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Predicting the Ophthalmic Surgical Backlog as a Result of the COVID-19 Pandemic: A population-based study and microsimulation model to inform surgical recovery plans
Preprint
in English
| medRxiv
| ID: ppmedrxiv-21254375
ABSTRACT
BackgroundJurisdictions worldwide ramped down ophthalmic surgeries to mitigate the effects of coronavirus disease 2019 (COVID-19), creating a global surgical backlog. We sought to predict the long-term impact of COVID-19 on ophthalmology surgical care delivery. MethodsThis is a population-based and a microsimulation modelling study. Provincial administrative data from January 2019 to May 2021 was used to estimate the backlog size and wait-times following the COVID-19 pandemic. For the post-pandemic recovery phase, we estimated the resources required to clear the backlog of patients accumulated on the waitlist during the pandemic. ResultsA total of 56,923 patients were on the waitlist in the province of Ontario awaiting non-emergency ophthalmic surgery as of March 15, 2020. The number of non-emergency surgeries performed in the province decreased by 45-98% from March to May 2020, and 48-80% from April to May 2021 compared to the same months in 2019. By 2 years and 3 years, the overall estimated number of patients awaiting surgery grew by 129% and 150%, respectively. The estimated mean wait-time for patients for all subspecialty surgeries increased to 282 (SD 91) in March 2023 compared to 94 days (SD 97) in 2019. The provincial monthly additional resources required to clear the backlog by March 2023 was estimated to be a 34% escalation from the pre-pandemic volumes (4,626 additional surgeries). InterpretationThe magnitude of the ophthalmic surgical backlog from COVID-19 has important implications for the recovery phase. The estimates from this microsimulation modelling can be adapted to other jurisdictions to assist with recovery planning for vision saving surgeries.
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Full text:
Available
Collection:
Preprints
Database:
medRxiv
Type of study:
Prognostic study
Language:
English
Year:
2021
Document type:
Preprint