A tale of two patients – How did the pandemic impact patients’ usage of health portals
Bibliographic record
Abstract
Objective: The study examines whether patient health portal usage significantly increased during the COVID-19 pandemic between 2019 and 2022.Methods: In order to measure patient usage of patient portals before and during the first year of the COVID-19 pandemic, this study used the Health Information National Trends Survey results for 2019, 2020, 2021, and 2022. It was compared, using a least square regression model, to see if there was a significant relationship between increased use of telehealth, the usage of health portals, and the number of times seen by a regular healthcare provider.Results: The number of patients who saw their health care provider thrice a year and used their patient portal pre- and postpandemic increased. However, the overall increase in patients using their portals before and during the first two years of the pandemic remains below 50%.Conclusions: Overall, the pandemic increased patients’ use of telemedicine but only significantly increased their usage of patient portals for those patients who saw their provider three or more times a year. These findings indicate that more interaction with providers might impact future portal usage.
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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 | 0.000 |
| 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) | 0.000 | 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".