The power of knowledge: Sharing patient test results electronically to improve quality of care.
Bibliographic record
Abstract
305 Background: For many patients going through the cancer diagnosis journey, the time from suspicion to diagnosis or rule-out can be a confusing and anxious time. To better support patients during this time, Cancer Care Ontario (CCO) is supporting Diagnostic Assessment Programs (DAPs) and the web-based tool known as the Diagnostic Assessment Program–Electronic Pathway Solution (DAP-EPS). DAPs consist of multi-disciplinary healthcare teams who provide diagnostic and supportive care services in a patient-focused environment, improving access to care and the patient experience. DAPs help manage and coordinate a patient’s diagnostic care from testing to a definitive diagnosis and part of this support involves providing access to personal health information through the DAP-EPS. This work was undertaken to determine the best approach to sharing test results with patients, including the type of test results that should be released and the most effective method for sharing these results with patients, from both the patient and provider perspective. Methods: The exploratory project involved conducting key informant interviews with individuals who had been involved with implementing similar patient portals, a targeted literature review, and a series of engagement sessions with physicians to measure the clinical response to this new strategy. Results: Initial discussions with patients and nurses yielded a strong endorsement for releasing all results, with no time delay. Key Informant interviews yielded similar results from the majority of the hospital contacts consulted. The environmental scan did not suggest that releasing results was associated with any adverse patient or provider effects. The physician engagement sessions generated both positive and negative feedback but overall, doctors were comfortable releasing all results, provided there was a delay built into the system. Conclusions: The release of diagnostic test results is seen as a valuable component of quality of care from the perspective of informing and empowering the patient. As the DAP-EPS moves forward with this initiative, the DAP program will continue to monitor the impact that the release of results has on both patients and providers.
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.
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 | 0.022 | 0.078 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".