Pharmacy Practice Standards for Outpatient Nephrology Settings
Bibliographic record
Abstract
Patients with kidney disease represent a medically complex group of patients with high medication burdens that could benefit from clinical pharmacy services as part of the interdisciplinary care team to optimize medication use. The "Advancing American Kidney Health" executive order includes new value-based reimbursement models to be tested by the Center for Medicare and Medicaid Innovation beginning January 2021 and January 2022. Advancing American Kidney Health executive order poses opportunities for the inclusion of comprehensive medication management. Following an iterative process integrating input from a diverse expert panel, published standards, clinical practice guidelines, peer review, and stakeholder feedback, our group developed practice standards for pharmacists caring for patients with kidney disease in health care settings. The standards focus on activities that are part of direct patient care and also include activities related to public health and advocacy, population health, leadership and management, and teaching, education and dissemination of knowledge. These standards are intended to be used by a variety of professionals, from pharmacists starting new practices to practice managers looking to add a pharmacist to the clinical team, to create standardization in services provided.
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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 | 0.081 | 0.193 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".