A Comparison of Two Personal Health Portals: British Columbia's Health Gateway and China's Healthcare Cloud
Bibliographic record
Abstract
Increasingly, countries internationally have begun offering citizens access to their health information through personal health portals (PHP). A PHP aims to empower users with secure access to their health data to facilitate proactively managing and controlling their health. The content contained in health portals varies, but many provide users with their laboratory results, medical records, prescription medications, and other information depending on each portal’s specific purpose. The COVID-19 pandemic created an additional use for these portals – to allow citizens to see their COVID-19 test results and vaccination status. British Columbia offers a PHP called Health Gateway (HG) and China offers one named Healthcare Cloud (HC). The usability of PHPs is increasingly crucial as more people use them. This study compared the usability of HG and HC through testing selected COVID-19 related tasks. Both PHPs would benefit from including visuals to represent health records and increase health documentation such as tutorials to assist users in completing tasks. This study revealed usability issues that could be improved in future designs PHPs. However, people that use PHPs vary, and PHPs need to be tailored and enhanced accordingly.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".