AbstractObjective

: To assess the volume of deferred ophthalmic surgeries in Ontario, Canada associated with the coronavirus disease 2019 (COVID-19) pandemic from March-December 2020 and suggest strategies and duration required to clear the backlog.

Design

: Cross-sectional study.

Participants

: Ontarians eligible for the Ontario Health Insurance Plan in 2017-2020.

Methods

: Backlog and clearance time for ophthalmic surgeries associated with the COVID-19 pandemic were estimated from time series forecasting models and the queuing theory.

Results

: From March 16 to December 31, 2020, the estimated ophthalmic surgical backlog needing operating rooms (OR) was 92,150 surgeries (95% prediction interval [PI] 71,288–112,841). Roughly 90% of the delayed surgeries were cataract surgeries and a concerning 4% were retinal detachment surgeries. Nearly half of the provincial backlog (48%, 44,542/92,150) was in patients from the West health region. In addition, an estimated 23,755 (95% PI 14,656–32,497) anti-VEGF (vascular endothelial growth factor) injections were missed. Estimated provincial clearance time was 248 weeks (95% confidence interval [CI] 235–260) and 128 weeks (95% CI 121–134) if 10% and 20% of OR surgical capacity per week were added, respectively, based on the weekly ophthalmic surgical volume in 2019.

Conclusions

: Ontario data demonstrates that the magnitude of ophthalmic surgical backlog in 2020 alone raises serious concerns for meeting the ophthalmic surgical needs of patients. As the pandemic continues the accrued backlog size is likely increasing. Planning and actions are needed urgently to better manage the collateral impacts of the pandemic on the ophthalmic surgical backlog.

Keywords

In response to the COVID-19 (coronavirus disease of 2019) pandemic,1 worldwide jurisdictions intermittently stopped or ramped down nonemergent surgeries,2-4 creating a global surgical backlog of unknown size. This unknown information limits the ability to develop strategies to effectively address the backlog.

In Ontario, Canada, the Ministry of Health directed hospitals/clinics to begin a measured “ramping down of elective surgeries and other nonemergent clinical activity” on March 15, 2020.2 In less than three months this directive resulted in 148,364 deferred surgeries, including cancer, cardiac, transplant, pediatric, vascular and other (including ophthalmic) surgeries.5 The directive was lifted on May 26, 2020.6 Since then hospital/clinic services in Ontario have gradually increased, but have not returned to full capacity due to the ongoing pandemic, patient hesitancy and new protocols to limit the impact of COVID-19.

In 2020, Wang et al. estimated it will take 84 weeks to clear the backlog accrued in the first three months of the pandemic in Ontario, under the scenario of 717 weekly surgeries with 719 operating room (OR) hours, 265 hospital ward beds and 9 intensive care unit (ICU) beds available per week.5 As ophthalmic surgeries are mostly day surgeries, clearing the ophthalmic surgical backlog is not constrained by available hospital and ICU beds. The estimated clearance time by Wang et al. thus does not apply to ophthalmic surgeries, the most common adult surgery.5

With global COVID-19 vaccination efforts,7-9 the impact of the pandemic will hopefully lessen. To assist with better comprehension of the magnitude of ophthalmic surgical backlog and development of an evidence-based recovery plan, we analyzed population-based data to assess the volume of deferred ophthalmic surgeries associated with COVID-19 in March-December 2020 and suggest strategies and duration required to clear the backlog in Ontario.

Methods

In Canada, medically necessary services are universally covered for all residents by publicly funded health insurance plans administered at the provincial level. In Ontario, the largest province in Canada by population (over 14.7 million in 2020, 39.2% of Canada's population),10 ophthalmologists submit claims to Ontario Health Insurance Plan (OHIP) for payment of insured services.

Ophthalmic surgeries were arranged into nine subgroups using fee codes:11 retinal detachment (RD), intravitreal anti-VEGF (vascular endothelial growth factor) (code E147), retina (other than RD and anti-VEGF), glaucoma, cataract, strabismus, pterygium, cornea (other than pterygium) and other. Surgeries for RD, retina, glaucoma, cataract, strabismus and cornea typically require the use of OR. These subgroups were analyzed separately and combined into one group – ophthalmic OR surgeries. Anti-VEGF injections and pterygium surgery typically are done in clinics and were analyzed individually. We also analyzed data on ophthalmologists’ clinical visits and consults to assess the volumes of delayed non-surgical services. We considered five health regions (Toronto, Central, North, West and East) in Ontario (Figure 1) to examine geographical backlog distribution.12,13

Figure 1Five health regions in Ontario in 2020.

