Getting results for hematology patients through access to the electronic health record
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
PURPOSE: To conduct a needs assessment to identify patient and provider perceptions about providing patients with access to their electronic health record in order to develop an online system that is appropriate for all stakeholders. METHODS: Malignant hematology patients were surveyed and health care providers were interviewed to identify issues and validate concerns reported in the literature. Based on the analysed data, a prototype will be designed to examine the feasibility and efficacy of providing patients with access to their electronic health record and tailored information. RESULTS: 61% of patients reported using the internet to find health information; 89% were interested in accessing their electronic health record and 79% stated they would benefit from educational material along with the results. Staff members viewed patient online access to the record favourably, but expressed the importance of providing the necessary patient support and education. A Web-based prototype was developed for patients to review their registration data and blood results. CONCLUSIONS: Hematology oncology patients are more interested in using the internet to monitor their clinical information than to find health information. Using the constructed prototype, the feasibility of this project is currently being tested.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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