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Record W2033141035 · doi:10.4018/jhisi.2011010101

State of IS Integration in the Context of Patient-Centered Care

2011· article· en· W2033141035 on OpenAlexaff
Ali Reza Montazemi, Jeff J. Pittaway, Karim Keshavjee

Bibliographic record

VenueInternational Journal of Healthcare Information Systems and Informatics · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicInformation Systems Theories and Implementation
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHealth careContext (archaeology)AssertionBusinessKnowledge managementInformation exchangeInformation asymmetryInformation systemPlan (archaeology)NursingPublic relationsMedicineComputer sciencePolitical science

Abstract

fetched live from OpenAlex

For more than a decade, healthcare reform has emphasized coordinated “patient-centered care”. To that end, policymakers have invested in integration of healthcare providers’ information flows. Research has studied healthcare providers’ information needs but overlooked communicative exchanges among participants in coordinating treatment plan decisions. Consequently, although medical literature asserts that patients should depend on information exchange with healthcare providers to enable participation in treatment plan decisions, the assertion has not been tested. In this paper, the authors conduct an empirical study to elucidate the structure of actors’ communications in support of their information dependencies. The findings illustrate that although patients are well connected through personal contact with healthcare providers, patients are disenfranchised from integrated healthcare information systems (IS) and the potential of IS to support patients’ participation in coordinated “patient-centered care” decisions. Furthermore, knowledge asymmetry between patients and healthcare providers should be considered in the selection and design of healthcare IS.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.003
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 head0.039
GPT teacher head0.338
Teacher spread0.298 · 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 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

Citations5
Published2011
Admission routes1
Has abstractyes

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