Data sources

We analyzed three population-based databases housed at ICES: OHIP physician billing database, ICES Physician Database (IPDB) and Registered Persons Database (RPDB). The OHIP database provided physician services related information (e.g., surgery type, surgery date). The IPDB database furnished physician related information (e.g., physician specialty). The RPDB database contained demographics information (e.g., age, sex, location of residence) for OHIP-insured Ontarians. Database linkages were done using encrypted health card numbers in a protected environment by ICES analysts. Aggregated data were provided for analyses. This study was approved by the Research Ethics Board at the University of Toronto (# 39901).

Estimating the backlog size

We estimated the backlog size as the difference between the expected and observed number of surgeries from March 16 to December 31, 2020 on a weekly basis. This backlog is the result of ramping down surgical services from the initial Ministry of Health announcement on March 15th to gradual reopening on May 26, 2020, up to December 31, 2020.2,6

The observed number of surgeries was the number of surgeries billed to OHIP by ophthalmologists. The expected number of surgeries was the number of surgeries expected to be performed by ophthalmologists as obtained from time series forecasting models considering historical patterns and seasonal variations.14,15

Estimating the clearance time

The clearance time was estimated as the backlog size divided by the weekly surgical volume that would be added, an adaptation of Little's Law from queuing theory16 and used in prior publications.5 According to the Little's Law, the average number of customers L in a queuing system is equal to the average arrival rate λ multiplied by the average time W that a customer spends in the system, i.e. L = λW.5,16 Through algebraic manipulations, we can easily get W = L/λ. In our case, W is the average time spent waiting for surgery (clearance time), L is the surgical backlog (waiting in the queue), λ is the weekly surgical volume being added.5,16 The weekly surgical volumes that would be added were estimated in two steps. First, we obtained the average weekly number of ophthalmic OR surgeries in 2019 (e.g., 3,177 for cataract surgeries). We then divided the weekly number by the conventional 40 working hours per week to estimate the number of surgeries per hour in Ontario (e.g. 3,177/40=79 cataract surgeries per hour). Second, the product of hourly number of surgeries and additional operating hours added per week (assuming status quo weekly volumes, i.e. no additional backlog) was used to calculate the clearance time. The added weekly additional operating hours divided by the conventional 40 weekly working hours was the percentage of increased surgical capacity, e.g. adding 4 additional hours per surgical week/40 hours per week=10% increased surgical capacity.

Clearance time was estimated using various recovery scenarios between two extremes: 10% and 70% increase in weekly surgical time. The 10% increase being equivalent to adding half a day in the scenario of 8 hours in a day and 5 surgical days in a week; 70% increase being equivalent to adding 8 operating hours on Saturday plus prolonging Monday to Friday from an 8-hour operating day to a 12-hour operating day. These two extremes represent potential additional surgical hours from a conservative to an aggressive approach. Clearance time in various scenarios between these two extremes were calculated. No clearance time was estimated for anti-VEGF injection as anti-VEGF injections are typically administered at a specific frequency. A missed injection would not result in an extra injection to catchup but rather a resumption of the injection frequency.

Statistical analysis

Time series models were used to forecast the expected number of surgeries with data divided into three subsets: training set, validation set and forecasting set. The training set included data from January 2, 2017 to March 11, 2019 (115 weeks), aiming to identify the weekly patterns of ophthalmic surgeries. The validation set included data from March 18, 2019 to March 9, 2020 (52 weeks), aiming to use the external dataset to recognize which of several forecasting models performed best. The forecasting set included data from March 16, 2020 to December 31, 2020 (42 weeks), aiming to obtain the observed and the expected number of surgeries for the pandemic period. Ophthalmic surgical volumes in Ontario displayed a clear seasonal variation (higher volumes in April and September and lower volumes in August and December in 2019, Figure 2). We used the following models to take into account the effects of seasonal variations to improve the model performance in forecasting: seasonal naïve model, seasonal and trend decomposition using locally estimated scatterplot smoothing, dynamic harmonic regression with trigonometric terms for seasonality, and TBATS state space models.14,15 Model selection was done using the root mean squared error during the validation period.15 Variability and uncertainty of the backlog estimation was dealt with the bootstrap technique with 1,000 trials. Uncertainty of the clearance time was taken into account with the Monte Carlo simulation with 1,000 trials at the provincial level and 10,000 trials at the regional level. All analyses were performed using SAS 9.4 (SAS Institute Inc.).

