The Subjective Causal Impact of COVID-19 on Graduate Medical Education and Recommendations for Bridging the Educational Gap: A Global Cross-sectional Study

doi:10.21203/rs.3.rs-3001293/v1

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The Subjective Causal Impact of COVID-19 on Graduate Medical Education and Recommendations for Bridging the Educational Gap: A Global Cross-sectional Study

https://doi.org/10.21203/rs.3.rs-3001293/v1

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Background: COVID-19 generated a system-wide shock causing an unbalanced equilibrium be- tween producing adequately trained physicians and meeting extraordinary operational needs. Pre- vious studies report the experience of surgical residents during COVID-19 on a regional level. This study measures the learning losses causally associated with the re-deployment of highly special- ized medical professionals to the care of COVID-19 patients, while we systematically investigate proposed remedial strategies.

Methods: We administered an online cross-sectional survey in 67 countries capturing training inputs (i.e., surgeries and seminars residents participated in) before and during the pandemic and retrieved residents’ expected learning outputs, career prospects and recommended remedial mea- sures for learning losses. We compared responses of residents working in (treatment group) and out (control group) of hospitals with COVID-19 patients.

Results: The analysis included 432 plastic surgery residents who were in training during the pandemic. Most of the learning losses were found in COVID-19 hospitals with 37% and 16% loss of surgeries and seminars, respectively, per week. Moreover, 74%, 44%, and 55% of residents ex- pected their surgical skill, scientific knowledge, and overall competence, respectively, to be lower than those of residents who graduated prior to COVID. Residents in COVID-19 hospitals reported participating in significantly (p < 0.001) fewer surgeries and having significantly (p < 0.001) lower surgical skill relative to those not in COVID-19 hospitals.

Conclusions: The perceived lower competence and the fall-off in surgical skill and scientific knowl- edge among future surgeons suggest that healthcare systems globally may have limited capacity to perform delicate and costly procedures in the future.

COVID-19

Graduate Medical Education

Plastic Surgery

Learning Losses

Sub- jective Causal Inference

Our results from an international survey of 432 plastic surgery residents illustrate the signifi- cant negative impact of COVID-19, as a system-wide shock, on graduate medical education.
The learning losses among surgery residents suggest that healthcare systems globally might have limited capacity to perform delicate and costly procedures in the future.
Residents report planning to pursue further clinical training to mitigate their learning losses.

The resident-recommended reform policies are consistent with a Competency-Based Time- Variant Graduate Medical Education (CB-TV GME) model.
Our subjective causal inference strategy serves as a blueprint for other contexts where ad- ministrative or experimental data are limited.

By May 15^th, 2022, 1 million people have lost their lives in the US alone since the COVID- 19 pandemic started [1]. The public health emergency created operational pressure on healthcare systems around the world, re-set care provision priorities, and derailed Graduate Medical Education (GME) [2, 3]. Early studies documented the changes in resident training during the pandemic [4, 5, 6, 7]. Residents’ training, in surgical specialties in particular, has been severely held back by the pandemic [8, 9, 10, 11, 12, 13, 14]. Previous studies, although informative, may not depict the learning losses causally associated with the re-deployment of hospital resources and highly specialized medical professionals to the care of COVID-19 patients. We conduct the first global study on the causal impact of the COVID-19 pandemic on residents of a highly specialized surgical specialty: plastic, reconstructive, and aesthetic surgery.

We focus on plastic surgery residents for a number of reasons. First, the learning losses of plastic surgery residents due to the COVID-19 disruptions may be comparable to those of residents in other surgical specialties. Training inputs and core competences such as procedural skills and medical knowledge are similar across specialties (Table 1) [15]. For example, the Accreditation Council for Graduate Medical Education (ACGME) expects residents, regardless their specialty, to obtain competency in six core competencies.

Second, plastic surgeons contribute to patient care well beyond aesthetic or reconstructive con- sultation [16, 17]. Similar to other physicians, plastic surgeons play an integral role in healthcare systems as their input is often crucial in treatment design and generates a substantial economic impact [18]. By targeting a single specialty we achieve a homogeneous sample of respondents, al- lowing us to infer the COVID-related learning losses of residents with comparable baseline medical background and comparable training expectations and professional aspirations.

