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Record W2990345414 · doi:10.12927/hcq.2016.24695

Understanding Clinical Complexity the Hard Way: A Primary Care Journey

2016· article· en· W2990345414 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealthcare Quarterly · 2016
Typearticle
Languageen
FieldHealth Professions
TopicMedical Coding and Health Information
Canadian institutionsPublic Health Ontario
Fundersnot available
KeywordsPrimary careBest practiceNursingMedicinePsychologyFamily medicinePolitical science

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.790
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.717
GPT teacher head0.522
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it