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Record W4413365888 · doi:10.5334/ijic.nacic24056

Developing a Patient Reported Experience Measure (PREM) to assess patients’ experiences with care transitions and integration

2025· article· en· W4413365888 on OpenAlexaboutno aff
Sarah Filiatreault, Jodi Cullum, Ceara Cunningham, Staci Hastings, Judy Seidel, Sara N. Davison

Bibliographic record

VenueInternational Journal of Integrated Care · 2025
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMeasure (data warehouse)MedicineIntegrated careNursingHealth carePsychologyComputer science

Abstract

fetched live from OpenAlex

Background: Care transitions (CTs) across the care continuum (e.g., hospital to primary care/community), especially for those with complex care needs and multimorbidity, is an important focus for improvement. Complex patients in particular tend to be at higher risk for adverse events such as medication errors and rehospitalization due to poor discharge coordination and communication. Primary care plays a significant role in improving coordination and communication to support successful transitions in care. An ongoing study in Alberta, Canada called A DiseAse-Inclusive Pathway for Transitions in Care (ADAPT) focuses on integrating care by collaborating with Primary Care Providers to enhance CTs. Alberta Health Service (AHS) Primary Health Care Integration Network (PHCIN) has been leading the development of the Home to Hospital to Home (H2H2H) Transitions Guideline for several years. A major aspect of this initiative is evaluating how patients experience transitions from hospital to home. There are few validated patient reported experience measures (PREMs) that capture multiple transition points from discharge preparation, to home, to primary care. The objective of this work was to develop a PREM to capture patients experience of care while transitioning across multiple settings, with a focus on integration of care across. Approach: Methods to achieve our objective included a literature review, identification of core domains and questions across clinical settings, and then pre-testing the instrument with content experts and patients/caregivers with lived experience to establish content and face validity. After iterative pre-testing and revisions, we plan to pilot the newly developed PREM in one site prior to broader application. Psychometric testing of the PREM will be done as part of the larger study which will also explore strategies to bolster response rates from patients involved in this study aimed at improving CTs for adult patients with diverse chronic conditions and better integrating their care. Results: The literature review identified 3 potentially relevant PREM instruments. Criteria for inclusion in the review were an adult patient population, and relevance to transitions in care between hospital and primary care settings. Core domains of interest were superimposed onto PREM items, including patient knowledge, self-efficacy, care preference alignment, integration/coordination, and satisfaction throughout CTs. Existing PREMs were limited in capturing the patient experience as they transitioned through different levels of care. Items for the new PREM were developed to ensure representation of core domains of interest for CTs from hospital to home, including integration with primary care in the post-discharge period. The PREM is currently undergoing pre-testing with patient advisors (n = 5) and content experts (n = 5). Once pre-testing and revisions are complete the PREM will be applied in a small pilot, and then in the implementation evaluation of a provincial transitions in care initiative, i.e., the H2H2H Guideline. Implications: Creating an instrument that captures patient experiences as they move between acute and primary care, with a focus on integrating care will be key to gaining understanding and improving CTs. The development of a PREM to evaluate across levels of care will better inform various interest groups on how different system changes impact the patient experience. This approach to a PREM instrument also reinforces the importance of viewing the patient experience in a more integrated manner rather than in components.There are few validated PREMs in Canada, or elsewhere, that capture patient experiences throughout the transition process across the continuum of care from hospital to home. The PREM we are developing would be applicable to applied research and learning health organizations across Canada given the current gap in this area. The PREM will provide robust evidence to assess patient experience metrics to support quality improvement work and enhance integration of care.

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)0.010
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
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 head0.058
GPT teacher head0.413
Teacher spread0.355 · 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 designBench or experimental
Domainnot available
GenreMethods

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
Published2025
Admission routes1
Has abstractyes

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