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Record W4393432995 · doi:10.5334/ijic.7623

Interprofessional Teams Supporting Care Transitions from Hospital to Community: A Scoping Review

2024· review· en· W4393432995 on OpenAlexafffund
Cara L. Brown, Brenda J. Tittlemier, Komal Krishna Tiwari, Hal Loewen

Bibliographic record

VenueInternational Journal of Integrated Care · 2024
Typereview
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsCanadian Physiotherapy AssociationManitoba HealthHealth Sciences CentreUniversity of Manitoba
FundersCanadian Institutes of Health Research
KeywordsNursingIntegrated careMedicineHealth carePolitical science

Abstract

fetched live from OpenAlex

Introduction: Poor outcomes following the transition from hospital back to community living are common, especially for older adults with complex health and social care needs. Some health care systems now have multiple interprofessional teams (in hospital and community) to support care transitions. These teams will need to be well coordinated to improve care transition outcomes. Methods: We conducted a scoping review to identify and map peer-reviewed literature on how interprofessional teams are working together to support older adults transitioning from hospital back to the community. We used the six-stage framework developed by Levac and colleagues (2010). Procedures were guided by the Joanna Briggs Institute scoping review guidelines. Results: Our structured search and screening process resulted in 70 articles, published between 2000 and 2022, from 14 counties. Within these articles, 26 programs were described that used interprofessional teams in both the hospital and community. Discussion: The qualitative articles suggested that effective teamwork is very important for promoting care transition quality, but the quantitative research did not report on team-related outcomes. Quantitative research has described, but not evaluated, strategies for promoting interprofessional collaboration. Conclusion: Future research should focus on evaluating processes used to promote effective interprofessional teamwork in care transition interventions.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.761
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.006
Insufficient payload (model declined to judge)0.0030.001

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 head0.046
GPT teacher head0.516
Teacher spread0.470 · 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 designOther design
Domainnot available
GenreReview

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

Citations8
Published2024
Admission routes2
Has abstractyes

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