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Record W1977450150 · doi:10.4018/jhisi.2006010101

A Metric for Healthcare Technology Management (HCTM)

2006· article· en· W1977450150 on OpenAlexaffabout
George Eisler, Joseph Tan, Samuel Sheps

Bibliographic record

VenueInternational Journal of Healthcare Information Systems and Informatics · 2006
Typearticle
Languageen
FieldHealth Professions
TopicQuality and Safety in Healthcare
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsConstruct (python library)Metric (unit)Health careKnowledge managementEmpirical researchProcess (computing)Health technologySet (abstract data type)Computer scienceField (mathematics)BusinessMarketingPolitical science

Abstract

fetched live from OpenAlex

Among key drivers of healthcare reform in Canadian society are the challenges faced by the rapid rate of technological change and its impact on organizational performance in terms of efficiency, cost-effectiveness, and innovation in business and operational processes. However, despite the noted significance of the impact of technological change on healthcare organizations, the challenge of healthcare technology management (HCTM) has received only scattered and marginal attention in the technology management (TM) literature. The lack of formalization in HCTM construct, attributes, and measures motivated an empirical study to develop a metric for HCTM. This metric was then used to assess HCTM practices in teaching hospitals across Canada. The project began with an analysis of developments to date in the fields of Management of Technology and Management of Medical Technology. An extensive literature content analysis generated a set of definitions and attributes of the conceptual TM construct, which was eventually extended to HCTM. A measuring instrument was developed through a formal design process involving expert panel review, pilot testing, instrument refinement, and field-testing to extract and measure HCTM performance indicators. Administration of this metric with the help of the Association of Canadian Academic Health Organizations via a Web-based survey of senior healthcare administrators provided insights into the HCTM status of Canadian teaching hospitals and its relationship with organizational performance.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.901
Threshold uncertainty score0.721

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
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 head0.419
Teacher spread0.374 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations5
Published2006
Admission routes2
Has abstractyes

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