Understanding Engagement and the Potential Impact of an Electronic Drug Repository: Multi-Methods Study (Preprint)
Bibliographic record
Abstract
BACKGROUND Centralized drug repositories can reduce adverse events and inappropriate prescriptions by enabling access to dispensed medication data at the point of care; however, how they achieve this goal is largely unknown. OBJECTIVE This study aims to understand the perceived clinical value; the barriers to and enablers of adoption; and the clinician groups for which a provincial, centralized drug repository may provide the most benefit. METHODS A mixed methods approach, including a web-based survey and semistructured interviews, was used. Participants were clinicians (eg, nurses, physicians, and pharmacists) in Ontario who were eligible to use the digital health drug repository (DHDR), irrespective of actual use. Survey data were ranked on a 7-point adjectival scale and analyzed using descriptive statistics, and interviews were analyzed using qualitative descriptions. RESULTS Of the 161 survey respondents, only 40 (24.8%) actively used the DHDR. Perceptions of the utility of the DHDR were neutral (mean scores ranged from 4.11 to 4.76). Of the 75.2% (121/161) who did not use the DHDR, 97.5% (118/121) rated access to medication information (eg, dose, strength, and frequency) as important. Reasons for not using the DHDR included the cumbersome access process and the perception that available data were incomplete or inaccurate. Of the 33 interviews completed, 26 (79%) were active DHDR users. The DHDR was a satisfactory source of secondary information; however, the absence of medication instructions and prescribed medications (which were not dispensed) limited its ability to provide a comprehensive profile to meaningfully support clinical decision-making. CONCLUSIONS Digital drug repositories must be adjusted to align with the clinician’s needs to provide value. Ensuring integration with point-of-care systems, comprehensive clinical data, and streamlined onboarding processes would optimize clinically meaningful use. The electronic provision of accessible drug information to providers across health care settings has the potential to improve efficiency and reduce medication errors.
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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 | 0.031 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".