爱尔兰LCS经济评估议定书:建模成本,资格和结果
Tatiana Bezdenezhnykh1, James O'Mahony2, Benjamin Jacob1
1General Practice, Royal College of Surgeons in Ireland, Dublin, Leinster, Ireland.
HRB open research
|September 10, 2025
概括
本研究评估了肺癌治疗的经济影响和爱尔兰低剂量计算机断层扫描 (LDCT) 查的成本效益. 调查结果将为制定国家肺癌查计划提供信息.
科学领域:
- 卫生经济学 卫生经济学
- 公共卫生政策 公共卫生政策
- 在瘤学瘤学.
背景情况:
- 肺癌是爱尔兰癌症死亡的主要原因,没有现有的国家查计划.
- 低剂量计算机断层扫描 (LDCT) 查可以在高风险群体中将肺癌死亡率降低20%,但其在爱尔兰的成本效益尚不清楚.
- 关于肺癌的经济负担和查可行性的证据对于政策决策至关重要.
研究的目的:
- 评估爱尔兰肺癌护理的经济影响.
- 评估LDCT肺癌查的成本效益.
- 为资源分配和制定有关肺癌查的政策产生证据.
主要方法:
- 使用动态马尔科夫模型与人口统计,人口预测和吸烟史数据估计查资格.
- 使用离散事件模拟 (DES) 来进行特定阶段的成本分析,使用来自国家癌症和医疗保健登记处的数据.
- 适应英国肺癌自然史模型 (更新的ENaBL 2022) 进行成本效益分析,结合爱尔兰特有的数据和质量调整后寿命年 (QALYs).
主要成果:
- 该研究计划将产生证据,为在爱尔兰设计一个具有成本效益的肺癌查 (LCS) 计划提供信息.
- 结果将指导医疗保健规划和优化查策略.
- 该研究旨在支持针对肺癌预防和管理的可持续政策决策.
结论:
- 这项研究对于在爱尔兰建立一个具有成本效益的肺癌查计划至关重要.
- 这些发现将为医疗保健规划和政策制定提供关键数据.
- 优化查策略将有助于降低肺癌死亡率并改善患者的治疗结果.
相关概念视频
01:25Statistical Methods for Analyzing Epidemiological Data
900
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
900
01:21Cancer Survival Analysis
650
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
650
01:20Actuarial Approach
290
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
290