Assessment of Glycosylated Hemoglobin Outcomes Following an Enhanced Medication Therapy Management Service via Telehealth
Bibliographic record
Abstract
(1) Background: Regular contact with a medication therapy management (MTM) pharmacist is shown to improve patients’ understanding of their condition; however, continued demonstration of the value of a pharmacist delivered comprehensive medication review (CMR) using enhanced MTM services via telehealth is needed. The study aimed to describe a pilot program designed to improve type 2 diabetes mellitus (T2DM) management through enhanced condition specific MTM services. (2) Methods: This retrospective study included patients with T2DM aged 40–75 years who received a pharmacist-delivered CMR between January and December 2018. An evaluation of glycosylated hemoglobin (HbA1c) values 3 months pre- and post-CMR was performed. Wilcoxon signed-rank and chi-square tests were used. (3) Results: Of 444 eligible patients, a majority were female (58%) with a median age of 70 years. Median HbA1c values post-CMR were lower than pre-CMR (median 7.1% range 4.5–13.6; median 7.4% range 4.5–13.9, respectively; p = 0.009). There were fewer participants with HbA1c >9% post-CMR (n = 66) than pre-CMR (n = 80; p < 0.001) and more with HbA1C <6.5% post-CMR (n = 151) than pre-CMR (n = 130; p < 0.001). (4) Conclusion: This program evaluation highlighted the value of an enhanced condition specific MTM service via telehealth. Patients had improved HbA1c values three months after receiving a single pharmacist delivered CMR.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".