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Record W3048184921 · doi:10.35680/2372-0247.1480

Is this really happening? Family-centered care during COVID-19: People before policy

2020· article· en· W3048184921 on OpenAlexaff
Terri Savino, Karri Crispino

Bibliographic record

VenuePatient Experience Journal · 2020
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsMiddlesex London Health Unit
Fundersnot available
KeywordsPhoneFeelingVisitor patternHappeningWifePsychologyCoronavirus disease 2019 (COVID-19)NursingMedicineMedical emergencyInternet privacySocial psychologyComputer sciencePolitical scienceLawHistory

Abstract

fetched live from OpenAlex

In the middle of a global pandemic, hospitals created policies for visitor restrictions to reduce the transmission of coronavirus to protect patients and staff and developed protocols allowing only one support person to call the critical care unit for patient updates. Late on a Tuesday afternoon, the Manager of Patient Experience received a phone call asking her to call Karri, the wife of one of our patients who was on a ventilator. Karri was struggling with updating her mother-in-law because she was very upset with the news she received, making it difficult to call her husband’s mom. Karri asked the nurse on the phone if her mother-in-law could call in to get updates and was bluntly advised, “No we only allow one family member to call in to get updates.” Although Karri understood the protocol, she wished it had been a different response. This narrative describes the feelings and emotions experienced by Karri, along with what the Middlesex Health did to put people before policy to reduce the suffering for Karri and provide family-centered care. Experience Framework This article is associated with the Patient, Family & Community Engagement lens of The Beryl Institute Experience Framework. (http://bit.ly/ExperienceFramework) Access other PXJ articles related to this lens. Access other resources related to this lens.

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)0.000
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.100
GPT teacher head0.406
Teacher spread0.306 · 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.

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

Citations1
Published2020
Admission routes1
Has abstractyes

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