医疗保健
心理干预
干预(咨询)
精算学
价值(数学)
成本效益分析
风险分析(工程)
人口
医学
成本效益
经济
计算机科学
护理部
环境卫生
经济增长
机器学习
作者
Matthew Greenhawt,John Oppenheimer,Christopher D. Codispoti
标识
DOI:10.1016/j.jaip.2021.10.006
摘要
Cost-effectiveness analysis is a way to understand the value of a health care intervention in terms of assessing the money spent to produce beneficial outcomes. Cost-effectiveness analyses are used by various stakeholders for such purposes because health care resources and financing may be scarce, depending on the economy, and certain interventions may be costly to produce such outcomes compared with other options. These analyses are built on well-researched and robust inputs for costs and outcomes and may be modeled using a technique called Markov chain models, which allow transitions among various health states (eg, alive, dead, outgrow allergy, allergy relapses) relative to the condition of interest to reflect a base-case scenario. Then, the margins of the inputs are explored for a sensitivity analysis of potential findings. These analyses should be investigated from multiple perspectives (eg, society, health care payer). Limitations of the analysis should be clearly stated. Although such models are an informative way to explore a situation and can be performed without additional direct patient intervention, a weakness of the approach is that this may overlook individual patient nuances. Cost-effectiveness analyses are important policy tools to show, on average, an optimal way to improve value in population health.
科研通智能强力驱动
Strongly Powered by AbleSci AI