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Record W1987070476 · doi:10.1057/palgrave.jors.2601894

Incorporating operations research techniques to evaluate information systems impact on healthcare

2004· article· en· W1987070476 on OpenAlexaffabout
Kevin J. Leonard, Jia Lu Lilian Lin, Sandra Dalziel, Rye Yern Yap, David R. Adams

Bibliographic record

VenueJournal of the Operational Research Society · 2004
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBig Data and Business Intelligence
Canadian institutionsCanadian Hospice Palliative Care AssociationHome and Community Care Support ServicesStatistics CanadaUniversity of Toronto
Fundersnot available
KeywordsInformation systemHealth careInformation technologyComputer scienceProject managementOperations researchInformation and Communications TechnologyScheduling (production processes)PurchasingHealthcare systemManagement scienceRisk analysis (engineering)Operations managementSystems engineeringBusinessEngineeringEconomics

Abstract

fetched live from OpenAlex

Abstract Over the past 4 years, the Hospice Palliative Care Network Project, co-led by the Temmy Latner Centre for Palliative Care, Mount Sinai Hospital, and the Toronto Community Care Access Centre, has been working toward developing an innovative model of home palliative care coordination and service delivery. After a successful completion of stage one involving data collection of approximately 400 variables to a common Linux database repository, the current stage of the Project is to compare various modes of care delivery and disseminate the results to internal and external evaluation stakeholders. The Temmy Latner Centre's customized Panacea Information Management System (PIMS) had been linked to the Linux repository in order to customize reports to determine the optimal model of coordination and service delivery that could serve as a template for home palliative care delivery in Ontario. The objective of this paper is to outline the development and functionality of the PIMS and to evaluate its contribution in terms of improved data quality and health outcomes; in other words, to justify the information systems investment by demonstrating the relationship between this investment and improved health system delivery and effectiveness.

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)0.012
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.000
Scholarly communication0.0020.004
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 head0.246
GPT teacher head0.484
Teacher spread0.238 · 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
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
Published2004
Admission routes2
Has abstractyes

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