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Record W4381326119 · doi:10.1071/ah23048

Supply and demand – a health economic perspective on the Australian hospital and elective surgery crisis

2023· article· en· W4381326119 on OpenAlexaff
Jeffrey CL Looi, Stephen Allison, Tarun Bastiampillai, Steve Kisely, Stephen Robson

Bibliographic record

VenueAustralian Health Review · 2023
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsDalhousie University
Fundersnot available
KeywordsHealth careHealth economicsPandemicContext (archaeology)Population healthBusinessPublic healthSupply and demandMedicineCoronavirus disease 2019 (COVID-19)Economic growthEconomicsNursingGeography

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has contributed to longstanding structural shortfalls in the supply of healthcare services in high-income countries, including Australia. These impacts are reflected in Australian public hospital key performance indicators for acute care, elective surgery and hospital exit block. The challenges occur in the context of increased demand following the suspension of a range of healthcare services during the pandemic. The main supply challenge is suitable numbers of skilled healthcare workers. Rebalancing of supply and demand in healthcare is challenging, but needs to be achieved.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.777
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.002

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 head0.111
GPT teacher head0.480
Teacher spread0.369 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations9
Published2023
Admission routes1
Has abstractyes

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