Figure 2Monthly volume of ophthalmic surgeries in Ontario from 2017 to 2020. *: Not including anti-VEGF (vascular endothelial growth factor) injections and other less common ophthalmic surgeries that require the use of operating rooms; ⁎⁎: Excluding retinal detachment surgeries and anti-VEGF injections; ⁎⁎⁎: Excluding pterygium surgeries.

Results

In 2018 and 2019, Ontario ophthalmologists provided 6.48 million and 6.60 million services, respectively. In 2020, services were reduced by 22% to 5.13 million. In 2019, 6.2% (411,823) of the services were procedures, including 203,567 ophthalmic OR surgeries, 205,945 anti-VEGF injections and 2,311 pterygium surgeries. In 2020, the number of OR surgeries was 149,146 (26.7% decrease versus 2019), and the number of anti-VEGF injections was 193,921 (5.8% decrease versus 2019). The weekly mean number of surgeries and standard deviation for Ontario and the five health regions in 2017-2020 is shown in Table 1.

Table 1The weekly mean number and standard deviation (in parenthesis) of ophthalmic surgeries in Ontario and health regions in 2017-2020

*: excluding anti-VEGF (vascular endothelial growth factor) and pterygium surgery.

**: anti-VEGF: anti-vascular endothelial growth factor.

Compared to the monthly volumes of surgeries in 2019, the number of surgeries in April 2020 was the lowest, reduced by 95% for ophthalmic OR surgeries, 66%-80% for emergent eye surgeries and nearly 100% for non-emergent eye surgeries (Figure 2). For anti-VEGF injections, the volume reduction in April 2020 was 42%. In November 2020, all types of ophthalmic surgical volumes increased (Figure 2). For anti-VEGF injection, the volume increased by 25% in November 2020.Results of the weekly time series forecast for ophthalmic OR surgeries are shown in Figure 3. Weekly time series forecasts for each surgery type can be found in Appendix A. Between March 16 and December 31, 2020, the incremental provincial backlog was 92,150 OR surgeries (95% prediction interval [PI] (71,288–112,841) (Table 2). By health region, the largest backlog was amongst patients in West (44,542) and the smallest was amongst patients in Toronto (4,132) (Table 2). Weekly accumulation of the provincial backlog is illustrated in Figure 4.

Figure 3Weekly volumes versus forecasts for all ophthalmic surgeries that require the use of operating rooms in Ontario from January 2017 to December 2020. Shaded area: 95% prediction interval. Anti-VEGF (vascular endothelial growth factor) injections and other less common ophthalmic surgeries that require the use of operating rooms were not included.

Table 2Estimated backlog size and 95% prediction interval of ophthalmic surgeries in Ontario and health regions in 2020

*: RD: Retinal detachment; anti-VEGF: anti-vascular endothelial growth factor.

⁎⁎: Not including other less common eye surgeries that require the use of operating rooms.

Figure 4Week-over-week accumulation of the mean provincial backlog for all ophthalmic surgeries that require the use of operating rooms from March to December 2020. Anti-VEGF (vascular endothelial growth factor) injections and other less common ophthalmic surgeries that require the use of operating rooms were not included.

By surgery type, the largest backlog was cataract surgery (Table 2 and Figure 5). This was followed by RD surgery. The smallest backlog was cornea surgery. The missed number of anti-VEGF injections was 23,755 (95% PI 14,656 –32,497) (Table 2).

Figure 5Percentage of delayed ophthalmic surgeries by surgery type. *: Excluding retinal detachment surgeries and anti-VEGF injections; ⁎⁎: Excluding pterygium surgeries.

In 2020, assessments and consults decreased by 27% (510,571 fewer assessments) and 28% (157,413 fewer consults) compared to 2019, which was 5.5 times and 1.7 times, respectively, greater than the delayed number of OR surgeries. In 2019, 21% of patient assessments had a diagnosis of glaucoma, 21% had cataract and 22% had a retinal diagnosis (Appendix B). The percentages of diagnostic groups in ophthalmologist consults were 17% for glaucoma, 20% for cataract and 15% for retina (Appendix B).

