Drug-Related Problems on Hospital Admission: Relationship to Medication Information Transfer
Bibliographic record
Abstract
BACKGROUND: Patients with end-stage renal disease (ESRD) are at risk for drug-related problems (DRPs), especially on hospital admission. OBJECTIVE: To identify and characterize the DRPs experienced by patients with ESRD on admission and investigate how these DRPs could be related to gaps in medication information transfer. METHODS: Patients with ESRD admitted to the hospital were prospectively identified and clinically assessed by a pharmacist to identify and categorize DRPs on admission. Each DRP was evaluated to determine whether it could have been caused by a gap in medication information transfer. For DRPs caused in this manner, the interface in the information transfer process where the gap may have occurred was determined. RESULTS: A total of 199 DRPs were identified in 47 patients with ESRD over a 12 week period. Ninety-two percent of patients had at least one DRP on admission, with an average of 4.2 +/- 2.2 DRPs per patient. The most common DRP identified was indication for drug therapy--patient requires drug but is not receiving it (51.3%). Of the total DRPs, 130 (65%) were related to gaps in medication information transfer, with 21.5% occurring between the inpatient hospital and the ambulatory clinic pharmacists and 17.7% between the admitting physician and the patient. CONCLUSIONS: Results of this study demonstrate that, in patients with ESRD, DRPs on admission are frequently related to gaps in medication information transfer between healthcare professionals and also between healthcare providers and patients. Improved communication is required at medication information transfer interfaces to prevent these DRPs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".