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Record W4409337725 · doi:10.5334/ijic.9492

A provider experience survey in integrated care. Closing out the quadruple aim

2025· article· en· W4409337725 on OpenAlexaboutno aff
Walter P. Wodchis, Ruth Hall, Shannon L. Sibbald, Jennifer Gutberg, Vijay Kunaratnam

Bibliographic record

VenueInternational Journal of Integrated Care · 2025
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsnot available
Fundersnot available
KeywordsClosing (real estate)Integrated careNursingHealth careMedicinePsychologyBusinessPolitical science

Abstract

fetched live from OpenAlex

Background: Capturing the provider’s experience, delivering care and provider well-being has become a major focus of health system leaders and recognized as the fourth component of the Quadruple Aim. However, tools to measure the experience of provider care are limited, with few examples in integrated care. Existing measurement is both specific to provider types/professional groups or is narrowly focused on teamwork measures. Instruments are needed to assess interprofessional health care providers experience and well-being in the context of integrated care. We sought to develop and test a provider experience scale applicable across provider types and organizations engaged in integrated care models. Approach: A provider experience survey was developed through a three-phase approach. The first phase included a rapid literature review of provider experience surveys and research team consensus meetings to identify thematic areas and candidate items from existing survey tools. The second phase involved 4 focus groups with 16 providers including physicians, therapists, social workers, nurses and community health workers. The third phase was a field test of the survey in 3 health system interventions aimed to advance integrated care. The field test took place with providers in Ontario, Canada in the implementation of population-based integrated care models called Ontario Health Teams. Exploratory factor analysis was used to group items into domains and domain-specific factor scores and reliability was assessed. Results: A 39-item survey was fielded to 2145 respondents with an average 22% response rate and 472 returned surveys. Factor analysis resulted in 5 subscales: 1) care coordination; 2) workplace culture; 3) autonomy; 4) burnout/satisfaction; and 5) digital/virtual care. The internal consistency estimates of reliability of each subscale ranged from 0.72 to 0.94, and overall reliability was 0.82. Conclusions: This provider experience survey addresses gaps important for integrated care in that it was developed and validated with multiple professions and applied in the context of integrated care. Statistical results from an initial survey of 472 respondents in Ontario, Canada suggests strong internal consistency and reliability while engagement with providers in the development of the survey tool provides support for content validity. This tool is publicly available in French and English for integrated care programs to use to assess provider experience as essential outcome of integrated care initiatives. Further testing and refinement of the measure will strengthen the measurement of provider experience in quadruple aim evaluation of integrated care programs.

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)0.014
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 score0.027
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.460
Teacher spread0.419 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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