Abstract
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.
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More From: European heart journal. Quality of care & clinical outcomes
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