个基于数据的假设队列进行成本-效果评价。参与者：基于文献资料和哈里斯卫生系统2013-2020年接受电视影像检查的2457名患者的电子病历，对具有参数的50万名患者的假设队列进行了模拟。干预措施包括扩张性眼底检查，称为临床筛查、电视成像和等待和观看建议。主要观察指标：基于患者特定因素的个性化筛查建议。不同筛查政策下每个患者的累积质量调整寿命年(QALY)和成本(美元)。增量成本-效果比比较不同的政策。结果：对于基础队列，平均而言，在每个患者的一生中，86.7%的时间建议进行远程成像。基于模型的个性化保单主导了其他标准化保单，为至少57%的基本队列带来了更多的QALY收益和成本节约。在基础队列、Harris健康特定队列和农村人群情景分析的敏感性分析中也观察到了类似的结果。结论：建立了一个数学模型作为决策支持工具，以确定结合远程影像和临床筛查的个性化筛查策略，并适应患者的特征。与当前的标准化政策相比，基于模型的政策显著降低了成本，而在QALY收益方面，它的表现即使不是更好，也是相当的。个性化的DR筛查方法具有显著的潜在好处，值得进一步探索。财务披露(S)：参考文献后可能会发现专有或商业披露。眼科Retina 2023；7：532-542&Copy；2023，美国眼科学会
Purpose: Although teleretinal imaging has proved effective in increasing population-level screening for diabetic retinopathy (DR), there is a lack of quantitative understanding of how to incorporate teleretinal imaging into existing screening guidelines. We develop a mathematical model to determine personalized DR screening recommendations that utilize teleretinal imaging and evaluate the cost-effectiveness of the personalized screening policy.Design: A partially observable Markov decision process is employed to determine personalized screening recommendations based on patient compliance, willingness to pay, and A1C level. Deterministic sensitivity analysis was conducted to evaluate the impact of patient-specific factors on personalized screening policy. The cost-effectiveness of identified screening policies was evaluated via hidden-Markov chain Monte Carlo simulation on a data-based hypothetical cohort.Participants: Screening policies were simulated for a hypothetical cohort of 500 000 patients with param-eters based on the literature and electronic medical records of 2457 patients who received teleretinal imaging from 2013 to 2020 from the Harris Health System.Methods: Population-based mathematical modeling study. Interventions included dilated fundus examina-tions referred to as clinical screening, teleretinal imaging, and wait and watch recommendations.Main Outcome Measures: Personalized screening recommendations based on patient-specific factors. Accumulated quality-adjusted life-years (QALYs) and cost (USD) per patient under different screening policies. Incremental cost-effectiveness ratio to compare different policies.Results: For the base cohort, on average, teleretinal imaging was recommended 86.7% of the time over each patient's lifetime. The model-based personalized policy dominated other standardized policies, generating more QALY gains and cost savings for at least 57% of the base cohort. Similar outcomes were observed in sensitivity analyses of the base cohort and the Harris Health-specific cohort and rural population scenario analysis.Conclusions: A mathematical model was developed as a decision support tool to identify a personalized screening policy that incorporates both teleretinal imaging and clinical screening and adapts to patient charac-teristics. Compared with current standardized policies, the model-based policy significantly reduces costs, whereas it is performing comparably, if not better, in terms of QALY gain. A personalized approach to DR screening has significant potential benefits that warrant further exploration.Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references. Ophthalmology Retina 2023;7:532-542 & COPY; 2023 by the American Academy of Ophthalmology