So far, the experiences of plastic surgery residents during the pandemic have been investigated non-causally and only at a regional level [19, 20, 21, 22, 23, 24, 25]. Policy-makers and medical education leaders around the world rely on comparisons with national and international standards to advocate for policy and curriculum reforms. Single-country studies feature a more homogeneous sampled population allowing for a high degree of internal validity but are limited in the insights they can provide to non-studied populations (i.e., limited external validity) [26, 27].

Our study is the first to mobilize national and international resident networks in so many countries to understand the consequences of COVID-19 for graduate medical education under a unified research methodology that gets as close as possible to causality. For example, our methodology adjusts for reported pre-pandemic levels of training inputs and provides a control

group of residents, which none of the previous studies features. This allows the fair comparison of the impact of COVID-19 on training inputs and outputs across countries. To the best of our knowledge, this is the first international study to evaluate residents’ perceptions on changes in learning inputs and expected outputs during the pandemic.

Our methodology implements a causal inference framework to identify the component of train- ing disruption associated with re-deployment of resources and personnel to the care of COVID-19 patients. The objective is to account for contemporaneous training disruptions in healthcare sys- tems that did not treat COVID-19 patients.

2.1 Subjective Causal Identification Strategy

Our 37-question survey was conducted automatically through an online link in English between January 10^th and February 6^th, 2022. The timing of our survey captured roughly two years of pandemic experience. Given that prior pandemics lasted 1-2 years, our study provides a holistic view of the impact of COVID-19 on graduate medical education [28]. We recruited the help of the International Society for Aesthetic Plastic Surgery (ISAPS) to reach plastic surgery residents around the world. ISAPS is the leading professional body for board-certified plastic surgeons with a network of residents in over 100 countries. To our knowledge, no societies in other specialties with comparable network currently exist. The survey was disseminated by 63 associations of plastic surgeons, including ISAPS, to their resident members via email and social media. The survey questions and the dissemination strategy are provided in the Supplementary Information Appendix. This project was approved by the Institutional Review Board (IRB) at Stanford University.

2.2 Study Design

The survey design follows a causal inference framework. Recovering the impact of COVID-19 at the resident level entails comparison of the resident’s outcomes in two alternate states of the world: with the pandemic and without. With standard data on realizations, a given resident is observed in only one state of the world (in our case, COVID-19=1 ). The alternate outcomes are counter- factual and unobserved. A large econometric and statistics literature studies the identification of counterfactual outcomes from realized data [29, 30].

We follow Aucejo et al. in directly asking individuals for their expected outcomes with and

without COVID-19 [31]. From the collected data, we directly calculate the resident-level subjective treatment effect. Our approach builds on a growing literature that uses subjective expectations to understand decision-making under uncertainty [32, 33, 34, 35]. The soundness of our approach relies on the key assumption that residents have well-formed expectations for outcomes in both the realized and the counterfactual state.

Plastic surgery residents who did not work in hospitals that treated COVID-19 patients serve as the control group for residents in hospitals with COVID-19 patients. We consider two groups of COVID-impacted residents: (1) residents in hospitals with COVID-19 patients who did not work in COVID-19 wards and (2) residents in hospitals with COVID-19 patients who worked in COVID-19 wards.

2.3 Outcomes

Our study has two primary sets of outcomes: the training inputs and the expected training outputs. Inputs include surgeries residents participated or scrubbed in, seminar or lectures attended, and independent study. Outputs include surgical skill, scientific knowledge, overall competence, and future professional prospects.

Residents reported the number of surgeries and seminars per week or month before and during the pandemic. We calculate the percentage change before and during the pandemic. Residents also reported the magnitude of change in their study time before and during the pandemic. We create a score variable that takes the values -1, -0.5, 0, 0.5, and 1 for the responses decreased significantly, decreasedslightly, didnotchange, increasedslightly, and increasedsignificantly, respectively. We also create a binary variable that takes the value 1
when the response was decreased slightly or decreased significantly. Another binary variable captures the responses increased slightly and increasedsignificantly.

