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Record W2145234345 · doi:10.1071/ah13133

Factors associated with transfers from healthcare facilities among readmitted older adults with chronic illness

2014· article· en· W2145234345 on OpenAlexaff
Tasneem Islam, Bev OʼConnell, Mary Hawkins

Bibliographic record

VenueAustralian Health Review · 2014
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineOdds ratioHealth careSocioeconomic statusConfidence intervalPublic healthMultivariate analysisLogistic regressionMedical recordUnivariate analysisAcute careResidenceEmergency medicineEnvironmental healthPopulationDemographyInternal medicineNursing

Abstract

fetched live from OpenAlex

Objective Because chronic illness accounts for a considerable proportion of Australian healthcare expenditure, there is a need to identify factors that may reduce hospital readmissions for patients with chronic illness. The aim of the present study was to examine a range of factors potentially associated with transfer from healthcare facilities among older adults readmitted to hospital within a large public health service in Melbourne, Australia. Methods Data on readmitted patients between June 2006 and June 2011 were extracted from hospital databases and medical records. Adopting a retrospective case-control study design, a sample of 51 patients transferred from private residences was matched by age and gender with 55 patients transferred from healthcare facilities (including nursing homes and acute care facilities). Univariate and multivariate logistic regression analyses were used to compare the two groups, and to determine associations between 46 variables and transfer from a healthcare facility. Results Univariate analysis indicated that patients readmitted from healthcare facilities were significantly more likely to experience relative socioeconomic advantage, disorientation on admission, dementia diagnosis, incontinence and poor skin integrity than those readmitted from a private residence. Three of these variables remained significantly associated with admission from healthcare facilities after multivariate analysis: relative socioeconomic advantage (odds ratio (OR) 11.30; 95% confidence interval (CI) 2.62–48.77), incontinence (OR 7.18; 95% CI 1.19–43.30) and poor skin integrity (OR 18.05; 95% CI 1.85–176.16). Conclusions Older adults with chronic illness readmitted to hospital from healthcare facilities are significantly more likely to differ from those readmitted from private residences in terms of relative socioeconomic advantage, incontinence and skin integrity. The findings direct efforts towards addressing the apparent disparity in management of patients admitted from a facility as opposed to a private residence. What is known about the topic? Older adults with chronic disease require ongoing medical care in both community and healthcare settings. They may frequently require emergency admission to hospital for management of exacerbations of their chronic disease. Previous Australian research has found that transfer from a healthcare facility may be associated with likelihood of readmission among older adults. What does this paper add? This research addresses the shortage of research on the link between transfer from a healthcare facility and likelihood of readmission within Australia. Older adults with chronic illness readmitted to hospital from healthcare facilities were found to be significantly more likely to differ from those readmitted from private residences in terms of relative socioeconomic advantage, incontinence and skin integrity. What are the implications for practitioners? The findings may be used to identify older readmitted patients with chronic diagnoses at greater risk of presenting with poor skin integrity or incontinence, and direct efforts towards addressing the apparent disparity in management of patients admitted from facilities as opposed to private residences. Sound discharge planning and clear channels of communication between healthcare facilities are particularly important for patients transferred between facilities.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.247
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.054
GPT teacher head0.313
Teacher spread0.259 · 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 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
Published2014
Admission routes1
Has abstractyes

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