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Record W4402739632 · doi:10.1177/07067437241281068

Virtual Versus In-Person Follow-up After a Psychiatric Emergency Visit: A Population-Based Cohort Study: Suivi virtuel opposé à en personne après une visite à l’urgence psychiatrique : une étude de cohorte dans la population

2024· article· en· W4402739632 on OpenAlexaffvenueabout
Matthew H. Crocker, Anjie Huang, Kinwah Fung, Thérèse A. Stukel, Alène Toulany, Natasha Saunders, Paul Kurdyak, Lucy C. Barker, Tanya S. Hauck, Martin Rotenberg, Emily Hamovitch, Simone N. Vigod

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2024
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsWomen's College HospitalHospital for Sick ChildrenPublic Health OntarioUniversity of TorontoCentre for Addiction and Mental HealthInstitute for Clinical Evaluative Sciences
Fundersnot available
KeywordsPsychiatryCohortMedicinePsychologyPopulation

Abstract

fetched live from OpenAlex

OBJECTIVE: With increased utilization of virtual care in mental health, examining its appropriateness in various clinical scenarios is warranted. This study aimed to compare the risk of adverse psychiatric outcomes following virtual versus in-person mental health follow-up care after a psychiatric emergency department (ED) visit. METHODS: Using population-based health administrative data in Ontario (2021), we identified 28,232 adults discharged from a psychiatric ED visit who had a follow-up mental health visit within 14 days postdischarge. We compared those whose first follow-up visit was virtual (telephone or video) versus in-person on their risk for experiencing either a repeat psychiatric ED visit, psychiatric hospitalization, intentional self-injury, or suicide in the 15-90 days post-ED visit. Cox proportional hazard models generated adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs), adjusted for age, income quintile, psychiatric hospitalization, and intentional self-injury in the 2 years prior to ED visit. We stratified by sex and diagnosis at index ED visits based on the International Classification of Diseases and Related Health Problems, 10th Revision, Canada (ICD-10-CA) coding. RESULTS: = 9,878) were in-person. About 13.9% and 14.6% of the virtual and in-person groups, respectively, experienced the composite outcome, corresponding to incidence rates of 60.9 versus 74.2 per 1000 person-years (aHR 0.95, 95% CI 0.89 to 1.01). Results were similar for individual elements of the composite outcome, when stratifying by sex and index psychiatric diagnosis, when varying exposure (7 days) and outcome periods (60 and 30 days), and comparing "only" virtual versus "any" in-person follow-up during the 14-day follow-up. CONCLUSIONS AND RELEVANCE: These results support virtual care as a modality to increase access to follow-up after an acute care psychiatric encounter across a wide range of diagnoses. Prospective trials to discern whether this is due to the comparable efficacy of virtual and in-person care, or due solely to appropriate patient selection may be warranted.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.074
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.287
Teacher spread0.270 · 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 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

Citations1
Published2024
Admission routes3
Has abstractyes

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