The effects of a regional telepathology project: a study protocol
Bibliographic record
Abstract
BACKGROUND: Telepathology, which is an emerging form of telemedicine in Canada, is defined as the electronic transmission of pathological images, usually derived from microscopes, from one location to another. There are various applications of telepathology, including case referral for an expert opinion, provision of an emergency service in the absence of a resident pathologist, and education. Until now, there has been relatively little use of telepathology for core diagnostic services in the absence of a local pathologist, but this practice is likely to increase in the future. The Laval University Integrated Health Network is in the process of deploying a telepathology system, primarily to provide an intraoperative frozen section service to small hospitals in sparsely populated areas which are experiencing a severe shortage of on-site pathologists. The telepathology project involves 17 hospitals located in five regions of eastern Quebec, Canada. This paper describes the study protocol that will be used to evaluate the benefits associated with the project. METHODS/DESIGN: A panel of experts was first assembled by Canada Health Infoway to agree on a set of benefits indicators that could be applied to all telepathology projects across Canada. Using the set of indicators as an input, we have developed a three-step study protocol. First, a survey questionnaire will be distributed to appraise the way pathologists, pathology technologists and surgeons perceive the telepathology system and its impacts. Second, a series of semi-structured interviews will be conducted with project leaders and telepathology users at sites that are representative of all the hospitals in the Laval University Integrated Health Network. The overall aim is to better understand the expected and unexpected effects of telepathology on health care professionals and patients as well as on the regional organization and delivery of care services. Finally, a pre-post design using secondary data is proposed to evaluate a wide array of tangible benefits to the patients, the health care providers, the hospitals, and the region as a whole. DISCUSSION: The Laval University Integrated Health Network's telepathology project is expected to yield positive and significant results that are relevant internationally. Our findings will provide valuable information on the nature and extent of benefits associated with telepathology systems intended to provide an intraoperative frozen section service to remote hospitals experiencing a shortage of specialists.
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How this classification was reachedexpand
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".