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Cost-Effectiveness of Pain Management Strategies in Advanced Cancer

心理干预 经济评价 成本效益 医学 质量调整寿命年 干预(咨询) 生活质量(医疗保健) 成本效益分析 医疗保健 成本效益分析 癌症疼痛 物理疗法 癌症 风险分析(工程) 护理部 内科学 病理 经济 生物 经济增长 生态学
作者
David Meads,John O’Dwyer,Claire Hulme,Rocío Rodriguez López,Mike Bennett
出处
期刊:International Journal of Technology Assessment in Health Care [Cambridge University Press]
卷期号:35 (2): 141-149 被引量:13
标识
DOI:10.1017/s0266462319000114
摘要

Abstract Objectives Uncontrolled pain in advanced cancer is a common problem and has significant impact on individuals’ quality of life and use of healthcare resources. Interventions to help manage pain at the end of life are available, but there is limited economic evidence to support their wider implementation. We conducted a case study economic evaluation of two pain self-management interventions (PainCheck and Tackling Cancer Pain Toolkit [TCPT]) compared with usual care. Methods We generated a decision-analytic model to facilitate the evaluation. This modelled the survival of individuals at the end of life as they moved through pain severity categories. Intervention effectiveness was based on published meta-analyses results. The evaluation was conducted from the perspective of the U.K. health service provider and reported cost per quality-adjusted life-year (QALY). Results PainCheck and TCPT were cheaper (respective incremental costs -GBP148 [-EUR168.53] and -GBP474 [-EUR539.74]) and more effective (respective incremental QALYs of 0.010 and 0.013) than usual care. There was a 65 percent and 99.5 percent chance of cost-effectiveness for PainCheck and TCPT, respectively. Results were relatively robust to sensitivity analyses. The most important driver of cost-effectiveness was level of pain reduction (intervention effectiveness). Although cost savings were modest per patient, these were considerable when accounting for the number of potential intervention beneficiaries. Conclusions Educational and monitoring/feedback interventions have the potential to be cost-effective. Economic evaluations based on estimates of effectiveness from published meta-analyses and using a decision modeling approach can support commissioning decisions and implementation of pain management strategies.
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