Integrating Family Medicine and Pharmacy to Advance Primary Care Therapeutics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The prevalence of suboptimal prescribing of medications is well documented. Patients are often undertreated or not offered therapeutic treatments that are likely to confer benefit. As a result, drug-related hospital admissions are common and often preventable. Improvements to the health-care system are clearly needed in order to maximize the benefits that can be derived from medications. Many countries are changing their primary health-care systems to improve the quality of health-care delivery. One main transformation is the use of multidisciplinary care teams to provide care in a coordinated manner often from the same location or by using the common medical record of the patients. It has been demonstrated that pharmacists can improve prescribing, reduce health-care utilization and medication costs, and contribute to clinical improvements in many chronic medical conditions, such as cardiovascular disease, diabetes, and psychiatric illness. However, the effect of integrating a pharmacist providing general services into a primary care group has not been extensively studied. The Integrating Family Medicine and Pharmacy to Advance Primary Care Therapeutics (IMPACT) project was designed to provide a real-world demonstration of the feasibility of integrating the pharmacist into primary care office practice. This article provides a description of the IMPACT project participants; the IMPACT practice model and the concepts incorporated in its development; some initial results from the program evaluation; sustainability of the model; and some reflections on the implementation of the practice model.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it