Clinical impact of a pharmacist-led inpatient anticoagulation service: a review of the literature
Bibliographic record
Abstract
BACKGROUND: Anticoagulant therapies provide management options for potentially life-threatening thromboembolic conditions. They also carry significant safety risks, requiring careful consideration of medication dose, close monitoring, and follow-up. Inpatients are particularly at risk, considering the widespread use of anticoagulants in hospitals. This has prompted the introduction of safety goals for anticoagulants in Canada and the USA, which recommend increased pharmacist involvement to reduce patient harm. The goal of this review is to evaluate the efficacy and safety of pharmacist-led inpatient anticoagulation services compared to usual or physician-managed care. METHODS: This narrative review includes articles identified through a literature search of PubMed, Embase, and International Pharmaceutical Abstracts databases, as well as hand searches of the references of relevant articles. Full publications of pharmacist-managed inpatient anticoagulation services were eligible if they were published in English and assessed clinical outcomes. RESULTS: Twenty-six studies were included and further divided into two categories: 1) autonomous pharmacist-managed anticoagulation programs (PMAPs) and 2) pharmacist recommendation. Pharmacist management of heparin and warfarin appears to result in improvements in some surrogate outcomes (international normalized ratio [INR] stability and time in INR goal range), while results for others are mixed (time to therapeutic INR, length of stay, and activated partial thromboplastin time [aPTT] measures). There is also some indication that PMAPs may be associated with reduced patient mortality. When direct thrombin inhibitors are managed by pharmacists, there seems to be a shorter time to therapeutic aPTT and a greater percentage of time in the therapeutic range, as well as a decrease in the frequency of medication errors. Pharmacist recommendation services have generally resulted in a greater time in therapeutic INR range, greater INR stability, decreased length of stay, and reduced major drug interactions, with no significant differences in safety outcomes. CONCLUSION: Pharmacist-led inpatient anticoagulation management seems to result in superior outcomes, as compared to usual or physician-managed care. This conclusion is limited by small, poorly designed studies lacking statistical power, focusing mainly on surrogate outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".