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背景在健康成人中针对心血管疾病(CVD)预防的病例主动发现策略是常见的,但是经济评估尚未针对该策略最有可能受益的人群进行调查。目的评估针对CVD预防的定向病例发现的成本效益。设计与场所英国基层医疗人群的成本效益建模。方法从健康改善网络数据库(一个大型基层医疗数据库)中抽样选取10 000例30~74岁且现无CVD或糖尿病的人群。采用离散事件仿真法模拟邀请人群进行评估的过程、评估心血管风险的过程和开始药物治疗和持续性药物治疗的过程。从基层医疗数据中获得风险因素和停药率。已发表的资料提供了对评估、治疗开始、治疗效果理解的估计。研究者通过机会性病例发现确定寿命成本和质量调整寿命年(QALYs),并确定根据年龄优先排序的策略,或根据患者预先估计的心血管风险的策略。如果一个QALY价值20 000英镑,这项研究便报道了最佳策略。结果与没有发现病例相比,在10 000人群中邀请30~74岁的所有成年人产生30.32个QALYs,总成本705 732英镑。最佳策略是根据预先风险估计对患者进行排序,并邀请8%的被评估为处在最高风险(预测患者生存10年间CVD风险≥12.76%)、产生17.53个QALYs、花费162 280英镑的人们。最佳策略邀请<35%的患者进行评估的可能有89.4%。结论在所有年龄范围的健康成人中使用CVD风险预先估计的定向病例发现比通用病例发现更有效。
Background The strategy of proactive detection of cases of cardiovascular disease (CVD) prevention is common in healthy adults, but economic assessments have not been investigated for those most likely to benefit from this strategy. Objective To evaluate the cost-effectiveness of targeted case-finding for CVD prevention. Design and Location Cost-benefit modeling of primary care populations in the United Kingdom. Methods A total of 10 000 people aged 30-74 years with no CVD or diabetes were selected from the Health Improvement Network database (a large primary medical database). Discrete event simulation is used to simulate the process of inviting people to assess, to assess the course of cardiovascular risk, and to the process of starting medication and continuing medication. Obtained risk factors and withdrawal rates from primary health care data. Published information provides an assessment of the assessment, the start of treatment, and an estimate of the effect of treatment. The investigators determined lifetime cost and quality adjusted life years (QALYs) through opportunistic case finding and identified age-prioritized strategies, or based on patient pre-estimated cardiovascular risk strategies. If a QALY is worth £ 20,000, the study reports the best strategy. Results All 30 to 74 adults were invited to produce 30.32 QALYs out of a 10,000 population, at a total cost of 705 732 pounds, compared to an unidentified case. The best strategy is to rank patients based on a priori risk estimate and invite 8% of people who are assessed to be at the highest risk (predicting a 10-year CVD risk for patients to survive ≥12.76%), producing 17.53 QALYs for £ 162,280. The best strategy to invite <35% of patients to assess the possible 89.4%. Conclusions Directional case predictions estimated in advance using CVD risk in healthy adults of all age ranges are more effective than the common case finding.