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A Multi-Tiered Perspective on Healthcare Interoperability

2013· book-chapter· en· W4235883711 on OpenAlexaff
Craig Kuziemsky

Bibliographic record

VenueAdvances in healthcare information systems and administration book series · 2013
Typebook-chapter
Languageen
FieldHealth Professions
TopicElectronic Health Records Systems
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsInteroperabilityHealth careSemantic interoperabilityCross-domain interoperabilityHealthcare deliveryProcess managementKnowledge managementComputer scienceDomain (mathematical analysis)WS-I Basic ProfileProcess (computing)BusinessWorld Wide WebWeb servicePolitical science

Abstract

fetched live from OpenAlex

The current healthcare delivery paradigm is defined by integrative care delivery across disparate providers and services. Therefore the ability to deliver efficient and effective healthcare services is dependent on designing and implementing interoperable systems. However, the notion of interoperability is multifaceted and complex. Although the exchange of data is often described as analogous with interoperability it must be remembered that healthcare is a process oriented domain and clinical, management, organizational and other processes must be considered as part of interoperability. This chapter discusses healthcare delivery and the role interoperability plays in supporting its delivery. First, the chapter provides a background on healthcare interoperability from multiple perspectives. Then it presents a case study of collaborative care delivery and uses it to outline specific interoperability requirements. The chapter then uses these requirements to develop a multi-tiered framework of healthcare interoperability, concluding with a discussion of the implications of the framework for interoperability research and for systems design to support integrated healthcare delivery.

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), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.005
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.049
GPT teacher head0.404
Teacher spread0.355 · 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
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

Citations5
Published2013
Admission routes1
Has abstractyes

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