Figure 6 shows the estimated clearance time for the ophthalmic OR surgeries backlog. With a 10% increase in surgical time, it would take 248 weeks (4.8 years) to clear the provincial backlog. With a 70% increase in surgical time, it would require 36 weeks (0.7 years) to clear Ontario's 2020 backlog. Figure 6 also shows that increasing surgical capacity from 10% to 20% per week, the clearance time was shortened by 120 weeks (248 to 128). However, increasing from 60% to 70% only decreases the clearance time by 6 weeks (42 to 36). In the West region, the estimated clearance time exceeds the estimated provincial clearance time in every additional surgical capacity added per week (Figure 7).

Figure 6Estimated clearance time for total number of ophthalmic surgeries that require the use of operating rooms at the provincial level. Not including anti-VEGF (vascular endothelial growth factor) injections and other less common ophthalmic surgeries that require the use of operating rooms. A 10% increase in surgical capacity is equivalent to adding half a day (4 hours) in the scenario of 8 hours in a day and 5 surgical days in a week (4/(8 × 5)=10%). Shaded area: 95% confidence interval.

Figure 7Estimated clearance time for total number of ophthalmic surgeries that require the use of operating rooms by health region in Ontario. Not including anti-VEGF (vascular endothelial growth factor) injections and other less common ophthalmic surgeries that require the use of operating rooms. A 10% increase in surgical capacity is equivalent to adding half a day (4 hours) in the scenario of 8 hours in a day and 5 surgical days in a week (4/(8 × 5)=10%).

Discussion

This analysis estimated 92,150 ophthalmic OR surgeries were delayed in Ontario due to COVID-19 restrictions in March-December 2020 alone. Of these, the majority (90%) were cataract surgeries and a concerning 4% were RD surgeries. However, emergency surgeries were allowed throughout the pandemic suggesting possible delays in diagnosis due to issues with access to assessments or patient hesitancy as demonstrated in Figure 2 where RD surgeries were reduced by 66% in April 2020. The backlog was unevenly distributed across the province, with the largest being amongst patients in West region and the smallest in Toronto (Table 2). The estimated provincial clearance time was 248 and 128 weeks if additional 10% and 20% surgical capacity per surgical week were added, respectively. In addition, 23,755 anti-VEGF injections were missed. Missed anti-VEGF injections may lead to worsening or permanent vision loss.17 In comparison to the surgical backlog, 5.5 times more ophthalmologist assessments and 1.7 times more consults were missed. Some of these “missed” assessments would be the result of cancelled surgeries. Overall, the impact of the ophthalmology backlog is large, developing and implementing strategies to address this are required urgently to lessen the potential vision loss created by the reaction to the pandemic.

Reduced surgical services during the pandemic has been a ubiquitous phenomenon worldwide.5,18,19 Estimates on the scale of cancelled surgeries during the initial COVID-19 peak disruption have been published.5,18,19 However, ophthalmic surgeries are often grouped into “other” category.5,18 Recently, Felfeli et al predicted ophthalmic surgical backlog due to COVID-19 using the Ontario Wait Time Information System database and a microsimulation model.20 The authors reported that “By 2 years and 3 years since the start of the pandemic, the overall estimated number of patients awaiting surgery grew by 129% and 150%, respectively.” Due to differences in database used (Wait Time Information System database vs physician billing database) and time period studied (2-3 years versus 10 months following the pandemic declaration), it is difficult to compare their findings to this study. Aggarwal et al. forecasted the volume of cataract surgery in the US Medicare beneficiaries due to COVID-19 using linear regression model19 which ignores seasonal variations of ophthalmic surgeries. Compared with previous reports, our study not only focused on ophthalmic surgeries, but also assessed anti-VEGF injections, office assessments and new consults using population-based physician billing data and time series forecasting models.

Physicians and allied healthcare workers are indispensable in clearing the surgical backlog. Physicians including training physicians have endured long working hours before COVID-19 compared with the general population (weekly working hours 45-85 in practicing physicians and >50 in 87% of training physicians versus 40 in general population).21-25 Physicians also experienced higher burnout rates before COVID-19.26,27 The pandemic has heightened existing challenges that physicians face and increased physicians’ burnout.28-30 Adding additional operating hours is necessary to clear the backlog but may worsen existing burnout and other health issues in physicians and allied healthcare providers.

