DynIA: Dynamically Informed Allegories
Bibliographic record
Abstract
An important strategy for improving population health is to use what we learn from medical research in our patient care. One approach to this is using the highest quality medical research to make recommendations and guide healthcare providers in deciding how to diagnose and treat their patients. These recommendations form the basis of healthcare tools that are called clinical practice guidelines. Theme four focused on strategies for increasing the uptake of clinical practice guidelines on low back pain and headache into community-based care. Theme four researchers collaborated with guideline developers in Alberta at the Institute of Health Economics and an organization called Towards Optimize Practice (TOP) that is sponsored by the Alberta Medical Association and the Alberta Ministry of Health (Alberta Health and Wellness). The research team first looked at what is already been known about uptake of guideline recommendations for chronic pain. This process involved going back to original research from around the world. Research librarians and scientists found 19 scientific papers that are relevant. Taken together, these studies indicated that the best approach to improving uptake of chronic pain guidelines into community care is to present them to care providers in special interactive educational settings where they are able to discuss the recommendations approaches with the educators. Theme four then went on to test this approach in the study of using an interactive educational workshop focused on the low back pain guideline. The study was conducted in collaboration with researchers from the University of Calgary and the University of Alberta. The workshop presenters were an expert team of physicians, physiotherapists, nurses and psychologists that traveled to the offices of the community healthcare providers. This study showed that the providers’ knowledge of low back pain increased after the workshop. When the medical records were examined, the researchers were unable to detect changes in how care was provided. This was a small study involving 24 providers. The researchers concluded that a larger study may confirm the increase in provider knowledge and detect changes in care. An important advance in healthcare is the use of computerized medical records. Computerization also provides an opportunity for healthcare providers to access relevant health information during their time with the patient. Theme four researchers collaborated with the Department of Family Medicine that McMaster University to develop a tool to help community caregivers use the recommendations from clinical practice guidelines while they are in the office with patients. This tool called the McMaster Pain Assistant has undergone successful usability testing and is now being tested in the community to see if using the tool leads to increases in knowledge and decisions that reflect the guideline. Rural physicians face important challenges in accessing medical education. In the past they would have to leave their practices and travel to a distant site to learn. Theme four researchers collaborated with the Department of Continuing Medical Education at the University of Calgary to explore a distance learning approach using Internet-based webinars and “virtual patients” that are designed to teach about the guidelines and how it might affect their care. This preliminary study demonstrated that rural physicians appreciated being able to access high quality medical education where they can interact with experts without having to travel. They found the sessions and the virtual patients highly engaging and realistic. Only small changes were shown in management of the virtual patients through the case series. Detailed analysis of practice patterns showed participants to be very conformant with clinical practice guideline recommendations.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.076 | 0.013 |
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".