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Effectiveness of Patient Navigation During Transition to Adult Care

2025· article· en· W4407301562 on OpenAlexaffabout
Susan Samuel, Zoya Punjwani, Daniella San Martin-Feeney, Brooke Allemang, Gregory M.T. Guilcher, Eddy Lang, Danièle Pacaud, Jorge Pinzon, Gail Andrew, Lonnie Zwaigenbaum, Claire Perrott, John Roger Andersen, Lorraine Hamiwka, Alberto Nettel‐Aguirre, Scott Klarenbach, Kerry McBrien, Shannon D. Scott, Megan Patton, Sophie Samborn, Ken Pfister, Laurel Ryan, Gina Dimitropoulos, Andrew S. Mackie

Bibliographic record

VenueJAMA Pediatrics · 2025
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsStollery Children's HospitalUniversity of CalgaryGlenrose Rehabilitation HospitalInstitute for Clinical Evaluative SciencesAlberta Children's HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicinePsychological interventionHealth careEmergency departmentRandomized controlled trialPopulationMental healthYoung adultFamily medicineGerontologyNursingPsychiatryEnvironmental health

Abstract

fetched live from OpenAlex

Importance: Transition to adult care is a challenging and complex process for youth and emerging adults with chronic health and/or mental health conditions. Patient navigation has been proposed to improve care during transition, but previous studies have used single disease cohorts with a nonrandomized design. Objective: To compare the effectiveness of a patient navigator service to reduce emergency department (ED) use among adolescents and emerging adults with chronic health and/or mental health conditions undergoing transition to adult-oriented health care. Design, Setting, and Participants: This was a pragmatic, parallel-group, nonblinded randomized clinical trial design. Patients were followed up for a minimum 12 months and maximum 24 months after enrollment. The setting was the Canadian province of Alberta, with a population of 4.3 million inhabitants, having 3 tertiary care pediatric hospitals serving the entire population with universal health coverage. Participants included youth aged 16 to 21 years, followed up within a diverse array of chronic care clinics, expected to be transferred to adult care within 12 months, residing in Alberta, Canada. Interventions: A 1:1 allocation to either access to a personalized navigator, an experienced social worker within the health services environment, or usual care, for up to 24 months after randomization. Main Outcomes and Measures: All-cause ED visit rate while under observation. Results: A total of 335 participants were randomized over a period of 45 months, 164 (49.0%) to the intervention arm and 171 (51.0%) to usual care. After 1 patient withdrew, 334 participants (usual care: mean [SD] age, 17.8 [0.7] years; 99 female [57.9%]; intervention: mean [SD] age, 17.7 [0.6] years; 81 male [49.7%]) were included in the final data analysis. Among the participants, 131 (39.2%) resided in a rural location, and 126 (37.7%) had a self-reported mental health comorbidity during baseline assessment. We observed significant effect modification in the relationship between intervention and ED visits based on mental health comorbidity. Among those with a self-reported mental health condition, ED visit rates were lower in those with access to the navigator, but the association was not significant (adjusted incidence rate ratio [IRR] 0.75; 95% CI, 0.47-1.19). Among those with no mental health comorbidity, the corresponding adjusted IRR was 1.45 (95% CI, 0.95-2.20). Conclusions and Relevance: In this randomized clinical trial, the navigator intervention was not associated with a significant reduction in ED visits among youth with chronic health conditions transitioning to adult care. The study did not accrue sufficient sample size to demonstrate a significant difference between groups should it exist. Trial Registration: ClinicalTrials.gov Identifier: NCT03342495.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.553

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.011
GPT teacher head0.358
Teacher spread0.347 · 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 designObservational
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

Citations8
Published2025
Admission routes2
Has abstractyes

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