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Record W2807777002 · doi:10.11124/jbisrir-2017-003492

Strategies for communicating patient health information between emergency and primary care settings: a scoping review protocol

2018· review· en· W2807777002 on OpenAlexaff
Andrea Bishop, Janet Curran, Heather Rose, Shelley McKibbon

Bibliographic record

VenueThe JBI Database of Systematic Reviews and Implementation Reports · 2018
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsKellogg's (Canada)Izaak Walton Killam Health CentreDalhousie University
Fundersnot available
KeywordsInformation exchangePrimary careIntervention (counseling)Protocol (science)Medical emergencyHealth information exchangeMedicineEmergency departmentHealth careNursingKnowledge managementHealth informationComputer scienceAlternative medicineFamily medicine

Abstract

fetched live from OpenAlex

REVIEW QUESTION: The objective of this scoping review is to explore strategies being used to communicate patient information between emergency and primary care settings. This information will be used as a first step to develop an intervention to improve information exchange and communication between emergency and primary care providers.Specifically the review questions are:i) What tools and strategies are being used to support the communication and exchange of patient information between emergency and primary care settings?ii) What models/frameworks are being used to guide the development of these strategies and tools?iii) What are the identified barriers to exchanging patient information between emergency and primary care settings?iv) What are the outcomes measures reported in these studies?

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.098
metaresearch head score (Gemma)0.124
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.098
Threshold uncertainty score0.516

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0980.124
Meta-epidemiology (narrow)0.0040.005
Meta-epidemiology (broad)0.0110.014
Bibliometrics0.0200.018
Science and technology studies0.0050.005
Scholarly communication0.0080.009
Open science0.0050.008
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0400.009

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 head0.116
GPT teacher head0.449
Teacher spread0.333 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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
Published2018
Admission routes1
Has abstractyes

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