We asked residents whether the impact of the pandemic on their surgical skill and scientific knowledge has been significantly negative, slightly negative, zero, slightly positive, or significantly positive. We also asked residents whether they expect, in the absence of any remedial measures, the pandemic would make them significantlyless, slightlyless, equally, slightlymore, or significantly more competent compared with residents who did not face the pandemic during their residency.

For the outputs of surgical skill, scientific knowledge, and overall competence, we construct three variables. The first is a score variable that assigns the values -1, -0.5, 0, 0.5, and 1 for the responses significantly less/negative, slightly less/negative, no impact, slightly more/positive, and significantly more/positive impact, respectively. The second variable is binary and takes the value one when the respondent replied slightly or significantly less/negative impact. The third variable is also binary and takes the value one when the respondent replied slightly or significantly more/positive impact. Respondents who reported slightly or significantly lower competence were asked whether they anticipate an impact on their professional future and development. We create a binary variable that takes the value one when the participant replied probably or definitely yes. We also asked residents who reported lower competence than plastic surgeons before them the reasons that contributed to their responses. We create a binary variable for each of the reasons provided for reported lower overall competence. Those variables allow us to causally attribute reported lower competence to pandemic-related and non-pandemic-related justifications.

2.4 Statistical Analysis

Our main analytic strategy is a simple-differences model that compares changes in learning inputs and expected outputs before and during the pandemic of residents in hospitals with COVID- 19 patients and those in hospitals without (specification (1) in the Supplementary Information Appendix). This approach filters out pandemic-related influences on residents across all hospitals. For instance, some plastic surgery procedures may have been postponed across all hospitals during the pandemic, regardless of whether they treated COVID-19 cases [36].

We use multivariate regression models for continuous outcomes. For binary outcomes, we use multivariate linear probability models. All models include adjustments for gender, whether the resident has dependents, and the different levels of training program quality.¹ We directly asked respondents whether they believe that their training program prepares competent plastic surgeons.² All analyses use heteroskedasticity-robust standard errors. Our analysis relies on the assumption that had the pandemic not occurred, the learning inputs and outputs of residents in hospitals that treated COVID-19 patients would have been comparable to those of residents in hospitals that did not treat COVID-19 patients.

The association between changes in learning inputs and expected learning outputs during the pandemic was also investigated. We implemented models with pairwise interaction terms between indicators for whether residents worked in COVID hospitals/wards and changes of learning inputs during the pandemic (specification (2) in the Supplementary Information Appendix). We use linear models for ease of interpretation of interaction terms, as is standard practice in differences analyses [37].

¹Table S3 presents estimates when we do not control for reported training program quality.

²This question is intended to infer program quality regardless of the pandemic.

The Supplementary Information Appendix offers several heterogeneity analyses on the differen- tial impact of the pandemic on residents in hospitals with COVID-19 patients by year of training, quality of training program, hospital type, gender, whether the resident has dependents, whether the resident has prior experience in plastic surgery, and number of surgeries and seminars prior to the pandemic.

3.1 Demographics and Training Settings

The overall sample included 432 respondents from 67 countries (Table 1). The response rate could not be calculated because the number of plastic surgery residents who were in training during the pandemic was unknown and the methods of distribution precluded calculation of the respondent denominator. Table 1 presents summary statistics of characteristics of participants and their training settings. Ninety percent of respondents worked in a hospital that treated COVID-19 patients, while 50% of those were asked to work in a COVID-19 ward. Males represent 62% of respondents. The majority (61%) of respondents are non-Hispanic white. The average age is 32 years. Roughly one third (31%) of respondents have dependents. Roughly 17% of respondents are international medical school graduates. Sixty-three percent have prior general surgery experience of up to 2 years, while approximately 42% of residents have plastic surgery training prior to their residency. The average program duration is 4.8 years. Our sampled residents are roughly equally distributed in PGY 1 through 5+.

Regarding hospital type, 58% of respondents work in university hospitals. The Chi-square tests of independence show that university hospitals were more likely to treat COVID-19 patients. At the same time, plastic surgery residents working in community, tertiary, or military hospitals are significantly more likely to be re-deployed in the care of COVID-19 patients than their colleagues in university or private hospitals.

