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Record W2115833431 · doi:10.4018/joeuc.2015040101

Strategic Information System Planning in Healthcare Organizations

2015· article· en· W2115833431 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.

Bibliographic record

VenueJournal of Organizational and End User Computing · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInformation Technology Governance and Strategy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsStrategic information systemHealth careBusinessKnowledge managementInformation systemQuality (philosophy)Healthcare industryInformation technologyHealthcare systemMarketingComputer scienceHealth informaticsEngineeringEconomicsEconomic growth

Abstract

fetched live from OpenAlex

The healthcare industry is a critical and growing part of economies worldwide. To provide better quality of care, and value for money, billions of dollars are being spent on bettering information systems in healthcare organizations. Strategic Information System Planning (SISP) is instrumental in making informed decisions to achieve the health organizations' goals and objectives. This paper undertakes a systematic review to gain insight into existing studies on SISP in healthcare organizations. Our systematic review of papers on SISP from 1985 to 2011 examines the background and trend of research into SISP in the healthcare industry, classification of topics in SISP, as well as sets of tools and guidelines to aid practitioners and the research community alike.

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)0.000
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 score0.435
Threshold uncertainty score0.293

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 studies0.0000.000
Scholarly communication0.0000.002
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 head0.019
GPT teacher head0.223
Teacher spread0.203 · 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