Digitizing Medical History: French Validation of FirstHx Primary Care Tool: Research protocol
Bibliographic record
Abstract
Abstract Background Digital healthcare technology is experiencing a surge in popularity, being embraced both within clinical care and research. Adopting a digital system for medical history has the potential to enhance patient engagement in shared decision-making processes effectively bridging the gap between patients and healthcare providers. Centered on patient empowerment and improving the quality of care, our vision is to revolutionize the way healthcare providers gather and utilize patient information. FirstHx is currently collaborating and has toolsets within the eVisitNB framework, however, deployment within primary care clinics remains elusive due to our limited understanding of the needs, cultural and acceptability of triage for the francophone population with the majority being anglophone. Aim The purpose of this study is to evaluate the validity and user satisfaction of the digital medical history tool used by FirstHx at the French-language level in primary care. Design: A multi-phase study with an explanatory sequential mixed design. Methods Phase 1- Non-patient facing: In the quantitative phase, students from a French university will be recruited to perform a simulation with the French medical history tool. The students (participants) will play the role of the patient and the tool will be administered to them. Following the simulation, the participants will be asked to answer a survey to validate the French medical tool. The quality of French and the clarity of the questions will be some of the topic questions. In the qualitative phase, a descriptive approach will be used. Participants will be the same as in the quantitative phase and will be selected by purposive sampling. Data will be gathered through semi-structured interviews with a minimum of 25% of the participants from the quantitative phase. The qualitative data obtained will be employed to support the data from the quantitative survey. Phase 2 - Patient facing: In collaboration with a private clinic (Energii) in the Dieppe area the French medical history tool from phase one will be piloted with patients from the clinic Energii. The same mixed design will be conducted.
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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 | 0.047 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.044 | 0.008 |
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".