Effect of a formalised discharge process which includes electronic delivery of prescriptions to pharmacies on the incidence of delayed prescription retrieval
Bibliographic record
Abstract
BACKGROUND: Lack of prescription adherence after discharge from the inpatient hospital setting is a barrier to the delivery of optimal patient care. Non-adherence to medication for cardiac diseases can lead to substantial morbidity, mortality and healthcare costs. Electronic delivery of prescriptions by fax is a potential method of improving patient satisfaction and reducing pharmacy wait times. METHODS: This study was completed in the cardiology inpatient wards at a hospital in London, Ontario, Canada. 'Delayed prescription retrieval' was defined as the retrieval of a prescribed medication by a patient from their local pharmacy after the documented calendar day of discharge. The current discharge process on the cardiology wards was assessed and an initial monitoring period of study participants was completed to determine the baseline delayed prescription retrieval rate (preintervention group). A formalised discharge process, which included electronic delivery of prescriptions to pharmacies by fax, was implemented for study participants (postintervention group). The rate of delayed prescription retrieval was assessed in both groups. RESULTS: 15 of 42 patients (35.7%) in the preintervention group and 9 of 72 (14.3%) in the postintervention group had delayed prescription retrieval suggesting relative and absolute risk reductions of 65% and 23.2% (p=0.0045). Of the participants with delayed prescription retrieval, 100% in the preintervention group and 77.8% in the postintervention group were due a new prescribed medication on the day of discharge. CONCLUSIONS: Patients who experienced a formalised discharge process, which included electronic delivery of prescriptions by fax, at the time of discharge from cardiac inpatient care had a lower rate of delayed prescription retrieval. Future studies are required to examine the impact of formal discharge processes on patient morbidity and mortality.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".