■基于真实世界的数据,我们开发了一个10年预测模型,从公共医疗系统支付者的角度估计抑郁症患者的负担,为香港的早期资源规划提供信息.
■我们开发了一个马尔可夫队列模型,该模型具有每年的周期,专门捕获了疾病过程中难治性抑郁症(TRD)和合并症发展的途径。预计从2023年到2032年,主要结果包括全因和精神病护理的费用,次要结果是全因死亡,多年的生活,和质量调整寿命年。使用全港的电子病历,我们从2014年到2016年,确定了25,190名年龄≥10岁的新诊断抑郁症患者,随访至2020年,以观察真实世界的事件时间模式,在此基础上,使用负二项建模和参数生存分析得出成本和时变过渡输入。我们将模型应用于两个封闭队列,它研究了2023年的事件患者的固定队列和开放队列,从2014年到2032年,按年份介绍了事件患者。公用事业和年度新患者来自已发布的来源。
■在2023年有9217名新患者,我们的封闭队列模型预测,全因和精神病护理的10年累计费用将达到3.09亿美元和5830亿美元,分别,到2032年,899人死亡(病死率:9.8%)。在我们的开放队列模型中,55,849-57,896例活跃的流行病例将花费超过3223亿美元和6070万美元,分别,从2023年到2032年,每年有超过943人死亡。少于20%的病例会患有TRD或合并症,但占费用的31-54%。最大的集体负担发生在40岁以上的女性中,但65岁以上和25岁以下有病史的男性每患者年的费用最高。关键的成本驱动因素与疾病早期阶段有关。
■有限比例的患者会发生TRD和合并症,但导致高比例的费用,这就需要适当的关注和资源分配。我们的预测还展示了现实数据在长期成本和死亡率建模中的应用,这有助于政策制定者预测可预见的负担,并进行预算规划,为替代方案中的护理需求做好准备。
■来自大学资助委员会的研究影响基金,研究资助委员会与香港制药业协会(R7007-22)的配套基金。
UNASSIGNED: Based on real-world data, we developed a 10-year prediction model to estimate the burden among patients with depression from the public healthcare system payer\'s perspective to inform early resource planning in Hong Kong.
UNASSIGNED: We developed a Markov cohort model with yearly cycles specifically capturing the pathway of treatment-resistant depression (TRD) and comorbidity development along the disease course. Projected from 2023 to 2032, primary outcomes included costs of all-cause and psychiatric care, and secondary outcomes were all-cause deaths, years of life lived, and quality-adjusted life-years. Using the territory-wide electronic medical records, we identified 25,190 patients aged ≥10 years with newly diagnosed depression from 2014 to 2016 with follow-up until 2020 to observe the real-world time-to-event pattern, based on which costs and time-varying transition inputs were derived using negative binomial modelling and parametric survival analysis. We applied the model as both closed cohort, which studied a fixed cohort of incident patients in 2023, and open cohort, which introduced incident patients by year from 2014 to 2032. Utilities and annual new patients were from published sources.
UNASSIGNED: With 9217 new patients in 2023, our closed cohort model projected the 10-year cumulative costs of all-cause and psychiatric care to reach US$309.0 million and US$58.3 million, respectively, with 899 deaths (case fatality rate: 9.8%) by 2032. In our open cohort model, 55,849-57,896 active prevalent cases would cost more than US$322.3 million and US$60.7 million, respectively, with more than 943 deaths annually from 2023 to 2032. Fewer than 20% of cases would live with TRD or comorbidities but contribute 31-54% of the costs. The greatest collective burden would occur in women aged above 40, but men aged above 65 and below 25 with medical history would have the highest costs per patient-year. The key cost drivers were relevant to the early disease stages.
UNASSIGNED: A limited proportion of patients would develop TRD and comorbidities but contribute to a high proportion of costs, which necessitates appropriate attention and resource allocation. Our projection also demonstrates the application of real-world data to model long-term costs and mortality, which aid policymakers anticipate foreseeable burden and undertake budget planning to prepare for the care need in alternative scenarios.
UNASSIGNED: Research Impact Fund from the University Grants Committee, Research Grants Council with matching fund from the Hong Kong Association of Pharmaceutical Industry (R7007-22).