Effect of point-of-care computer reminders on physician behaviour: a systematic review
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Bibliographic record
Abstract
BACKGROUND: The opportunity to improve care using computer reminders is one of the main incentives for implementing sophisticated clinical information systems. We conducted a systematic review to quantify the expected magnitude of improvements in processes of care from computer reminders delivered to clinicians during their routine activities. METHODS: We searched the MEDLINE, Embase and CINAHL databases (to July 2008) and scanned the bibliographies of retrieved articles. We included studies in our review if they used a randomized or quasi-randomized design to evaluate improvements in processes or outcomes of care from computer reminders delivered to physicians during routine electronic ordering or charting activities. RESULTS: Among the 28 trials (reporting 32 comparisons) included in our study, we found that computer reminders improved adherence to processes of care by a median of 4.2% (interquartile range [IQR] 0.8%-18.8%). Using the best outcome from each study, we found that the median improvement was 5.6% (IQR 2.0%-19.2%). A minority of studies reported larger effects; however, no study characteristic or reminder feature significantly predicted the magnitude of effect except in one institution, where a well-developed, "homegrown" clinical information system achieved larger improvements than in all other studies (median 16.8% [IQR 8.7%-26.0%] v. 3.0% [IQR 0.5%-11.5%]; p = 0.04). A trend toward larger improvements was seen for reminders that required users to enter a response (median 12.9% [IQR 2.7%-22.8%] v. 2.7% [IQR 0.6%-5.6%]; p = 0.09). INTERPRETATION: Computer reminders produced much smaller improvements than those generally expected from the implementation of computerized order entry and electronic medical record systems. Further research is required to identify features of reminder systems consistently associated with clinically worthwhile improvements.
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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 | 0.016 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.009 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it