We find that roughly 61% of participants are satisfied with the quality of their training program. Chi-square tests reveal attending programs with lower satisfaction ratings is significantly associated with greater likelihood of being re-assigned in COVID-19 wards.

3.2 Learning Inputs

The top panel of Table 2 reports the impact of COVID-19 on residents’ learning inputs. We find a 37% (P < 0.01) and a 16% (P < 0.05) decrease in surgeries and seminars, respectively, across all respondents. Residents who worked in hospitals with COVID-19 patients but not in COVID wards and those who worked in COVID-19 wards report a percentage decrease (increase) in surgeries (seminars) of 43% (33%) and 41% (23%), respectively, compared with the control group. Only the differences in surgeries participated in were statistically significant (P < 0.05). The control group of residents who worked in hospitals that did not treat COVID-19 patients report a 2% increase in the number of surgeries they participated/scrubbed in and a 39% decrease in the number of seminars attended. Hospitals treating COVID-19 patients during the pandemic might have re-directed necessary personnel for operations, such as nursing staff, to the care of COVID-19 patients. As a result, their capacity to perform surgical procedures during the pandemic may have been limited relative to hospitals that did not receive COVID-19 patients.

Changes in independent study time during the pandemic seem to be insubstantial across the entire sample. Among control group residents in hospitals without COVID-19 patients, a slightly higher percentage report less study time than the percentage reporting increased study time during the pandemic, suggesting decreased study efforts on average. We find that residents in hospitals with COVID-19 patients, regardless of having worked in COVID wards, are more likely to report increased study efforts compared with the control group, but the estimates are imprecise.

3.3 Learning Outputs

The middle panel of Table 2 presents the estimated impact of the pandemic on training inputs and on expected outputs, when adjusting for pandemic shocks across all hospitals, regardless of whether they treated COVID-19 patients. We find that 74% and 44% of all participants reported significantly lower surgical skill and scientific knowledge, respectively (P < 0.01). More than half of all residents (55%) report having a lower overall competence compared with residents who completed their training before the pandemic (P < 0.01).

We find that residents in hospitals with COVID-19 patients are roughly 25-34% more likely to report having lower surgical skill due to the pandemic (P < 0.01). We do not find significant differences in the likelihood to report lower scientific knowledge or overall lower competence by residents in hospitals with COVID-19 patients compared with residents in hospitals without.

Two thirds (67%) of participants anticipate their self-reported lower overall competence due to the pandemic to negatively impact their future professional prospects (P < 0.01). We do not find

the impact on future professional prospects to significantly differ between residents in and out of hospitals that treated COVID-19 patients.

3.4 Country-level Results

We estimate the changes in learning inputs and outputs associated with attending a training program in a hospital that treats COVID-19 patients during the pandemic in each country. Our control group comprises of residents in hospitals that did not treat COVID-19 patients during the pandemic. Table S5 provides detailed country-level estimates. Figure 1 summarizes key patterns in the estimated impact of COVID-19 on residents in COVID-19 hospitals in each country relative to the control group. We focus on countries with at least five residents in COVID-19 wards or five residents who were not asked to work in COVID-19 wards.

We find substantially wide variation in the impact of COVID-19 on resident training across the world.³ Residents who were asked to work in COVID-19 wards report severe learning losses in both surgical skill and scientific knowledge in a number of countries such as Egypt, Germany, Greece, Italy, Romania, and Turkey. Residents who were not asked to work in COVID-19 wards seem to be rather shielded from the learning losses, while such residents in a number of countries such as Russia, South Korea, Taiwan, and the US report learning gains during the pandemic.

3.5 Origins of Learning Losses

The bottom panel of Table 2 shows the reported reasons associated with residents’ learning losses during the pandemic. The most frequently cited justification for lower overall competence is the decreased number of surgeries residents participated in (85%, P<0.01), followed by the decreased number of seminars or lectures residents attended (60%, P < 0.01).

We find that no resident attributes his/her learning losses to justifications unrelated to the pandemic.

