MétaCan
Menu
Back to cohort
Record W4281563879 · doi:10.1080/20476965.2022.2075797

Assessing the maturity and performance of the IT function in acute-care hospitals: a configurational view

2022· article· en· W4281563879 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHealth Systems · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBig Data and Business Intelligence
Canadian institutionsHEC MontréalUniversité du Québec à Trois-RivièresUniversité de Sherbrooke
FundersHEC Montréal
KeywordsMaturity (psychological)Acute careFunction (biology)MedicineHealth administrationHealth informaticsNursingHealth carePsychologyPublic healthEconomics

Abstract

fetched live from OpenAlex

This study aims to characterises the maturity of IT management in hospitals, to identify the IT management configurations needed to achieve greater performance and to characterise the organisational and strategic IT contexts in which these configurations evolve. Drawing on survey data from 72 Canadian acute-care hospitals with the CIO as the main respondent, we used a configurational approach to assess the maturity of their IT functions. We classified participating hospitals in two distinct groups, each related to different levels of performance. Hospitals in the first group are characterised by a rather "immature" IT management model and presented low levels of IT performance. Hospitals in the second group showed more maturity in their IT management model and high levels of IT performance. Importantly, both the strategic influence of the CIO and the centrality of IT to the hospital's strategic goals were found to be significantly greater in the mature group.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.432

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.061
GPT teacher head0.323
Teacher spread0.262 · 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