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Record W4308320943 · doi:10.1177/10398562221135492

Australian older persons mental health inpatient and ambulatory services in 2015–2020 – A descriptive analysis and commentary

2022· article· en· W4308320943 on OpenAlexaff
Matthew Brazel, Stephen Allison, Tarun Bastiampillai, Steve Kisely, Samantha M. Loi, Jeffrey CL Looi

Bibliographic record

VenueAustralasian Psychiatry · 2022
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMental healthPer capitaMedicineDescriptive statisticsAmbulatoryPopulationGerontologyWelfareHealth economicsAmbulatory careHealth careCommissionDemographyEnvironmental healthPublic healthPsychiatryNursingBusinessFinanceEconomic growth

Abstract

fetched live from OpenAlex

OBJECTIVE: To provide a commentary on Australian state/territory older persons mental health service (OPMHS) expenditure, inpatient and outpatient services and key performance indicators (KPIs). METHOD: Descriptive analysis of data from the Australian Institute of Health and Welfare (AIHW), the Australian Bureau of Statistics and the World Health Organisation. RESULTS: Between 2015-16 and 2019-20, annual expenditure on OPMHS in Australia increased by an average of only 2.3%, compared to 2.9% for all population groups, despite an increase in the number of over 65 year olds. Per capita recurrent expenditure on OPMHS decreased by an average of 1% annually. Australia's total mental health beds increased, whereas OPMHS beds decreased, mainly due to a reduction in non-acute beds. Outcomes for OPMHS admissions were similar to other age groups, except for a longer length of stay and reduced readmission rate. Older Australians accessed ambulatory mental health care at a lower rate and had a lower rate of improvement after a completed episode. CONCLUSIONS: OPMHS expenditure has not increased at commensurate levels compared to other populations. The mental health of people aged over 65 appears to be a neglected policy priority in Australia. The Royal Commission into Aged Care Quality and Safety may herald service and expenditure changes.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.325
Teacher spread0.312 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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