Bibliographic record
Abstract
Ten years ago, complexity was not a term often used in primary care. In the last decade, however, the population seen in primary care has shifted, posing substantial challenges for both primary care providers and health systems. In this essay, I will document the approaches that evolved in an academic family practice environment to address the challenges posed by complex patients typified by multiple concurrent chronic conditions and social determinants challenges. I will describe the research that lead to the creation, implementation and evaluation of an inter-professional model of care and associated outcomes. I will describe how this work subsequently led to the evolution of clinical models and research projects designed to reframe the discourse around complexity as well as move forward on elaborating new policy, clinical and service delivery innovations. I will conclude with some thoughts about what I see as the major challenges in the short and immediate term for research and practice, drawing on 15 years of practice and research experience with complex populations.
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 | 0.042 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.031 | 0.065 |
| Scholarly communication | 0.032 | 0.037 |
| Open science | 0.004 | 0.031 |
| Research integrity | 0.016 | 0.031 |
| Insufficient payload (model declined to judge) | 0.005 | 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".