The IMPACT clinic
Bibliographic record
Abstract
Problem addressed The growing number of elderly patients with multiple chronic conditions presents an urgent challenge in primary care. Current practice models are not well suited to addressing the complex health care needs of this patient population. Objective of program The primary objective of the IMPACT (Interprofessional Model of Practice for Aging and Complex Treatments) clinic was to design and evaluate a new interprofessional model of care for community-dwelling seniors with complex health care needs. A secondary objective was to explore the potential of this new model as an interprofessional training opportunity. Program description The IMPACT clinic is an innovative new model of interprofessional primary care for elderly patients with complex health care needs. The comprehensive team comprises family physicians, a community nurse, a pharmacist, a physiotherapist, an occupational therapist, a dietitian, and a community social worker. The model is designed to accommodate trainees from each discipline. Patient appointments are 1.5 to 2 hours in length, during which time a diverse range of medical, functional, and psychosocial issues are investigated by the full interprofessional team. Conclusion The IMPACT model is congruent with ongoing policy initiatives in primary care reform and enhanced community-based care for seniors. The clinic has been pilot-tested in 1 family practice unit and modeled at 3 other sites with positive feedback from patients and families, clinicians, and trainees. Evaluation data indicate that interprofessional primary care models hold great promise for the growing challenge of managing complex chronic disease.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.182 | 0.017 |
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".