Purpose Improvement in the quality of life of patients with cancer requires attention to symptom burden across the continuum of care, with the use of patient-reported outcomes key to achieving optimal care. Yet there have been few studies that have examined symptoms in the early postdiagnosis period during which suboptimal symptom control may be common. A comprehensive analysis of temporal trends and risk factors for symptom burden in newly diagnosed patients with cancer is essential to guide supportive care strategies. Methods A retrospective observational study was performed of patients who were diagnosed with cancer between January 2007 and December 2014 and who survived at least 1 year. Patient-reported Edmonton Symptom Assessment System scores, which are prospectively collected at outpatient visits, were linked to provincial administrative health care data. We described the proportion of patients who reported moderate-to-severe symptom scores by month during the first year after diagnosis according to disease site. Multivariable logistic regression models were constructed to identify risk factors for moderate-to-severe symptom scores. Results Of 120,745 patients, 729,861 symptom assessments were recorded within 12 months of diagnosis. For most symptoms, odds of elevated scores were highest in the first month, whereas nausea had increased odds of elevated scores up to 6 months after diagnosis. On multivariable analysis, cancer site, younger age, higher comorbidity, female sex, lower income, and urban residence were associated with significantly higher odds of elevated symptom burden. Conclusion A high prevalence of moderate-to-severe symptom scores was observed in cancers of all sites. Patients are at risk of experiencing multiple symptoms in the immediate postdiagnosis period, which underscores the need to address supportive care requirements early in the cancer journey. Patient subgroups who are at higher risk of experiencing moderate-to-severe symptoms should be targeted for tailored supportive care interventions.

IMPORTANCE The coronavirus disease 2019 (COVID-19) pandemic has burdened health care resources and disrupted care of patients with cancer. Virtual care (VC) represents a potential solution. However, few quantitative data support its rapid implementation and positive associations with service capacity and quality. OBJECTIVE To examine the outcomes of a cancer center-wide virtual care program in response to the COVID-19 pandemic. DESIGN, SETTING, AND PARTICIPANTS This cohort study applied a hospitalwide agile service design to map gaps and develop a customized digital solution to enable at-scale VC across a publicly funded comprehensive cancer center. Data were collected from a high-volume cancer center in Ontario, Canada, from March 23 to May 22, 2020. MAIN OUTCOMES AND MEASURES Outcome measures were care delivery volumes, quality of care, patient and practitioner experiences, and cost savings to patients. RESULTS The VC solution was developed and launched 12 days after the declaration of the COVID-19 pandemic. A total of 22 085 VC visits (mean, 514 visits per day) were conducted, comprising 68.4% (range, 18.8%-100%) of daily visits compared with 0.8% before launch (P < .001). Ambulatory clinic volumes recovered a month after deployment (3714-4091 patients per week), whereas chemotherapy and radiotherapy caseloads (1943-2461 patients per week) remained stable throughout. No changes in institutional or provincial quality-of-care indexes were observed. A total of 3791 surveys (3507 patients and 284 practitioners) were completed; 2207 patients (82%) and 92 practitioners (72%) indicated overall satisfaction with VC. The direct cost of this initiative was CAD$ 202 537, and displacement-related cost savings to patients totaled CAD$ 3 155 946. CONCLUSIONS AND RELEVANCE These findings suggest that implementation of VC at scale at a high-volume cancer center may be feasible. An agile service design approach was able to preserve outpatient caseloads and maintain care quality, while rendering high patient and practitioner satisfaction. These findings may help guide the transformation of telemedicine in the post COVID-19 era.