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The Hospitalist Movement – A Complex Adaptive Response to The Hospitalist Movement – A Complex Adaptive Response to Fragmentation of Care in Hospitals

2008· article· en· W4318812306 on OpenAlex
Kheng Hock Lee

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAnnals of the Academy of Medicine Singapore · 2008
Typearticle
Languageen
FieldMedicine
TopicHospital Admissions and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsFragmentation (computing)Health careComplex adaptive systemHealthcare systemMedicineNursingPolitical scienceComputer science

Abstract

fetched live from OpenAlex

The increasing complexity of healthcare is accelerating the rate of specialisation in medicine, which in turn aggravates the fragmentation of care in hospitals. The hospitalist movement advocates for the return of generalist physicians to the hospital to provide general and more holistic medical care to inpatients. This can be seen as an adaptive response to care fragmentation. Starting in the mid-1990s in North America, where the impact of healthcare complexity and fragmentation has been most widely felt, the hospital movement has gained strength and spread across the continent rapidly. This paper examines the phenomenon of the hospitalist movement in the United States, Canada and Singapore. The conclusion is that variants of the hospital movement may emerge in different parts of the world as healthcare systems adapt to common global trends that drive the increasing complexity of healthcare. Key words: Complexity, Generalist, Hospitalist

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.867
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.075
GPT teacher head0.365
Teacher spread0.290 · 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