Integrative Oncology Consultations Delivered via Telehealth in 2020 and In-Person in 2019: Paradigm Shift During the COVID-19 World Pandemic
Bibliographic record
Abstract
Background: The COVID-19 pandemic has catalyzed the use of mobile technologies to deliver health care. This new medical model has benefited integrative oncology (IO) consultations, where cancer patients are counseled about healthy lifestyle, non-pharmacological approaches for symptom management, and addressing questions around natural products and other integrative modalities. Here we report the feasibility of conducting IO physician consultations via telehealth in 2020 and compare patient characteristics to prior in-person consultations conducted in 2019. Methods: An integrated EHR-telemedicine platform was used for IO physician consultations. As in the prior in-person visits, patients completed pre-visit patient-reported outcome (PRO) assessments about common cancer symptoms [modified Edmonton Symptom Assessment Scale, (ESAS)], Measure Yourself Concerns and Wellbeing (MYCaW), and the PROMIS-10 to assess quality of life (QOL). Patient demographics, clinical characteristics, and PROs for new telehealth consultation in 2020 were compared to new in-person consultations in 2019 using t-tests, chi-squared tests, and -Wilcoxon rank-sum test. Results: We provided telehealth IO consultations to 509 new patients from April 21, 2020, to October 21, 2020, versus 842 new patients in-person during the same period in 2019. Most were female (77 % vs 73%); median age (56 vs 58), and the most frequent cancer type was breast (48% vs 39%). More patients were seeking counseling on herbs and supplements (12.9 vs 6.8%) and lifestyle (diet 22.7 vs 16.9% and exercise 5.2 vs 1.8%) in the 2020 cohort than 2019, respectively. The 2020 telehealth cohort had lower symptom management concerns compared to the 2019 in-person cohort (19.5 vs 33.1%). Conclusions: Delivering IO consultations using telehealth is feasible and meets patients’ needs. Compared to patients seen in-person during 2019, patients having telehealth IO consultations in 2020 reported lower symptom burden and more concerns about lifestyle and herbs and supplements. Additional research is warranted to explore the satisfaction and challenges among patients receiving telehealth IO care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".