Do Combined Pharmacist and Prescriber Efforts on Medication Reconciliation Reduce Postdischarge Patient Emergency Department Visits and Hospital Readmissions?
Bibliographic record
Abstract
BACKGROUND: Although medication reconciliation (Med Rec) has demonstrated a reduction in potential adverse drug events, its effect on hospital readmissions remains inconclusive. OBJECTIVE: To evaluate the impact of an interprofessional Med Rec bundle from admission to discharge on patient emergency department visits and hospital readmissions (hospital visits). METHODS: The design was a retrospective, cohort study. Patients discharged from general internal medicine over a 57-month interval were identified through administrative databases. Patients who received an enhanced, Gold level, Med Rec bundle (including both admission Med Rec and interprofessional pharmacist-prescriber collaboration on discharge Med Rec) were assigned to the intervention group. Patients who received partial Med Rec services, Silver and Bronze level, comprised the control group. The primary outcome was hospital visits within 30 days of discharge. RESULTS: Over a 57-month period, 9931 unique patient visits (n = 8678 patients) met the study criteria. The main analysis did not detect a difference in 30-day hospital visits between the intervention (Gold level bundle) and control (21.25% vs 19.26%; adjusted odds ratio, 1.06; 95% confidence interval [CI], 0.95-1.19). Propensity score adjustment also did not detect an effect (16.7% vs18.9%; relative risk of readmission, 0.88; 95% CI, 0.59-1.32). CONCLUSION: A long-term, observational evaluation of interprofessional Med Rec did not detect a difference in 30- day postdischarge patient hospital visits between patients who received enhanced versus partial Med Rec patient care bundles. In future prospective studies, researchers could focus on evaluating high-risk populations and specific elements of Med Rec services on avoidable, medication-related hospital admissions and postdischarge adverse drug events.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".