Drug-Therapy Problems, Inconsistencies and Omissions Identified During a Medication Reconciliation and Seamless Care Service
Bibliographic record
Abstract
Seamless care is the desirable continuity of care delivered to a patient in the healthcare system across the spectrum of caregivers and their environments. Medication Reconciliation is one component of seamless pharmaceutical care. A randomized controlled trial, carried out over nine months with a six-month follow-up period, investigated the impact of a pharmacist-directed seamless care service. Intervention patients admitted to one of two general medicine units were subjected to a comprehensive seamless care discharge process as they were discharged from a regional, academically affiliated hospital in Moncton, NB. The number, type and potential clinical impact of drug-therapy problems for seamless monitoring (DTPsm) and drug-therapy inconsistencies and omissions (DTIOs) in hospital discharge medications were measured. A total of 253 patients, with 134 patients in the intervention group and 119 in the control group, completed the study. An average of 3.59 DTPsm per intervention patient, with 72.1% of these being scored as having a significant or very significant clinical impact level, were communicated to community pharmacists. Ninety-nine DTIOs were identified and resolved in intervention patients before discharge. A retrospective medical chart review demonstrated that the intervention resolved almost all DTIOs. In conclusion, a pharmacist-directed seamless care service had a significant impact on drug-related clinical outcomes and processes of care.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".