Estimating Taiwan's QALY league table for catastrophic illnesses: Providing real-world evidence to integrate prevention with treatment for resources allocation
{"title":"Estimating Taiwan's QALY league table for catastrophic illnesses: Providing real-world evidence to integrate prevention with treatment for resources allocation","authors":"","doi":"10.1016/j.jfma.2024.05.011","DOIUrl":null,"url":null,"abstract":"<div><h3>Background/purpose</h3><div>Curative technologies improve patient's survival and/or quality of life but increase financial burdens. Effective prevention benefits all three. We summarize estimation methods and provide examples of how much money is spent per quality-adjusted life year (QALY) or life year (LY) on treating a catastrophic illness under a lifetime horizon and how many QALYs/LYs and lifetime medical costs (LMC) could be potentially saved by prevention.</div></div><div><h3>Methods</h3><div>We established cohorts by interlinkages of Taiwan's nation-wide databases including National Health Insurance. We developed methods to estimate lifetime survival functions, which were multiplied with the medical costs and/or quality of life and summed up to estimate LMC, quality-adjusted life expectancy (QALE) and lifetime average cost per QALY/LY for catastrophic illnesses. By comparing with the age-, sex-, and calendar year-matched referents simulated from vital statistics, we obtained the loss-of-QALE and loss-of-life expectancy (LE).</div></div><div><h3>Results</h3><div>The lifetime cost-effectiveness ratios of ventilator-dependent comatose patients, dialysis, spinal cord injury, major trauma, and cancers were US$ 96,800, 16,200–20,000, 5500–5,900, 3400–3,600, and 2900–11,900 per QALY or LY, respectively. The successful prevention of lung, liver, oral, esophagus, stomach, nasopharynx, or ovary cancer would potentially save US$ 28,000–97,000 and > 10 QALYs; whereas those for end-stage kidney disease, stroke, spinal injury, or major trauma would be US$ 55,000–300,000 and 10–14 QALYs. Loss-of-QALE and loss-of-LE were less confounded indicators for comparing the lifetime health benefits of different technologies estimated from real-world data.</div></div><div><h3>Conclusions</h3><div>Integration of prevention with treatment for resources allocation seems feasible and would improve equity and efficiency.</div></div>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S092966462400247X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
Background/purpose
Curative technologies improve patient's survival and/or quality of life but increase financial burdens. Effective prevention benefits all three. We summarize estimation methods and provide examples of how much money is spent per quality-adjusted life year (QALY) or life year (LY) on treating a catastrophic illness under a lifetime horizon and how many QALYs/LYs and lifetime medical costs (LMC) could be potentially saved by prevention.
Methods
We established cohorts by interlinkages of Taiwan's nation-wide databases including National Health Insurance. We developed methods to estimate lifetime survival functions, which were multiplied with the medical costs and/or quality of life and summed up to estimate LMC, quality-adjusted life expectancy (QALE) and lifetime average cost per QALY/LY for catastrophic illnesses. By comparing with the age-, sex-, and calendar year-matched referents simulated from vital statistics, we obtained the loss-of-QALE and loss-of-life expectancy (LE).
Results
The lifetime cost-effectiveness ratios of ventilator-dependent comatose patients, dialysis, spinal cord injury, major trauma, and cancers were US$ 96,800, 16,200–20,000, 5500–5,900, 3400–3,600, and 2900–11,900 per QALY or LY, respectively. The successful prevention of lung, liver, oral, esophagus, stomach, nasopharynx, or ovary cancer would potentially save US$ 28,000–97,000 and > 10 QALYs; whereas those for end-stage kidney disease, stroke, spinal injury, or major trauma would be US$ 55,000–300,000 and 10–14 QALYs. Loss-of-QALE and loss-of-LE were less confounded indicators for comparing the lifetime health benefits of different technologies estimated from real-world data.
Conclusions
Integration of prevention with treatment for resources allocation seems feasible and would improve equity and efficiency.