We propose three strategies to deal with the reported ophthalmic surgical backlog: 1) Maximizing current surgical capacity to help reduce the accrued backlog during the ongoing pandemic by carefully balancing patients’ needs, COVID-19 risk and healthcare providers’ wellness. 2) Programs specifically targeting cataract surgery, the main contributor to the surgical backlog, will provide the greatest impact to reduce the ophthalmic surgical backlog and associated impact on quality of life. 3) Retinal detachment is an emergency eye condition requiring timely surgical treatment to avoid permanent vision loss/blindness. Although emergency retinal detachment surgeries were allowed throughout the pandemic, the 4% retinal detachment surgical backlog suggests possible delays in diagnosis including access to assessments or patient hesitancy. Public education is needed to encourage patients to seek timely care for urgent medical conditions.

Study limitations include that the estimation of surgical backlog size and clearance time was focused on urgent and common ophthalmic surgeries only. This may result in an underestimation of the backlog size and clearance time for all ophthalmic surgeries. In dealing with massive backlog sizes, focusing on urgent and common surgeries is important. Second, our analysis included data up to December 2020 only and did not account for the backlog associated with COVID-19 in 2021 and beyond. Repeated shutdowns and re-opening and the surge in the Omicron variant further compound the backlog and call for an analysis with updated data. Third, due to backlogs upstream in primary care, obtaining a consultation and patient hesitancy, it is possible that actual wait lists for ophthalmic surgery may be less. Fourth, we did not have information on where the surgeries were done (e.g. Independent Health Facility (IHF), hospital etc). Future studies are needed to understand if the backlog was evenly distributed between IHFs and hospitals. Fifth, there is no differentiation between retinal re-detachment surgery vs. new detachment surgery. Finally, the regional analysis was based on patient residence. This should be considered in the event of regional allocation of additional resources.

In conclusion, using population-based, single-payer, real-world physician billing data and time series models, we estimated that 92,150 ophthalmic surgeries were delayed in Ontario due to COVID-19 in 2020 alone. Roughly 90% of the delayed surgeries were cataract surgeries and a concerning 4% were RD surgeries. The estimated provincial clearance time ranged from 248-36 weeks if additional surgical capacity of 10%-70% per week added. In addition, a much larger number of non-surgical visits were missed that may also result in worsening of patient outcomes. Health administrators and ophthalmologists must react and plan now to treat patients effectively and safely while balancing physicians’ wellness.

Funding

This work was supported by the Ontario's Ministry of Health for the COVID-19 Challenge Questions Initiative. The costs associated with preparing the data cut by ICES analysts for the study was provided by the Ministry of Health.

Declaration of Competing Interest non

Acknowledgement

This study contracted ICES Data & Analytic Services (DAS) and used de-identified data from the ICES Data Repository, which is managed by ICES with support from its funders and partners: Canada's Strategy for Patient-Oriented Research (SPOR), the Ontario SPOR Support Unit, the Canadian Institutes of Health Research and the Government of Ontario. The opinions, results and conclusions reported are those of the authors. No endorsement by ICES or any of its funders or partners is intended or should be inferred.

The authors thank Ms. Qi-Sheng Chen from the University of Waterloo, Canada, for preparation of Figure 1.

Authorship statement

Conceptualization: Yvonne M. Buys, Sherif El-Defrawy, Ya-Ping Jin

Data curation: Ya-Ping Jin, Yvonne M. Buys, Sherif El-Defrawy

Formal analysis: Mayilee Canizares, Ya-Ping Jin

Funding acquisition: Ya-Ping Jin, Yvonne M. Buys, Sherif El-Defrawy

Investigation: Ya-Ping Jin, Mayilee Canizares, Yvonne M. Buys, Sherif El-Defrawy

Methodology: Ya-Ping Jin, Mayilee Canizares, Yvonne M. Buys, Sherif El-Defrawy

Project administration: Ya-Ping Jin

Resources: Ya-Ping Jin, Yvonne M. Buys

Software: Mayilee Canizares, Ya-Ping Jin

Supervision: Yvonne M. Buys, Sherif El-Defrawy

Validation: Mayilee Canizares, Ya-Ping Jin

Visualization: Mayilee Canizares, Ya-Ping Jin

Roles/Writing - original draft: Ya-Ping Jin

Writing - review & editing: Ya-Ping Jin, Mayilee Canizares, Yvonne M. Buys, Sherif El-Defrawy

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Appendix. Supplementary materialsArticle InfoPublication History

Accepted: June 28, 2022

Received in revised form: February 22, 2022

Received: September 12, 2021

Publication stageIn Press Accepted ManuscriptIdentification

DOI: https://doi.org/10.1016/j.jcjo.2022.06.020

Copyright

© 2022 Canadian Ophthalmological Society. Published by Elsevier Inc. All rights reserved.

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