Survey of Telemedicine by Pediatric Nephrologists During the COVID-19 Pandemic
Bibliographic record
Abstract
INTRODUCTION: The slow increase in use of telemedicine began to expand rapidly, along with reimbursement changes, during the coronavirus disease-2019 (COVID-19) pandemic. Standardized protocols for these services are lacking but are needed for effective and equitable health care. In this study, we queried pediatric nephrologists and their patients about their telemedicine experiences during the pandemic. METHODS: Surveys that were in compliance with the Health Insurance Portability and Accountability Act were deployed online to patients and physicians. RESULTS: We collected survey responses from 400 patients and 197 pediatric nephrologists. Patients reported positive experiences with telemedicine visits as it was logistically easier than in-person visits. Patients also felt that the quality of their visits were equivalent to what they would receive in person. Physicians used a wide variety of online systems to conduct synchronous telemedicine with Zoom (23%), EPIC (9%), Doxy.me (7%), services not specified (37%), or a mix of local or smaller services (24%). Most physicians' concerns were related to technological issues and the ability to procure physical exams and/or laboratory results. CONCLUSIONS: There is a paucity of published trials on telemedicine services in pediatric nephrology. Virtual care was feasible and acceptable for patients, caregivers, and providers during the COVID-19 pandemic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".