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Record W4404067605 · doi:10.1177/10398562241292428

Australian community and inpatient general public sector mental health services between 2017–18 and 2021–22: Relative stasis in bed capacity, increasing outpatient demand, and stunted expenditure

2024· article· en· W4404067605 on OpenAlexaff
Hayden Cornell, Stephen Allison, Tarun Bastiampillai, Steve Kisely, Jeffrey CL Looi, Matthew Brazel

Bibliographic record

VenueAustralasian Psychiatry · 2024
Typearticle
Languageen
FieldPsychology
TopicPsychiatric care and mental health services
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineSchizoaffective disorderMental healthPer capitaAmbulatoryPublic sectorPublic healthPopulationHealth economicsGerontologyPsychiatryEnvironmental healthEconomicsNursingPsychosis

Abstract

fetched live from OpenAlex

OBJECTIVE: To descriptively analyse Australian public sector General Mental Health Services (GMHS) expenditure, ambulatory, and inpatient services, including key performance indicators (KPIs) in comparison with other subspeciality mental health services (MHS). METHOD: We descriptively analysed data published by the Australian Institute of Health and Welfare (AIHW), including inpatient, ambulatory services, expenditure, and KPIs. RESULTS: From 2017-18 to 2021-22, per capita expenditure for Australian GMHS (18-64) rose by an average annual inflation-adjusted change of 2%. Overall bed numbers remained static, with non-acute beds declining, and commensurate expansion of acute beds. Community GMHS had high outpatient utilisation, with high rates of schizophrenia, schizoaffective disorder, and bipolar affective disorders as primary diagnoses in mid-life. From 2017-18 to 2021-22, GMHS inpatient and ambulatory episodes had decreasing rates of significant improvement and increasing rates of significant deterioration. CONCLUSIONS: Although GMHS has the highest overall population and service utilisation, there has been static bed availability and relatively small increases in expenditure which are occurring concurrently with worsening clinical outcomes. Evidence-based modelling of GMHS and outcomes is required to inform future service improvement.

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)0.001
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 score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.046
GPT teacher head0.350
Teacher spread0.304 · 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

Citations6
Published2024
Admission routes1
Has abstractyes

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