How information retrieval technology may impact on physician practice: an organizational case study in family medicine
Bibliographic record
Abstract
RATIONALE: Information retrieval technology tends to become nothing less than crucial in physician daily practice, notably in family medicine. Nevertheless, few studies examine impacts of this technology and their results appear controversial. AIMS AND OBJECTIVES: Our article aims to explore these impacts using the medical literature, an organizational case study and the literature on organizations. METHODS: The case study was embedded in an evaluation of the implementation of medical and pharmaceutical databases on handheld computers in a Canadian family medicine centre. Six physicians were interviewed on specific events relative to the use of these databases and on their general perception of impacts of this use on clinical decision making and the doctor-patient relationship. A thematic data analysis was performed concomitantly by both authors. RESULTS AND CONCLUSION: Findings indicate six types of impact: practice improvement, reassurance, learning, confirmation, recall and frustration. These findings are interpreted in accordance with both a medical and organizational perspective. The fit with the literature on inter-organizational memory supports the transferability of the findings. In turn, this fit suggests how information retrieval technology may change physician routine. This study suggests a new basis for evaluating the impact of information retrieval technology in daily clinical practice. In conclusion, our paper encourages policy-makers to develop, and physicians to use, this technology.
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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 | 0.063 | 0.257 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.006 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".