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Record W2801054474 · doi:10.1186/s13012-018-0745-6

Impact of patient involvement on clinical practice guideline development: a parallel group study

2018· article· en· W2801054474 on OpenAlexaff
Melissa J. Armstrong, C. Daniel Mullins, Gary Gronseth, Anna R. Gagliardi

Bibliographic record

VenueImplementation Science · 2018
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversity Health Network
FundersNational Institute on AgingAgency for Healthcare Research and QualityUniversity of Florida
KeywordsGuidelineMedicinePublic healthFamily medicineNursingPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Patient and public involvement (PPI) is recognized as a key component of clinical practice guideline development with important implications for guideline implementability. The impact of PPI on guidelines, however, has not been rigorously assessed. