Intervention and Education in Diabetes: A Pilot Project Comparing Usual Care with Pharmacist-Directed Collaborative Primary Care
Bibliographic record
Abstract
Background: Prior to this project, patients were required to drive up to 2 hours to a diabetes education centre. As a result, many patients were not receiving diabetes education, and there was little or no follow-up of patients. Significant opportunity exists for pharmacists to fill such gaps in chronic disease management services. Methods: Patients were randomly assigned to the intervention or usual care arm. Laboratory data (glycosylated hemoglobin, fasting blood glucose, lipid panel, microalbumin, systolic and diastolic blood pressure) and Diabetes Empowerment Scale short form (DES-SF) score were collected at baseline and at 6 months. Intervention patients received a medication review, 3 one-on-one education sessions with one of the study pharmacists and follow-up phone calls. Usual care patients did not receive medication reviews or education sessions, and received follow-up phone calls only if drug-related problems were detected. Drug-related problems were tracked for all patients. Referrals to other health care professionals (dietitian, homecare, public health) were made as required. Paired-sample t-tests were used to compare baseline and 6-month data. Results: Forty-five patients were enrolled in the study (intervention: 23; usual care: 17). Five patients were lost to follow-up (intervention: 2; usual care: 3). There was a statistically significant improvement in DES-SF score in the intervention group ( p < 0.001) and a decline in DES-SF score in the usual care group ( p < 0.04). There was a significant decrease in glycosylated hemoglobin in the usual care group ( p < 0.04). Referrals to other health care professionals were higher in the intervention group (I: 36; UC: 0). The number of drug-related problems detected was also greater in the intervention group (I: 83; UC: 8). The overall acceptance rate of pharmacist recommendations for drug-related problems was high in both arms (I: 81%; UC: 100%). Conclusions: Most outcome measures were not statistically significant. Further study is needed to evaluate the change in clinical outcomes. However, greater involvement of a pharmacist in diabetes management resulted in greater detection of drug-related problems and referral to other health care professionals, and promoted diabetes-related self-efficacy and appropriate self-care behaviour. Pharmacists can play an important role in the management of diabetic patients.
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 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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".