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Record W1720655909

COPD patient and caregiver assessments of care transition quality

2011· article· en· W1720655909 on OpenAlexaffabout
Donna Goodridge, Shelly Hutchinson, Darcy D. Marciniuk, Donna Rennie

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineCOPDHealth careWarning signsPhysical therapyQuality of life (healthcare)Family medicineNursingInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Background: The high health care utilization of many patients with advanced COPD may reflect sub-optimal preparation of the patient and caregiver to effectively manage COPD upon discharge. Purpose: To examine the assessments of COPD patients and their caregivers regarding care transition quality within two weeks of discharge from hospital. Design: This cross-sectional study included 22 dyads (N=44) of patients with advanced COPD (MRC 3, 4 or 5) and their caregivers in two Canadian cities. The Care Transitions Measure (CTM-15) was used to obtain scores from both the patients and caregiver on the quality of care transition. CTM-15 scores range from 0-100, with higher scores indicating higher quality of care transition. Correlations between CTM-15 scores, global rating of health and the Clinical COPD Questionnaire (CCQ) were assessed. Results: Median CTM-15 score for patients was 58.9 (IQR= 30.5) compared with 46.7 (IQR= 16.5) for caregivers (NS). The majority of patients did not have clear health goals upon discharge (63.6%) a written plan of care (59.1%). Caregivers did not understand warning signs and symptoms to monitor (72.7%), understand how to manage the patient9s health (68.2%) or have all the information needed to be able to take care of the patient upon discharge (54.5%). CTM-15 scores were negatively correlated with CCQ scores (p=0.04) but not with global rating of health. Interpretation: COPD patients and their caregivers require additional preparation for discharge and reported important gaps that have important implications for self-care in the community. CTM-15 scores in this study were lower than those previously reported in geriatric literature.

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)0.003
metaresearch head score (Gemma)0.008
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.067
GPT teacher head0.356
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

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

Citations0
Published2011
Admission routes2
Has abstractyes

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