Future of Teleoncology: Trends and Disparities in Telehealth and Secure Message Utilization in the COVID-19 Era

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Abstract

PURPOSE

The COVID-19 pandemic created an imperative to re-examine the role of telehealth in oncology. We studied trends and disparities in utilization of telehealth (video and telephone visits) and secure messaging (SM; ie, e-mail via portal/app), before and during the pandemic.

METHODS

Retrospective cohort study of hematology/oncology patient visits (telephone/video/office) and SM between January 1, 2019, and September 30, 2020, at Kaiser Permanente Northern California.

RESULTS

Among 334,666 visits and 1,161,239 SM, monthly average office visits decreased from 10,562 prepandemic to 1,769 during pandemic, telephone visits increased from 5,114 to 8,663, and video visits increased from 40 to 4,666. Monthly average SM increased from 50,788 to 64,315 since the pandemic began. Video visits were a significantly higher fraction of all visits ( P < .01) in (1) younger patients (Generation Z 48%, Millennials 46%; Generation X 40%; Baby Boomers 34.4%; Silent Generation 24.5%); (2) patients with commercial insurance (39%) compared with Medicaid (32.7%) or Medicare (28.1%); (3) English speakers (33.7%) compared with those requiring an interpreter (24.5%); (4) patients who are Asian (35%) and non-Hispanic White (33.7%) compared with Black (30.1%) and Hispanic White (27.5%); (5) married/domestic partner patients (35%) compared with single/divorced/widowed (29.9%); (6) Charlson comorbidity index ≤ 3 (36.2%) compared with > 3 (31.3%); and (7) males (34.6%) compared with females (32.3%). Similar statistically significant SM utilization patterns were also seen.

CONCLUSION

In the pandemic era, hematology/oncology telehealth and SM use rapidly increased in a manner that is feasible and sustained. Possible disparities existed in video visit and SM use by age, insurance plan, language, race, ethnicity, marital status, comorbidities, and sex.

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Most cited references 41

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A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation

Mary Charlson, Peter Pompei, Kathy Ales … (1987)

The objective of this study was to develop a prospectively applicable method for classifying comorbid conditions which might alter the risk of mortality for use in longitudinal studies. A weighted index that takes into account the number and the seriousness of comorbid disease was developed in a cohort of 559 medical patients. The 1-yr mortality rates for the different scores were: "0", 12% (181); "1-2", 26% (225); "3-4", 52% (71); and "greater than or equal to 5", 85% (82). The index was tested for its ability to predict risk of death from comorbid disease in the second cohort of 685 patients during a 10-yr follow-up. The percent of patients who died of comorbid disease for the different scores were: "0", 8% (588); "1", 25% (54); "2", 48% (25); "greater than or equal to 3", 59% (18). With each increased level of the comorbidity index, there were stepwise increases in the cumulative mortality attributable to comorbid disease (log rank chi 2 = 165; p less than 0.0001). In this longer follow-up, age was also a predictor of mortality (p less than 0.001). The new index performed similarly to a previous system devised by Kaplan and Feinstein. The method of classifying comorbidity provides a simple, readily applicable and valid method of estimating risk of death from comorbid disease for use in longitudinal studies. Further work in larger populations is still required to refine the approach because the number of patients with any given condition in this study was relatively small.

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Risk factors for severe and critically ill COVID‐19 patients: a review

Ya-dong Gao, Mei Ding, Xiang Dong … (2020)

The pandemic of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused an unprecedented global social and economic impact, and high numbers of deaths. Many risk factors have been identified in the progression of COVID-19 into a severe and critical stage, including old age, male gender, underlying comorbidities such as hypertension, diabetes, obesity, chronic lung diseases, heart, liver and kidney diseases, tumors, clinically apparent immunodeficiencies, local immunodeficiencies, such as early type I interferon secretion capacity, and pregnancy. Possible complications include acute kidney injury, coagulation disorders, thoromboembolism. The development of lymphopenia and eosinopenia are laboratory indicators of COVID-19. Laboratory parameters to monitor disease progression include lactate dehydrogenase, procalcitonin, high-sensitivity C-reactive protein, proinflammatory cytokines such as interleukin (IL)-6, IL-1β, Krebs von den Lungen-6 (KL-6), and ferritin. The development of a cytokine storm and extensive chest computed tomography imaging patterns are indicators of a severe disease. In addition, socioeconomic status, diet, lifestyle, geographical differences, ethnicity, exposed viral load, day of initiation of treatment, and quality of health care have been reported to influence individual outcomes. In this review, we highlight the scientific evidence on the risk factors of severity of COVID-19.