Evolution of the surgical procedure gap during and after the COVID-19 pandemic in Ontario, Canada: cross-sectional and modelling study

Dear Editor During the COVID-19 pandemic, many countries faced significant reductions in surgical capacity1, leading to unprecedented surgical backlogs or ‘procedure gaps’2. The aim of the present study was to develop a framework to estimate procedure gaps and project their future evolution. The framework was applied to data from Ontario, Canada to provide policy insights for fair and effective surgical recovery. The present study updates previous work that estimated the impacts of COVID-19 on surgery rates3 and future surgical recovery4 by providing a more recent estimate and adding modelling of major ongoing COVID-19 impacts. In reality, COVID-19 and its downstream effects have continued to impact healthcare systems into 2023 and can be reasonably expected to continue into the future. Population-based weekly surgery count data were obtained for all scheduled adult surgical procedures in Ontario between 1 January 2017 and 25 June 2022, grouped by inpatient/outpatient and body system. Negative binomial regression was used to estimate the expected sizes of the procedure gaps as of 25 June 2022 and Monte Carlo simulation was used to estimate their evolution over 10 years under future COVID-19 and surgical capacity-increase scenarios (Fig. S1). See Supplementary Methods for detailed methods. As of 25 June 2022, the total outpatient and inpatient procedure gaps were estimated to be 214 925 (95 per cent c.i. 207 281 to 222 569) and 99 232 (95 per cent c.i. 96 856 to 101 609) respectively (Table 1). Assuming no future impacts of COVID-19 and a 10 or 20 per cent increase in surgical capacity, all procedure gaps were estimated to clear within 10 years. However, under scenarios in which COVID-19 impacts persist, with a 0 or 10 per cent increase in surgical capacity, no procedure gaps were expected to clear within 10 years. With a 20 per cent increase, only three procedure gaps were expected to clear; several other gaps were expected to grow. See Supplementary Results and Supplementary Figures and Tables for additional results and overview. Expected procedure gaps as of 25 June 2022 and evolution of the procedure gaps over the 10-year horizon starting from 26 June 2022 Values are mean(s.d.) unless otherwise indicated. Scenario columns report on the estimated evolution of procedure gaps using the following convention. The first row of each cell indicates the time to clear the procedure gap. Procedure gaps that do not clear in 10 years are indicated by ‘>10’. The second row of each cell indicates the size of the procedure gap at 10 years, included if the gap does not clear in 10 years. *Procedure gaps that clear within 10 years. †Procedure gaps that do not clear in 10 years and where the expected procedure gap at the end of 10 years is larger than at the start (25 June 2022). ‡Procedure gaps that do not clear in 10 years and where the expected procedure gap at the end of 10 years is smaller than at the start. Expected procedure gaps as of 25 June 2022 and evolution of the procedure gaps over the 10-year horizon starting from 26 June 2022 Values are mean(s.d.) unless otherwise indicated. Scenario columns report on the estimated evolution of procedure gaps using the following convention. The first row of each cell indicates the time to clear the procedure gap. Procedure gaps that do not clear in 10 years are indicated by ‘>10’. The second row of each cell indicates the size of the procedure gap at 10 years, included if the gap does not clear in 10 years. *Procedure gaps that clear within 10 years. †Procedure gaps that do not clear in 10 years and where the expected procedure gap at the end of 10 years is larger than at the start (25 June 2022). ‡Procedure gaps that do not clear in 10 years and where the expected procedure gap at the end of 10 years is smaller than at the start. The results of the present study highlight the heterogeneous impact of the pandemic on different procedure groups. These differences are apparent in the growth of procedure gaps over the pandemic (Fig. S4) and in their forecasted evolution. For example, the two largest outpatient procedure gaps (eye and musculoskeletal), which were the subject of pre-pandemic prioritization through added capacity and volume-based funding models, make up almost half of the total outpatient procedure gap. However, even if COVID-19 impacts persist, their forecasted gaps are expected to drop significantly with a 10 per cent increase in surgical capacity (Table 1). In contrast, the estimated inpatient gynaecology gap is currently much smaller, but, even with a 20 per cent increase in capacity, the gap is expected to more than double by 2032 (Table 1). On 2 February 2023, the Ontario government released a plan to significantly increase cataract surgeries and hip and knee replacements5 through the use of for-profit centres, but without a clear plan to increase overall surgical capacity in hospitals. The results of the present study suggest that other procedure groups (for example gynaecology and otolaryngology) require targeted increases in surgical capacity, especially if those groups are predominantly funded through global hospital budgets. To avoid unfair patient experiences, such as extensive wait times, targeted investments considering both the current procedure gaps and their future evolution are necessary for surgical recovery plans that strike a balance between efficiency and equity of clearing the procedure gaps. The present study has two key takeaways. First, small increases in overall surgical capacity will have little impact on clearing the surgical procedure gap in the near term. Second, capacity increases should be targeted by considering not only current procedure gaps but also their forecasted evolution. Indeed, procedure groups with the largest gaps currently may not be the ones most in need of increased capacity investments. The developed framework can be applied to other jurisdictions to provide insights for the design of robust surgical recovery plans. The present study was supported by a Canadian Institutes of Health Research (CIHR) operating grant (202109- 477229) and the Ontario Health Data Platform (OHDP). D.G. and T.C.Y.C. are co-senior authors. All authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Rachel Stephenson (Conceptualization, Formal analysis, Methodology, Software, Visualization, Writing—original draft, Writing—review & editing), Vahid Sarhangian (Conceptualization, Methodology, Writing—original draft, Writing—review & editing), Jangwon Park (Conceptualization, Formal analysis, Methodology, Software, Writing—original draft, Writing—review & editing), Ashwin Sankar (Funding acquisition, Writing—review & editing), Nancy N. Baxter (Writing—review & editing), Therese A. Stukel (Writing—review & editing), Andrea N. Simpson (Writing—review & editing), Duminda N. Wijeysundera (Writing—review & editing), Andrew S. Wilton (Data curation, Software), Charles de Mestral (Writing—review & editing), Stephen W. Hwang (Writing—review & editing), Daniel Pincus (Writing—review & editing), Robert Campbell (Writing—review & editing), David R. Urbach (Writing—review & editing), Jonathan Irish (Writing—review & editing), David Gomez (Conceptualization, Funding acquisition, Writing—review & editing), and Timothy C. Y. Chan (Conceptualization, Funding acquisition, Methodology, Writing—review & editing). The authors declare no conflict of interest. Supplementary material is available at BJS online. General information (research ethics, disclaimer, and data statements), as well as extended background and discussion are included in Supplementary Appendices. The data set from the present study is held securely in coded form at ICES. While data sharing agreements prohibit ICES from making the data set publicly available, access may be granted to those who meet pre-specified criteria for confidential access (see www.ices.on.ca/DAS). The full data-set creation plan and the underlying analytic code are available from the authors upon request; please note that the programs may rely upon coding templates or macros that are unique to ICES.

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