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1.
Curr Oncol ; 28(6): 5332-5345, 2021 12 13.
Article in English | MEDLINE | ID: covidwho-1572387

ABSTRACT

Virtual cancer care (i.e., teleoncology) was rapidly adopted during the COVID-19 pandemic to meet the needs of patients with cancer. However, there is a paucity of guidance for clinicians regarding virtual cancer care. We sought to develop consensus-based statements to guide the optimal provision of virtual care for clinicians caring for patients with cancer, using a modified Delphi consensus process with a 29-member panel consisting of an interprofessional group of clinicians caring for patients with cancer and patient representatives. The consensus process consisted of two rounds and one synchronous final consensus meeting. At the end of the modified Delphi process, 62 of 62 statements achieved consensus. Fifty-seven statements reached consensus in the first round of the process. Concerns regarding the ability to convey difficult news virtually and maintaining similar standards as in-person care without disproportionate strain on clinicians and patients were addressed in the consensus process. We achieved interprofessional consensus on virtual cancer care practices. Further research examining the impact of virtual cancer care on person-centred and clinical outcomes are needed to inform practices during the COVID-19 pandemic and beyond.


Subject(s)
COVID-19 , Pandemics , Consensus , Delphi Technique , Humans , SARS-CoV-2
2.
J Patient Exp ; 8: 23743735211039328, 2021.
Article in English | MEDLINE | ID: covidwho-1394400

ABSTRACT

During the COVID-19 pandemic, most cancer centers shifted from in-person to virtual cancer care to curb community spread and ensure care continuity. This qualitative descriptive study aimed to understand cancer patient-perceived risks related to COVID-19 and cancer treatment, as well as the patient-perceived and experienced value of virtual care. From June to August 2020, focus groups were conducted with patients under active management or observation for a diagnosed malignancy in Toronto, Canada. A thematic analysis of six focus groups found that most participants worried more about treatment delays than they did about COVID-19 infection. Despite some concern about COVID-19 exposure in the hospital, care delays contributed to increased anxiety among participants who already subscribed to strict safety measures in their everyday lives. Most participants accepted virtual care for some appointment types; however, preference for in-person care was found to sustain the humanistic and therapeutic aspects of cancer care that many participants valued. Nuances in the appropriateness and adequacy of virtual cancer care still need exploration. Preserving the humanistic aspects of care is of paramount importance.

3.
Health Expect ; 24(3): 978-990, 2021 06.
Article in English | MEDLINE | ID: covidwho-1153493

ABSTRACT

BACKGROUND: Waiting for procedures delayed by COVID-19 may cause anxiety and related adverse consequences. OBJECTIVE: To synthesize research on the mental health impact of waiting and patient-centred mitigation strategies that could be applied in the COVID-19 context. METHODS: Using a scoping review approach, we searched 9 databases for studies on waiting lists and mental health and reported study characteristics, impacts and intervention attributes and outcomes. RESULTS: We included 51 studies that focussed on organ transplant (60.8%), surgery (21.6%) or cancer management (13.7%). Most patients and caregivers reported anxiety, depression and poor quality of life, which deteriorated with increasing wait time. The impact of waiting on mental health was greater among women and new immigrants, and those of younger age, lower socio-economic status, or with less-positive coping ability. Six studies evaluated educational strategies to develop coping skills: 2 reduced depression (2 did not), 1 reduced anxiety (2 did not) and 2 improved quality of life (2 did not). In contrast, patients desired acknowledgement of concerns, peer support, and periodic communication about wait-list position, prioritization criteria and anticipated procedure date. CONCLUSIONS: Findings revealed patient-centred strategies to alleviate the mental health impact of waiting for procedures. Ongoing research should explore how to optimize the impact of those strategies for diverse patients and caregivers, particularly in the COVID-19 context. PATIENT OR PUBLIC CONTRIBUTION: Six patients and four caregivers waiting for COVID-19-delayed procedures helped to establish eligibility criteria, plan data extraction and review a draft and final report.


Subject(s)
COVID-19/psychology , Caregivers/psychology , Pandemics , Patient-Centered Care , Waiting Lists , COVID-19/epidemiology , Female , Humans , Mental Health , Quality of Life , SARS-CoV-2
4.
CMAJ ; 193(2): E63-E73, 2021 01 11.
Article in French | MEDLINE | ID: covidwho-1110107

