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Record W4412204142 · doi:10.1111/hex.70331

Advancing the Care Experience for Patients Receiving Palliative Care as They Transition From Hospital to Home (ACEPATH): Phase 2 of Codesigning an Intervention to Improve Hospital‐to‐Home Transitions for Patients and Family Caregivers

2025· article· en· W4412204142 on OpenAlexafffundabout
Madeline McCoy, Taylor Shorting, Vinay Kumar Mysore, Edward Fitzgibbon, Jill Rice, Meghan Savigny, Natalie C. Ernecoff, Marianne Weiss, Shirley H. Bush, Daniel Vincent, Meaghen Hagarty, Geneviève Lalumière, Rex Pattison, Mona Kornberg, Maya Stern, Kerry Kuluski, Colleen Webber, Adrianna Bruni, Tara Connolly, Sarina R. Isenberg

Bibliographic record

VenueHealth Expectations · 2025
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsCarleton UniversityInstitute of Health Services and Policy ResearchTrillium Health CentreUniversity of TorontoCanadian Patient Safety InstituteCARE CanadaVancouver Biotech (Canada)Canadian Hospice Palliative Care AssociationInstitute for Work & HealthOttawa HospitalBruyère
FundersCanadian Institutes of Health ResearchCanadian Frailty NetworkUniversity of Ottawa
KeywordsIntervention (counseling)Psychological interventionMedicineNursingPalliative careGeneral partnershipTransitional careFidelityEnd-of-life carePsychologyHealth careFamily medicineComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Although many people nearing the end of life wish to die at home, many patients experience re-hospitalisation and hospital death. No end-of-life hospital-to-home interventions have been developed with patients and caregivers, and none have been tested in Canada. Through an iterative, participatory design approach, we codesigned an intervention in partnership with potential users of the final intervention: patients, family caregivers (FCs) and healthcare providers (HCPs). OBJECTIVE: This study (ACEPATH) aimed to use a patient, FC and HCP engaged codesign process to continue to iterate and refine an intervention for transition from hospital to home in preparation for a pilot implementation. METHODS: The codesign process consisted of: (1) Development of codesign workshop (CDW) materials; (2) CDWs with patients and/or their FCs, who iterated our team's previously developed checklists and reference materials; (3) Low-fidelity prototyping sessions with hospital and community HCPs, who provided feedback on the low-fidelity prototype, the guidebook (that combined the refined checklists and guides) and identified HCPs to facilitate the guidebook; and (4) High-fidelity prototyping sessions entailed simulated interactions between an HCP and a patient/FC using the intervention, accompanied by discussion for feedback. RESULTS: Participants identified several areas for refinement to enhance the relevance, clarity and acceptability of the guidebook intervention. Patients and FCs refined and organised questions into specific 'moments' that would be helpful for conversations with HCPs during their transition home. HCPs identified social workers, hospital home care coordinators and community home care coordinators as the best fit for facilitating completion of the guidebook at three moments (preparing to leave the hospital, immediately before discharge and getting comfortable at home). CONCLUSIONS: We successfully codesigned a guidebook for hospital-to-home transitions that was amenable to patients, FCs and HCPs. The next steps will entail piloting the guidebook to evaluate its acceptability, appropriateness, feasibility, costs and fidelity. PATIENT OR PUBLIC CONTRIBUTION: Patients and FCs who had lived/living experiences with hospital-to-home transitions near the end of life participated in codesign workshops and high-fidelity prototyping sessions. We used codesign to ensure the final intervention was aligned with participants' needs and experiences and would hopefully improve aspects of the hospital-to-home transition that are important to them.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.773

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.032
GPT teacher head0.414
Teacher spread0.383 · 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 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

Citations1
Published2025
Admission routes3
Has abstractyes

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