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Record W2591531340 · doi:10.1177/2327857915041028

Twelve Tips to Designing a Situation Display for the Healthcare Team

2015· article· en· W2591531340 on OpenAlexaff
Avi Parush, Kathryn Momtahan, Chelsea Kramer, Ben Sohmer, George Mastorias, Lisa A. Calder

Bibliographic record

VenueProceedings of the International Symposium on Human Factors and Ergonomics in Health Care · 2015
Typearticle
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsUniversity of OttawaUniversité LavalOttawa HospitalCarleton University
Fundersnot available
KeywordsSituation awarenessHealth careSituational ethicsUnit (ring theory)Medical emergencyFocus (optics)Situation analysisKnowledge managementPsychologyMedicineComputer scienceEngineeringBusiness

Abstract

fetched live from OpenAlex

The objective of the team display is to present a current and dynamic situation picture to the healthcare team. The challenges in designing such a display are determining the relevant situational information and presenting it in a way that is timely, unobtrusive, and not overloading. The tips here focus on designing situation displays for healthcare teams during a clinical procedure (such as a surgery or a procedure in the emergency unit). These tips are based on the experience of designing two healthcare team situation displays, one for the cardiac OR team and the other for the ED/Resuscitation bay team, as well knowledge transferred from forest fire incident management.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.113
GPT teacher head0.410
Teacher spread0.297 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2015
Admission routes1
Has abstractyes

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