RESUMO
Background COVID-19 has been the worst pandemic of this century, resulting in economic, social, and educational disruptions. Residency training is no exception, with training restrictions delaying the progression and graduation of residents. We sought to utilize simulation modelling to predict the impact on future cohorts in the event of repeated and prolonged movement restrictions due to COVID-19 and future pandemics of a similar nature. Method A Delphi study was conducted to determine key Accreditation Council for Graduate Medical Education-International (ACGME-I) training variables affected by COVID-19. Quantitative resident datasets on these variables were collated and analysed from 2018 to 2021. Using the Vensim® software (Ventana Systems, Inc., Harvard, MA), historical resident data and pandemic progression delays were used to create a novel simulation model to predict future progression delay. Various durations of delay were also programmed into the software to simulate restrictions of varying severity that would impact resident progression. Results Using the model with scenarios simulating varying pandemic length, we found that the estimated average delay for residents in each accredited year ranged from an increase of one month for year 2 residents to more than three months for year 4 residents. Movement restrictions lasting a year would require up to six years before the program returned to a pre-pandemic equilibrium. Conclusion Systems dynamic modelling can be used to predict delays in residency training programs during a pandemic. The impact on the workforce can thus be projected, allowing residency programs to institute mitigating measures to avoid progression delay.
RESUMO
Background Over the past decade, telemedicine has experienced significant growth due to technological advancement, and the coronavirus disease 2019 (COVID-19) pandemic further accelerated its adoption. However, the field of anesthesiology has been slow in integrating and embracing telemedicine compared to other medical specialties. Methods We conducted an observational pilot feasibility study at a tertiary hospital in Singapore to assess the viability of a telemedicine hybrid protocol for preoperative anesthetic assessment. The study included patients aged 21 to 65 years, classified as American Society of Anesthesiology (ASA) physical status class 1 or 2, with a body mass index (BMI) below 35 kg/m2, who were capable of managing video conferencing. The patients selected were scheduled for low-risk surgeries. The primary objective was to evaluate the medical and technical feasibility of our telemedicine hybrid protocol, while the secondary objectives included assessing patient satisfaction and obtaining feedback from relevant stakeholders. Results From November 2021 to April 2022, a total of 116 patients were recruited, with 96 patients completing the study. No technical difficulties, surgical case cancellations, or incidents of unanticipated difficult airways were reported. The majority of survey respondents (88%) expressed satisfaction with the video consultation and indicated a preference for it over physical consultations for future preoperative anesthesia evaluations. Conclusion Based on our findings, a telemedicine hybrid protocol for preoperative anesthetic assessment demonstrated both technical and medical feasibility while yielding high patient satisfaction. Future research could focus on expanding the protocol to encompass more complex surgeries and include patients with higher ASA status.
