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Background: 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. Methods: 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. Findings: 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. Interpretation: 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. Funding: Research Impact Fund from the University Grants Committee, Research Grants Council with matching fund from the Hong Kong Association of Pharmaceutical Industry (R7007-22).
RESUMO
OBJECTIVE: The relative effects of various cardiovascular diseases (CVDs) and varying severity of chronic kidney disease (CKD) on mortality risk, direct medical cost, and life expectancy in patients with diabetes are unclear. The aim of this study was to evaluate these associations. RESEARCH DESIGN AND METHODS: This was a retrospective cohort study that included 208,792 adults with diabetes stratified into 12 disease status groups with varying combinations of heart disease, stroke, moderate CKD (estimated glomerular filtration rate [eGFR] 30-59 mL/min/1.73 m2) and severe CKD (eGFR <30 mL/min/1.73 m2) in 2008-2010. The effect of risk of mortality, annual direct medical costs, and life expectancy were assessed using Cox regression, gamma generalized linear method with log-link function, and flexible parametric survival models. RESULTS: Over a median follow-up of 8.5 years (1.6 million patient-years), 50,154 deaths were recorded. Mortality risks for patients with only a single condition among heart disease, stroke, and moderate CKD were similar. The mortality risks were 1.75 times, 2.63 times, and 3.58 times greater for patients with one, two, and all three conditions (consisting of stroke, heart disease, and moderate CKD), compared with patients without these diseases, suggesting an independent and individually additive effect for any combination. A similar trend was observed in annual public health care costs with 2.91-, 3.90-, and 3.88-fold increased costs for patients with one, two, and three conditions, respectively. Increases in the number of conditions reduced life expectancy greatly, particularly in younger patients. Reduction in life expectancy for a 40-year-old with one, two, and three conditions was 20, 25, and 30 years for men and 25, 30, and 35 years, respectively, for women. A similar trend of greater magnitude was observed for severe CKD. CONCLUSIONS: The effects of heart diseases, stroke, CKD, and the combination of these conditions on all-cause mortality and direct medical costs are independent and cumulative. CKD, especially severe CKD, appears to have a particularly significant impact on life expectancy and direct medical costs in patients with diabetes. These findings support the importance of preventing both CVD and CKD in patients with diabetes.
