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Record W1977647945 · doi:10.12927/hcq.2009.20759

Transitioning Initial Success into Sustainable Results: The Future of the WTIS

2009· article· en· W1977647945 on OpenAlexaffabout
Sharon Pfaff, Lynn Guerriero, Julian Martalog, Lindsay Arscott, Sandra Fontaine, Joseph Laforet

Bibliographic record

VenueHealthcare Quarterly · 2009
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsCancer Care Ontario
Fundersnot available
KeywordsSoftware deploymentWork (physics)BusinessInformation systemGovernment (linguistics)Health careProcess managementProject managementInformation technologyPublic relationsOperations managementKnowledge managementEngineering managementComputer scienceEngineeringPolitical scienceManagementEconomic growthEconomics

Abstract

fetched live from OpenAlex

Getting a new concept or project up and running is never an insignificant undertaking. In many cases, however, the successful completion of a project signals the start of the "real work" in which the greater challenge is in turning that initial success and investment into results that can be sustained over the long-term. This was the challenge facing Cancer Care Ontario (CCO) once they developed and deployed the Wait Time Information System (WTIS) on behalf of the Ontario Ministry of Health and Long-Term Care (MOHLTC). With the launch of the WTIS, the government, Local Health Integration Networks (LHINs), hospitals and patients had--for the first time--standardized, near real-time data to make more informed healthcare decisions and better manage access to critical health services. But much more work was ahead. The next step was to begin leveraging the technology and the wealth of data it provided to help drive significant performance improvements within the overall health system. The time had come to shift gears from an IT deployment project to a sustainable operations and information management program that could continue to provide value for the province. This article looks at the future of the WTIS and describes the journey CCO has taken to establish a permanent Wait Time Information Program. These concepts will be of interest to leaders of or participants in information management/information technology (IM/IT) projects looking for ideas on how to smoothly transition a successful project into a sustainable operational program.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.811
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.035
GPT teacher head0.419
Teacher spread0.385 · 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 designQualitative
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

Citations4
Published2009
Admission routes2
Has abstractyes

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