Towards a standardised method of patient prioritisation that accounts for clinical harm

Wathes, Rowan; Malhotra, Karina; Flott, Kelsey; Nath, Arup R.; Urch, Catherine

doi:10.7861/fhj.2020-0109

Cited by 6 publications

(1 citation statement)

References 5 publications

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“…A clinical priority system designed in New Zealand, prioritizing patients for valve surgery and coronary artery bypass graft by severity of symptoms, showed an 80% reduction in preprocedural deaths, 31 and a recently implemented prioritization framework for elective procedures in England has shown improvements in data quality and management of the waitlists. 32 Notwithstanding, only few studies have systematically assessed the effectiveness of prioritization tools thus far. 33 The CAN3T has the potential to improve patient outcomes, avoiding the occurrence of preventable preprocedural hospitalizations and deaths, and consequently improving system efficiency with fewer urgent procedures and shorter procedural length of stay.…”

Section: Discussionmentioning

confidence: 99%

Transcatheter Aortic Valve Implantation Wait‐Time Management: Derivation and Validation of the Canadian TAVI Triage Tool (CAN3T)

Miranda,

Qiu,

Manoragavan

et al. 2024

JAHA

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Background Transcatheter aortic valve implantation (TAVI) has seen indication expansion and thus exponential growth in demand over the past decade. In many jurisdictions, the growing demand has outpaced capacity, increasing wait times and preprocedural adverse events. In this study, we derived prediction models that estimate the risk of adverse events on the waitlist and developed a triage tool to identify patients who should be prioritized for TAVI. Methods and Results We included adult patients in Ontario, Canada referred for TAVI and followed up until one of the following events first occurred: death, TAVI procedure, removal from waitlist, or end of the observation period. We used subdistribution hazards models to find significant predictors for each of the following outcomes: (1) all‐cause death while on the waitlist; (2) all‐cause hospitalization while on the waitlist; (3) receipt of urgent TAVI; and (4) a composite outcome. The median predicted risk at 12 weeks was chosen as a threshold for a maximum acceptable risk while on the waitlist and incorporated in the triage tool to recommend individualized wait times. Of 13 128 patients, 586 died while on the waitlist, and 4343 had at least 1 hospitalization. A total of 6854 TAVIs were completed, of which 1135 were urgent procedures. We were able to create parsimonious models for each outcome that included clinically relevant predictors. Conclusions The Canadian TAVI Triage Tool (CAN3T) is a triage tool to assist clinicians in the prioritization of patients who should have timely access to TAVI. We anticipate that the CAN3T will be a valuable tool as it may improve equity in access to care, reduce preventable adverse events, and improve system efficiency.

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Section: Discussionmentioning

confidence: 99%

Transcatheter Aortic Valve Implantation Wait‐Time Management: Derivation and Validation of the Canadian TAVI Triage Tool (CAN3T)

Miranda,

Qiu,

Manoragavan

et al. 2024

JAHA

View full text Add to dashboard Cite

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A pragmatic digital health informatics based approach for aiding clinical prioritisation and reducing backlog of care: A study in cohort of 4022 people with diabetes

Karalliedde,

French,

Burnhill

et al. 2023

Diabetes Research and Clinical Practice

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Wait-times benchmarks for risk-based prioritization in transcatheter aortic valve implantation: a simulation study

Miranda,

Austin,

Fremes

et al. 2024

European Heart Journal - Quality of Care and Clinical Outcomes

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Background 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. Methods 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. Results 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. Conclusions 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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Towards a standardised method of patient prioritisation that accounts for clinical harm

Cited by 6 publications

References 5 publications

Transcatheter Aortic Valve Implantation Wait‐Time Management: Derivation and Validation of the Canadian TAVI Triage Tool (CAN3T)

Transcatheter Aortic Valve Implantation Wait‐Time Management: Derivation and Validation of the Canadian TAVI Triage Tool (CAN3T)

A pragmatic digital health informatics based approach for aiding clinical prioritisation and reducing backlog of care: A study in cohort of 4022 people with diabetes

Wait-times benchmarks for risk-based prioritization in transcatheter aortic valve implantation: a simulation study

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