Prescribing Phones to Address Health Equity Needs in the COVID-19 Era: The PHONE-CONNECT Program
Bibliographic record
Abstract
Vulnerable populations have been identified as having higher infection rates and poorer COVID-19-related outcomes, likely due to their inability to readily access primary care, follow public health directives, and adhere to self-isolation guidelines. As a response to the COVID-19 pandemic, many health care services have adopted new digital solutions, which rely on phone and internet connectivity. However, persons who are digitally inaccessible, such as those experiencing poverty or homelessness, are often unable to use these services. In response to this newly highlighted social disparity known as "digital health inequity," emergency physicians at the University Health Network in Toronto, Canada, initiated a program called PHONE-CONNECT (Phones for Healthier Ontarians iN EDs - COvid NEeds met by Cellular Telephone). This novel approach attempts to improve patients' access to health care, information, and social services, as well as improve their ability to adhere to public health directives (social isolation and contact tracing). Although similar programs addressing the same emerging issues have been recently described in the media, this is the first time phones have been provided as a health care intervention in an emergency department. This innovative emergency department point-of-care intervention may have a significant impact on improving health outcomes for vulnerable people during the COVID-19 pandemic and beyond.
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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 | 0.017 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".