Yao Guiqing Lily, Novielli Nicola, Manaseki-Holland Semira, Chen Yen-Fu, van der Klink Marcel, Barach Paul, Chilton Peter J, Lilford Richard J
Department of Public Health, Epidemiology and Biostatistics, University of Birmingham, Birmingham, UK.
BMJ Qual Saf. 2012 Dec;21 Suppl 1(Suppl_1):i29-38. doi: 10.1136/bmjqs-2012-001210. Epub 2012 Sep 13.
We developed a method to estimate the expected cost-effectiveness of a service intervention at the design stage and 'road-tested' the method on an intervention to improve patient handover of care between hospital and community.
The development of a nine-step evaluation framework: 1. Identification of multiple endpoints and arranging them into manageable groups; 2. Estimation of baseline overall and preventable risk; 3. Bayesian elicitation of expected effectiveness of the planned intervention; 4. Assigning utilities to groups of endpoints; 5. Costing the intervention; 6. Estimating health service costs associated with preventable adverse events; 7. Calculating health benefits; 8. Cost-effectiveness calculation; 9. Sensitivity and headroom analysis.
Literature review suggested that adverse events follow 19% of patient discharges, and that one-third are preventable by improved handover (ie, 6.3% of all discharges). The intervention to improve handover would reduce the incidence of adverse events by 21% (ie, from 6.3% to 4.7%) according to the elicitation exercise. Potentially preventable adverse events were classified by severity and duration. Utilities were assigned to each category of adverse event. The costs associated with each category of event were obtained from the literature. The unit cost of the intervention was €16.6, which would yield a Quality Adjusted Life Year (QALY) gain per discharge of 0.010. The resulting cost saving was €14.3 per discharge. The intervention is cost-effective at approximately €214 per QALY under the base case, and remains cost-effective while the effectiveness is greater than 1.6%.
We offer a usable framework to assist in ex ante health economic evaluations of health service interventions.
我们开发了一种在设计阶段估算服务干预预期成本效益的方法,并在一项旨在改善医院与社区之间患者护理交接的干预措施上对该方法进行了“实地测试”。
开发一个九步评估框架:1. 识别多个终点并将其分组以便管理;2. 估算基线总体风险和可预防风险;3. 采用贝叶斯方法得出计划干预措施的预期效果;4. 为终点组赋予效用值;5. 计算干预措施的成本;6. 估算与可预防不良事件相关的卫生服务成本;7. 计算健康效益;8. 计算成本效益;9. 敏感性和净空分析。
文献综述表明,19%的患者出院后会出现不良事件,其中三分之一可通过改善交接来预防(即占所有出院患者的6.3%)。根据推导结果,改善交接的干预措施将使不良事件发生率降低21%(即从6.3%降至4.7%)。潜在可预防的不良事件按严重程度和持续时间进行分类。为每类不良事件赋予效用值。各类事件的相关成本从文献中获取。干预措施的单位成本为16.6欧元,每次出院可带来0.010个质量调整生命年(QALY)的收益。每次出院可节省成本14.3欧元。在基础案例下,该干预措施每获得一个QALY的成本约为214欧元,具有成本效益,并且在效果大于1.6%时仍具有成本效益。
我们提供了一个可用的框架,以协助对卫生服务干预措施进行事前卫生经济评估。