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Priority setting in a hospital critical care unit: Qualitative case study*

2003· article· en· W2107425125 on OpenAlexaffabout
Jens Mielke, Douglas K. Martin, Peter Singer

Bibliographic record

VenueCritical Care Medicine · 2003
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsToronto Public Health
Fundersnot available
KeywordsAccountabilityThematic analysisMedicineNegotiationPublicityUnit (ring theory)Intensive care unitRelevance (law)Qualitative researchNursingPsychologyPolitical scienceSociology

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe priority setting for admissions in a hospital critical care unit and to evaluate it using the ethical framework of "accountability for reasonableness. DESIGN: Qualitative case study and evaluation using the ethical framework of accountability for reasonableness. SETTING: A medical/surgical intensive care unit in a large urban university-affiliated teaching hospital in Toronto, Canada. PARTICIPANTS: Critical care unit staff including medical directors, nurses, residents, referring physicians, and members of a hospital committee that formulated an admissions policy. INTERVENTIONS: Modified thematic analysis of documents, interviews with participants, and direct observation of critical care unit rounds. Evaluation using the four conditions of Daniels and Sabin's accountability for reasonableness: relevance, publicity, appeals/revisions, and enforcement. MEASUREMENTS AND MAIN RESULTS: We examined key features and participants' views about the priority setting process. Decisions to admit patients involve a complex cluster of reasons. Both medical and nonmedical reasons are used, although the nonmedical reasons are less well documented and understood. Medical directors, who are the chief decision makers, differ in their reasoning. Admitting decisions and reasons are usually explained to referring staff but seldom to patients and families, and nonmedical reasons are seldom surfaced. A hospital critical care admissions policy exists but is not used and is not known to all stakeholders. A formal appeals/revisions process exists, but appeals usually involve informal negotiations. The existence of priority programs in the hospital (e.g., transplantation) adds complexity and heightens disagreement by stakeholders. CONCLUSION: We have described and evaluated admissions decision making in a hospital's critical care unit. The key lesson of our study is not only the specific findings obtained here but also how combining a case study approach with the ethical framework of "accountability for reasonableness" can be used to identify good practices and opportunities for improving the fairness of priority setting in intensive care.

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 imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0150.010
Scholarly communication0.0040.006
Open science0.0020.006
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.127
GPT teacher head0.495
Teacher spread0.367 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations75
Published2003
Admission routes2
Has abstractyes

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