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Record W4415222248 · doi:10.1093/ijcoms/lyaf010

More than just a voice: how the OECD’s Patient-Reported Indicator Surveys (PaRIS) Patient Advisory Panel drives action and results

2025· article· en· W4415222248 on OpenAlexaffabout
Rebecca Barlow-Noone, Elizabeth Deveny, Cajsa Lindberg, Cristina Parsons Perez, Yann Heyer, Dani Mothci, Kent Cadogan Loftsgard

Bibliographic record

VenueIJQHC Communications · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsCanadian Patient Safety InstituteCanadian Institutes of Health Research
Fundersnot available
KeywordsAction (physics)Government (linguistics)Data collectionWork (physics)

Abstract

fetched live from OpenAlex

More than just a voice 2 How the PaRIS Patient Advisory Panel drives action and results with the OECD's 3 Patient-Reported Indicator Surveys (PaRIS)person's day-to-day self-care, and it offers continuity and a whole-person view that specialist services often 8 lack.This makes it essential for delivering coordinated, people-centred care.9 Yet, until recently, the lived experiences of people with chronic conditions in primary care have not been 10 captured in a consistent, international way.Health systems are often evaluated by workforce numbers or 11 clinical indicators, not by how patients experience care.Even when collected, patient-reported data is 12 sometimes seen as secondary.13 Key questions remain unanswered: How do people perceive their health?How do outcomes and 14 experiences vary across groups?Which aspects of care matter most?Do patients feel heard?Without 15 comparable international data from the point of view of those experiencing care, an evidence-based, 16 comprehensive perspective has been lacking.17 The OECD's Patient-Reported Indicator Surveys (PaRIS) addresses this gap.It embeds patient 18 involvement into every stage of the survey -design, implementation, and reporting.Over the past seven 19 years, the PaRIS Patient Advisory Panel (PaRIS-PP), made up of representatives from national and 20 international organisations, has shaped this process.While patient involvement in research is growing, 21 most examples remain episodic -tied to specific funding cycles or project timelines.Several countries 22 offer national frameworks for engagement, such as NIHR Involve (UK), SPOR (Canada), NHMRC 23 (Australia), and PCORI (USA).International organisations like the European Organisation for Research 24 and Treatment of Cancer (EORTC) and the International Consortium for Health Outcomes Measurement 25 (ICHOM) also involve patients, but typically focus on clinical research or outcomes measurement, not 26 system-level policy reform.In contrast, the PaRIS Patient Advisory Panel (PaRIS-PP) is embedded in an27international initiative designed to assess and improve primary care across health systems -a rare and 28 important shift.This paper outlines the practical impact of the PaRIS-PP's involvement and its implications 29 for policymakers, practitioners and policy researchers.

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)0.009
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.327
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.432
GPT teacher head0.433
Teacher spread0.001 · 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 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
Published2025
Admission routes2
Has abstractyes

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