We also investigate what drives expectations of learning losses. A learning input is found to drive an expected output if its estimated effect is statistically significant at α = 0.05. Panels A, B, and C of Figure 2 show to what extent the changes in surgeries, seminars, or studying influence expectations of lower surgical skill, lower scientific knowledge, and lower overall competence, respectively, of residents who worked in COVID-19 hospitals in and out of COVID-19 wards. The association between learning inputs and outputs of residents in hospitals without COVID-19 pa- tients serve as benchmark. Panel A of Figure 2 suggests that the expectation of lower surgical skill is driven only by the change in the number of surgeries participated in, especially among residents in COVID hospitals who did not work in COVID wards. Panel B shows that the expectation of lower scientific knowledge is driven primarily by the change in study time. Changes in the num- ber of surgeries also explains the expectation of lower scientific knowledge among residents who worked in COVID hospitals but not in COVID wards. The expectation of lower overall competence among residents in COVID hospitals but not in COVID wards is driven by changes in all learn- ing inputs (Panel C). No learning input is found to explain the expectation of lower competence among residents who worked in COVID wards. This finding suggests that their expectation of lower competence may represent expressed emotion.

3.6 Countermeasures of Learning Losses

Table 3 shows the countermeasures planned or recommended by respondents. Our results show that 65% and 25% of residents plan on pursuing a fellowship or an extension of residency, respectively. These percentages are substantially higher than pre-pandemic trends suggested [39]. Overall, 94% of residents plan to pursue more hands-on surgical training to counter the crisis-driven learning deficits. Less than half percent of respondents have no individual plans to mitigate their learning losses. In terms of policy measures recommended, roughly 70% and 35% of respondents propose intensive training on surgical skills or lectures on targeted topics, respectively. More than one third and more than one quarter of participants recommended interim assessments during residency and log book requirements for board exam eligibility, respectively. Both of those recommendations are consistent with the competency-based, time-variable GME model. More than 98% of respondents call for policy measures, suggesting the need for system-level actions to counter learning losses.

³Figures S3-S6 in the Supplementary Information Appendix investigate the association between country-level changes in surgeries attended, seminars, and study effort with system-wide indices of preparednessand response to the COVID-19 crisis obtained from Schiller et al (2021) [38]. We find greater declines in learning inputs (i.e., surgeries, seminars) and greater increases in independent study effort in countries with low healthcare system preparedness and high levels of system response to COVID-19. Our associations are mostly statistically imprecise.

The method we use to identify the impact of COVID-19 on training inputs and outputs can benefit any framework in which competing priorities exist between operational needs and investment in training, such as GME programs. A benefit of using subjective measures of learning outputs is that they constitute a leading indicator of training quality, program satisfaction and trainee fatigue, and may closely predict subsequent individual success and system resilience.

We cannot afford for the COVID crisis to go to waste. The pandemic has been an external system shock, similar to which others might appear in the future. On one hand, the American Board of Medical Specialties (ABMS) and the ACGME have recognized the challenges in time and volume based GMEs the COVID crisis revealed and the need for reforms [40]. On the other hand, a competency-based and time-variable (CB-TV) approach has been successfully introduced and refined GME programs in many countries (e.g., the UK, the Netherlands, Canada), presenting the paradigm shift in the education of the next generation of physicians [41, 42]. Our findings serve as a reference point, underscoring residents’ needs and readiness to transition to CB-TV GME to galvanize healthcare systems against future crises [43, 44, 45, 46, 47, 48].

Our results provide a key metric of the fall-off in global healthcare systems’ future capacity to meet their needs in delicate and costly procedures, potentially widening access gaps in health care, under the current GME structure. CB-TV GME will allow healthcare systems to successfully produce qualified medical professionals and adequately shield themselves against future crises.

