Miranda Rafael N, Austin Peter C, Fremes Stephen E, Mamas Mamas A, Sud Maneesh K, Naimark David M J, Wijeysundera Harindra C
Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto M5T 3M6, Canada.
ICES, Toronto M4N 3M5, Canada.
Eur Heart J Qual Care Clin Outcomes. 2025 Jan 16;11(1):10-18. doi: 10.1093/ehjqcco/qcae059.
Demand for transcatheter aortic valve implantation (TAVI) has increased in the last decade, resulting in prolonged wait-times and undesirable health outcomes in many health systems. Risk-based prioritization and wait-times benchmarks can improve equitable access to patients.
We used simulation models to follow-up a synthetic population of 50 000 individuals from referral to completion of TAVI. Based on their risk of adverse events, patients could be classified as 'low-', 'medium-', and 'high-risk', and shorter wait-times were assigned for the higher risk groups. We assessed the impacts of the size and wait-times for each risk group on waitlist mortality, hospitalization, and urgent TAVIs. All scenarios had the same resource constraints, allowing us to explore the trade-offs between faster access for prioritized patients and deferred access for non-prioritized groups. Increasing the proportion of patients categorized as high-risk, and providing more rapid access to the higher-risk groups achieved the greatest reductions in mortality, hospitalizations and urgent TAVIs (relative reductions of up to 29%, 23%, and 38%, respectively). However, this occurs at the expense of excessive wait-times in the non-prioritized low-risk group (up to 25 weeks). We propose wait-times of up to 3 weeks for high-risk patients and 7 weeks for medium-risk patients.
Prioritizing higher-risk patients with faster access leads to better health outcomes, however this also results in unacceptably long wait-times for the non-prioritized groups in settings with limited capacity. Decision-makers must be aware of these implications when developing and implementing waitlist prioritization strategies.
在过去十年中，经导管主动脉瓣植入术（TAVI）的需求不断增加，导致许多医疗系统中的等待时间延长，健康结果不理想。基于风险的优先级划分和等待时间基准可以改善患者的公平就医机会。
我们使用模拟模型对50000名从转诊到完成TAVI的合成人群进行随访。根据不良事件风险，患者可分为“低风险”“中风险”和“高风险”，并为高风险组分配较短的等待时间。我们评估了每个风险组的规模和等待时间对等待名单死亡率、住院率和紧急TAVI的影响。所有情景都有相同的资源限制，使我们能够探索优先患者更快就医与非优先群体延迟就医之间的权衡。增加高风险患者的比例，并为高风险组提供更快的就医机会，可使死亡率、住院率和紧急TAVI的降低幅度最大（相对降低幅度分别高达29%、23%和38%）。然而，这是以非优先低风险组等待时间过长（长达25周）为代价的。我们建议高风险患者等待时间最长为3周，中风险患者为7周。
优先考虑高风险患者并使其更快就医可带来更好的健康结果，但在能力有限的情况下，这也会导致非优先群体等待时间过长，令人无法接受。决策者在制定和实施等待名单优先级策略时必须意识到这些影响。
