<i>MyHealthPortal</i> – A web-based e-Healthcare web portal for out-of-hospital patient care
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Current e-Health portal platforms provide support for patients only if they have previously registered and received service from a healthcare facility (e.g., hospital, healthcare clinic, etc.). These portals are usually connected to a central EMR/EHR system linked to a central system. Furthermore, these portals are restrictive in that they are only accessible by these patients at the exclusion of parents, relatives and others that participate in providing care to the patient. Further complications include the increasing demand from our healthcare systems for patients to receive more off-site, non-primary, in-homecare, and/or specialized healthcare services at home (e.g., therapy, nursing, personal support, etc.). Lastly, an increasing number of people would like to have more autonomy over their health in terms of increased access to their own medical records and the services they receive. In this work, we addressed these limitations by creating MyHealthPortal – a patient portal aimed at non-primary care, in-homecare, and/or special healthcare for patients. MyHealthPortal can assist homecare and clinic-based healthcare services along with the benefits of existing portals (e.g., online appointment scheduling, monitoring, and information sharing). MyHealthPortal is secure, robust, flexible and user-friendly. We developed it in partnership with our industry partner, Closing the Gap Healthcare. Closing the Gap is a prominent homecare and clinic-based healthcare service provider that became the first homecare agency to score 100% on standards from accreditation Canada and was awarded the exemplary standing. In this paper we present MyHealthPortal, the architectural framework that we designed and developed to support the system, and the results of a usability study conducted from real field studies. Our system was tested in a variety of conditions and achieved SUS usability scores of 92.5% (high).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it