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Record W4391874446 · doi:10.1093/jcag/gwad061.092

A92 THE CURRENT STATE OF PEDIATRIC TO ADULT TRANSITION OF CARE: A ROUND TABLE DISCUSSION WITH KEY STAKEHOLDER GROUPS

2024· article· en· W4391874446 on OpenAlexaff
Ming Hu, Natasha Gakhal, C Kabakulak, Jordan LoMonaco, Natasha Bollegala

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2024
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsKey (lock)Round tableStakeholderState (computer science)Transition (genetics)Table (database)Current (fluid)MedicineProcess managementPolitical scienceBusinessComputer sciencePublic relationsEngineeringData miningWorld Wide WebComputer securityChemistry

Abstract

fetched live from OpenAlex

Abstract Background There is a severe paucity in available resources to facilitate a safe and effective pediatric to adult health care transition for patients with chronic disease. Aims This study aims to better understand the experiences of key stakeholder groups involved in pediatric to adult transition of care across various chronic disease specialties within a tertiary care urban environment. Methods A focus group was conducted on July 12th, 2018 at Women’s College Hospital with key stakeholder groups. Questions focused on the top issues related to pediatric to adult transition of care and an ideal transition model for their respective patient populations. The second part of this study included individual interviews with patients and carepartners. Focus group meetings and individual interviews were both audio-recorded and transcribed for qualitative thematic analysis. Results Seventeen pediatric and adult care physicians representing ten chronic disease specialties were represented. Seven patients and care partners were interviewed. Major focus group themes included: disproportionate access to resources between and within specialties (n=10), lack of mental health support in the adult setting (n=8), fragmentation of care due to multiple providers as a result of patients leaving for employment or education (n=6), patients feeling alienated due to decrease in allied health support or due to shorter appointment times (n=8), and difficulty retaining consistent care due to missed appointments as a result of inconsistent communications or change in location for education or employment (n=7). Ideal care models were suggested to include: centralized intake procedure to identify patients who may require extra support (n=9), education for scheduling administrators about second chances after a no-show (n=5), implementation of joint clinics with pediatric and adult care teams or back-and-forth clinic sessions to ensure bidirectional provider comfort before discharge to adult care system (n=4), and implementation of a dedicated transitions navigator or point of contact for patients (n=10). The individual patient and carepartner interviews emphasized the need for: centralized and comprehensive online resource (n=7), simple and clear educational content introducing the adult healthcare system (n=7), opportunities to meet and share information with other individuals in a similar position (n=3), and availability of a transitions navigator (n=4). Conclusions Current pediatric to adult transition of care resources are fragmented, allocated inefficiently, difficult to ascertain and often constrained to a specific condition or location. Future efforts should focus on improving the care transition process for high-risk patient populations by taking a comprehensive approach utilizing innovative, and multidisciplinary solutions. Funding Agencies None

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)0.054
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.286

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0540.040
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0270.010
Scholarly communication0.0090.014
Open science0.0040.015
Research integrity0.0070.012
Insufficient payload (model declined to judge)0.0070.001

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 head0.026
GPT teacher head0.314
Teacher spread0.287 · 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 designQualitative
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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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