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Record W2754468246 · doi:10.1177/1542305017703127

An e-Chart Review of Chaplains’ Interventions and Outcomes: A Quality Improvement and Documentation Practice Enhancement Project

2017· article· en· W2754468246 on OpenAlexaffabout
Vivian B. Stang

Bibliographic record

VenueJournal of Pastoral Care & Counseling Advancing theory and professional practice through scholarly and reflective publications · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsDocumentationPsychological interventionQuality managementChartNursingHealth careBest practiceElectronic health recordMedicineQuality (philosophy)Medical educationPsychologyOperations managementManagementComputer scienceEngineering

Abstract

fetched live from OpenAlex

In Canada, the spiritual care landscape in health care settings is becoming more regulated and standardized documentation is part of this rigorous environment. Staff chaplains at The Ottawa Hospital participated in a Quality Improvement project that aimed to advance patient-centered care through better charting practices. A sample of 104 spiritual-care assessments that had been posted on the patient electronic health record was examined. This chart review focused on chaplains' activities that were reported as interventions as well as chaplain-reported outcomes for the patient. These interventions and outcomes were coded into discreet categories in order to get a better sense of the activities and the impact of their work. The chaplains' electronic charting content and practices were evaluated. Chaplains found that the Quality Improvement process was beneficial as they updated their electronic templates in order to meet the new reporting requirements of the College of Registered Psychotherapists of Ontario.

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)0.089
metaresearch head score (Gemma)0.123
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.468

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0890.123
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.074
GPT teacher head0.533
Teacher spread0.459 · 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 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

Citations7
Published2017
Admission routes2
Has abstractyes

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Same venueJournal of Pastoral Care & Counseling Advancing theory and professional practice through scholarly and reflective publicationsSame topicReligion, Spirituality, and PsychologyFrench-language works237,207