PURPOSE: COVID-19 pandemic has impacted healthcare services worldwide. As a strategy to increase capacity during the pandemic, hospitals cancelled elective and non-urgent surgery. This resulted in many patients waiting for operations and an ever-increasing backlog of elective surgery. Delays in delivering healthcare services is likely to increase patient morbidity, mortality and associated health care costs. Evidence-based policy decisions regarding backlog management require forecasting and optimization models. These models should consider hospital and national perspectives. Several optimization outcomes can be considered, including backlog size, mortality, quality of life (QOL) and costs. For evidence-based policies, these capacity optimization models should be informed by data such as backlog size, capacity, as well as the impact of interventions on capacity and outcomes in terms of life expectancy, QOL and costs.

This workshop aims to propose a best practice guideline for modelling backlogs considering relevant optimization perspectives, optimization outcomes and relevant inputs needed for evidence-based backlog/capacity models to inform hospital and national policy interventions. It should inform local and national policymakers on minimal future data requirements and models needed to optimize population health from a hospital and health care perspective during and post-COVID-19.

DESCRIPTION: First 10 minutes: Project’s background and methodology. Discussion on existing policy frameworks at hospital and national levels relating to backlog management

Second 10 minutes: Evaluate the evidence on backlog size (caused by COVID-19) and its impact in terms of life years lost or quality-adjusted life years.

Next 10 minutes: Presentation of existing models that optimize backlog reduction and policy strategies, according to different parameters of optimization.

Next 20 minutes: Propose a best practice guideline for backlog modelling that focuses on how to best manage the backlog and the data needed to achieve population health outcomes, and discuss the relevance guideline across health systems.

Final 10 minutes: Q&A