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Record W2910110903 · doi:10.1071/ah18073

Examination of the dependency and complexity of patients admitted to in-patient rehabilitation in Australia

2019· article· en· W2910110903 on OpenAlexaff
Duncan McKechnie, Julie Pryor, Murray Fisher, Tara L Alexander

Bibliographic record

VenueAustralian Health Review · 2019
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsMount Royal University
Fundersnot available
KeywordsRehabilitationMedicineCohortPhysical therapyComorbidityEpidemiologyRetrospective cohort studyInternal medicine

Abstract

fetched live from OpenAlex

Objective The aim of this study was to determine whether there has been a measurable change in the dependency and complexity of patients admitted to in-patient rehabilitation in Australia between 2007 and 2016. Methods A retrospective cohort study design was used to examine in-patient rehabilitation data held in the Australasian Rehabilitation Outcomes Centre Registry Database for the period 2007-16. Epidemiological descriptive analysis was used to examine datasets for difference between four discrete years (2007, 2010, 2013 and 2016). Datasets included patient demographics, length of stay (LOS), comorbidities, complications and the Functional Independence Measure (FIM™). Results Between 2007 and 2016, rehabilitation in-patients as a whole: (1) had a mean decrease in total admission FIM score; (2) became more complex, as evidenced by the increased proportion of particular comorbidities impacting on rehabilitation, namely cardiac and respiratory disease, dementia, diabetes and morbid obesity; and (3) had a mean decrease in total discharge FIM score. However, there was an increase in the proportion of patients discharged home from rehabilitation (from 86.5% to 92%) and decreases in onset and rehabilitation LOS of 2.2 and 2.5 days respectively. Conclusion The dependency and complexity of patients admitted to in-patient rehabilitation in Australia has increased between 2007 and 2016. What is known about the topic? Anecdotal reports suggest that rehabilitation patients in Australia have become more complex, necessitating increased active management of their presenting health condition and comorbid health conditions. However, to date, no systematic investigation has been undertaken to examine trends in rehabilitation in-patient dependency and complexity over time. What does this paper add? This study provides measurable evidence of increased dependency and complexity in patients admitted to rehabilitation in Australia. Further, compared with 2007, rehabilitation in-patients as a whole had an increased burden of care on discharge from rehabilitation in 2016. What are the implications for practitioners? The changes in patient dependency and complexity reported in this study have implications for rehabilitation service delivery. This is because the increased need for illness or injury and comorbidity management may result in increased potential for acute complications and health deterioration, and compensatory care for patients during rehabilitation. Clinicians may need to widen their skill set to include more acute and chronic illness 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 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)0.002
metaresearch head score (Gemma)0.011
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 score0.027
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
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 head0.104
GPT teacher head0.396
Teacher spread0.292 · 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

Citations8
Published2019
Admission routes1
Has abstractyes

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