Evaluation of a Pharmacist–Dietician-Led Patient-Centered Approach to Managing CKD-MBD: A Mixed-Method Study
Bibliographic record
Abstract
Chronic kidney disease mineral and bone disorder (CKD-MBD) is a common complication in end-stage renal disease (ESRD). To improve prescribing consistency and patient outcomes, a patient-centered, pharmacist-dietician-led approach to managing CKD-MBD was developed. The purpose of this study was to evaluate if the new approach impacted serum markers of CKD-MBD and medication burden, and to evaluate patient satisfaction. A single-arm, pre-post, mixed-methods study was conducted. Serum markers of CKD-MBD and medication data were collected pre- and post-intervention, and a patient survey administered post-intervention. Focus groups were conducted, transcribed, and analyzed thematically. No statistically significant differences in serum markers of CKD-MBD or medication burden were found. Eighty-seven percent of patients were satisfied with their care, however, 31% were very dissatisfied with medical explanations provided to them and 48% felt their allotted time with healthcare professionals was too short. Four major themes identified from focus groups included lack of privacy, knowledge and perceptions of blood work rounds, issues with taking phosphate binders, and areas for increased patient education. Patients would prefer more information regarding their blood work results and more time with the healthcare team. Areas for expanded education include renal diet, phosphate binders, and consequences of abnormal bloodwork.
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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 | 0.036 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".