4.1 Limitations

Our study has some inherent limitations. Our laser focus on plastic surgery trainees constrains the statistical power of our analyses. However, our objective was to collect the views of residents with comparable training inputs and outputs from different nations. The inclusion of only plastic surgery residents serves that purpose, decreasing interviariabilty and creating a more homogeneous sample. In order to collect a global sample of respondents and gather the views of a global audience of plastic surgery residents, we reached out to as many societies of plastic surgery as we could. The main objective was to reach plastic surgery societies that had a teaching national footprint and gathered the attention of plastic surgery residents. In our extensive dissemination strategy we included 67 national and international societies of plastic surgery. We find that 19 out of the 67 societies are specifically focused on aesthetic surgery. The remaining societies do not differentiate between aesthetic surgery and target the whole spectrum of plastic, reconstructive and aesthetic surgery. In 12 out of the 19 aesthetic surgery societies, no counterpart association of non-aesthetic surgery societies existed in the country. In the remaining 7 cases, were both an aesthetic and a non-aesthetic surgery society existed, we were able to reach both and disseminate the survey to their resident members. For example, we reached both the British Association of Aesthetic Plastic Surgeons (BAAPS) and the United Kingdom Association of Aesthetic Plastic Surgeons (UKAAPS) to achieve better coverage in our survey. Further studies can harness future networks of residents across multiple specialties to obtain more responses, however they run the risk of creating a wildly heterogeneous sample of respondents.

Our self-reported measures of learning inputs and expected outputs from residents in 67 coun- tries may suffer from recall and expectation bias and may reflect residents’ perceptions in a single point in time. Future research could use administrative data to measure training inputs and out- puts and obtain more accurate estimates of the COVID impact. Also, training characteristics represented in the sample reflect primarily the training in core plastic surgery programs and may not capture the training in rotating subspecialties.

The pandemic has affected some regions of the world more than others and at different times. Our convenience non-random sample of participants from 67 countries from all five continents represent a broad geographic distribution of resident experiences during the pandemic. COVID-19 cases were in decline globally during data collection and procedures were expected to resume [49]. Additional waves of COVID-19 cannot be excluded though and continued restrictions on elective procedures are possible.

Our study is the first to causally identify the crisis-driven learning deficits of future surgeons, who will be expected to play a critical role in complex case treatment [18, 50], and investigate recommended remedial measures. We are confident that our study increases the evidence base to catalyze the reform in GME and provide salient reform recommendations and policy levers towards building resilient healthcare systems globally.

Our subjective causal inference strategy is general and can serve as a blueprint for other con- texts. Any setting in which observational administrative or experimental data are limited can profit from our approach to combine self-reported training inputs and outputs before and during a system-wide shock and a treatment-control group framework. A benefit of using subjective mea- sures of learning outputs is that they constitute a leading indicator of training quality, program satisfaction and trainee fatigue, and may closely predict subsequent individual success and system resilience.

Ethics approval

This study was approved by the Institutional Review Board at Stanford University (protocol #63918)

Data availability

Data and code are available for replication upon request.

Author contribution

G.K. conceptualized the survey, S.G. and G.K. designed the research; S.G. analyzed the data; and

S.G. and G.K. drafted the manuscript.

Funding

This work was made possible by the British Embassy in Athens, Greece and the State Scholarships Foundation. The publication of the article in OA mode was financially supported by HEAL-Link Greece.

Acknowledgements

The authors thank Dr. Vakis Kontoes and Dr. Maria Wiedner for mobilizing resources of the International Society of Aesthetic Plastic Surgery (ISAPS) to reach residents is 67 countries. The authors also thank the 63 national associations and societies of plastic surgeons who joined this international project and disseminated the online survey to their resident members. The authors also kindly acknowledge funding from the British Embassy in Athens, Greece and the State Schol- arships Foundation, and research support from the Institute for Social and Economic Research (ISER) at the University of Essex.

Conflict of Interest

None declared

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Tables 1 to 3 are available in the Supplementary Files section

No competing interests reported.

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The Subjective Causal Impact of COVID-19 on Graduate Medical Education and Recommendations for Bridging the Educational Gap: A Global Cross-sectional Study

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Abstract

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Key Messages

1. Introduction

2 Methods

2.1 Subjective Causal Identification Strategy

2.2 Study Design

2.3 Outcomes

2.4 Statistical Analysis

3 Results

3.1 Demographics and Training Settings

3.2 Learning Inputs

3.3 Learning Outputs

3.4 Country-level Results

3.5 Origins of Learning Losses

3.6 Countermeasures of Learning Losses

4 Discussion

4.1 Limitations

5 Conclusion

Declarations

References

Tables

Additional Declarations

Supplementary Files

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