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Towards Patient-Driven Agile Supply Chains in Healthcare

2012· book-chapter· en· W4252789387 on OpenAlexaff
Véronique Nabelsi

Bibliographic record

VenueSupply Chain Management · 2012
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsSupply chainAgile software developmentBusinessHealth careOrder (exchange)Supply chain managementProcess managementIndustrial organizationOperations managementMarketingEngineeringEconomicsManagementFinance

Abstract

fetched live from OpenAlex

Healthcare organizations in many countries are compelled to pursue drastic supply cost reductions, while continuing to improve patient health outcomes, as they must meet ever increasing economic and performance pressures brought on by changes in national health policies. As demonstrated in many other industries, these improvements require more integrated Supply Chain Management (SCM) practices, processes, and systems. The author develops a strategic framework for Customer-Oriented or Patient-Driven SCM, integrating the evolving economics of the healthcare industry and the emerging dynamics of global supply chains. The chapter focuses on modern SCM approaches such as agile and lean supply chains, in order to efficiently realign hospitals and their Material Management Systems (MMS) on patient health outcomes.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.890
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.004

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 head0.024
GPT teacher head0.236
Teacher spread0.212 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2012
Admission routes1
Has abstractyes

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