ABSTRACT

CONTEXTE: Pour limiter la propagation de la maladie à coronavirus 2019 (COVID-19), de nombreux pays ont décidé de réduire le nombre d'interventions chirurgicales non urgentes, ce qui a créé des retards en chirurgie partout dans le monde. Notre objectif était d'évaluer l'ampleur du retard pour ce type d'interventions en Ontario, au Canada, ainsi que le temps et les ressources nécessaires pour y remédier. MÉTHODES: Nous avons consulté 6 bases de données administratives décrivant la population ontarienne et canadienne pour dégager la distribution du volume chirurgical et de la cadence des salles d'opération pour chaque type d'interventions et chaque région, et connaître la durée d'occupation d'un lit d'hôpital et d'un lit de soins intensifs. Les données utilisées concernent l'ensemble ou une partie de la période du 1er janvier 2017 au 13 juin 2020. Nous avons estimé l'ampleur du retard accumulé et prédit le temps nécessaire pour le reprendre dans un scénario avec capacité d'appoint de + 10 % (ajout d'un jour à 50 % de la capacité par semaine) à l'aide de modèles de séries chronologiques, de modèles de files d'attente et d'une analyse de sensibilité probabiliste. RÉSULTATS: Entre le 15 mars et le 13 juin 2020, le retard en chirurgie à l'échelle de l'Ontario s'est accru de 148 364 opérations (intervalle de prévision à 95 % 124 508­174 589) au total, et en moyenne de 11 413 opérations par semaine. Pour reprendre le retard accumulé, il faudra environ 84 semaines (intervalle de confiance [IC] à 95 % 46­145) et une cadence hebdomadaire de 717 patients (IC à 95 % 326­1367), qui elle demande 719 heures passées au bloc opératoire (IC à 95 % 431­1038), 265 lits d'hôpital (IC à 95 % 87­678) et 9 lits de soins intensifs (IC à 95 % 4­20) par semaine. INTERPRÉTATION: L'ampleur du retard en chirurgie dû à la COVID-19 laisse entrevoir de graves conséquences pour la phase de reprise en Ontario. Le cadre qui nous a servi à modéliser la reprise du retard peut être adapté ailleurs, avec des données locales, pour faciliter la planification.

5.
Canadian Medical Association. Journal ; 192(44):E1347-E1356, 2020.
Article in English | ProQuest Central | ID: covidwho-911399

ABSTRACT

BACKGROUND: To mitigate the effects of coronavirus disease 2019 (COVID-19), jurisdictions worldwide ramped down nonemergent surgeries, creating a global surgical backlog. We sought to estimate the size of the nonemergent surgical backlog during COVID-19 in Ontario, Canada, and the time and resources required to clear the backlog. METHODS: We used 6 Ontario or Canadian population administrative sources to obtain data covering part or all of the period between Jan. 1, 2017, and June 13, 2020, on historical volumes and operating room throughput distributions by surgery type and region, and lengths of stay in ward and intensive care unit (ICU) beds. We used time series forecasting, queuing models and probabilistic sensitivity analysis to estimate the size of the backlog and clearance time for a +10% (+1 day per week at 50% capacity) surge scenario. RESULTS: Between Mar. 15 and June 13, 2020, the estimated backlog in Ontario was 148364 surgeries (95% prediction interval 124 508-174 589), an average weekly increase of 11413 surgeries. Estimated backlog clearance time is 84 weeks (95% confidence interval [CI] 46-145), with an estimated weekly throughput of 717 patients (95% CI 326-1367) requiring 719 operating room hours (95% CI 431-1038), 265 ward beds (95% CI 87-678) and 9 ICU beds (95% CI 4-20) per week. INTERPRETATION: The magnitude of the surgical backlog from COVID-19 raises serious implications for the recovery phase in Ontario. Our framework for modelling surgical backlog recovery can be adapted to other jurisdictions, using local data to assist with planning.

6.
CMAJ ; 192(44): E1347-E1356, 2020 11 02.
Article in English | MEDLINE | ID: covidwho-740406

ABSTRACT

BACKGROUND: To mitigate the effects of coronavirus disease 2019 (COVID-19), jurisdictions worldwide ramped down nonemergent surgeries, creating a global surgical backlog. We sought to estimate the size of the nonemergent surgical backlog during COVID-19 in Ontario, Canada, and the time and resources required to clear the backlog. METHODS: We used 6 Ontario or Canadian population administrative sources to obtain data covering part or all of the period between Jan. 1, 2017, and June 13, 2020, on historical volumes and operating room throughput distributions by surgery type and region, and lengths of stay in ward and intensive care unit (ICU) beds. We used time series forecasting, queuing models and probabilistic sensitivity analysis to estimate the size of the backlog and clearance time for a +10% (+1 day per week at 50% capacity) surge scenario. RESULTS: Between Mar. 15 and June 13, 2020, the estimated backlog in Ontario was 148 364 surgeries (95% prediction interval 124 508-174 589), an average weekly increase of 11 413 surgeries. Estimated backlog clearance time is 84 weeks (95% confidence interval [CI] 46-145), with an estimated weekly throughput of 717 patients (95% CI 326-1367) requiring 719 operating room hours (95% CI 431-1038), 265 ward beds (95% CI 87-678) and 9 ICU beds (95% CI 4-20) per week. INTERPRETATION: The magnitude of the surgical backlog from COVID-19 raises serious implications for the recovery phase in Ontario. Our framework for modelling surgical backlog recovery can be adapted to other jurisdictions, using local data to assist with planning.


Subject(s)
Cardiac Surgical Procedures/statistics & numerical data , Coronavirus Infections , Neoplasms/surgery , Organ Transplantation/statistics & numerical data , Pandemics , Pneumonia, Viral , Vascular Surgical Procedures/statistics & numerical data , Betacoronavirus , COVID-19 , Elective Surgical Procedures/statistics & numerical data , Forecasting , Hospital Bed Capacity/statistics & numerical data , Humans , Intensive Care Units/supply & distribution , Length of Stay/statistics & numerical data , Models, Statistical , Ontario , Operating Rooms/supply & distribution , Pediatrics/statistics & numerical data , SARS-CoV-2 , Time Factors
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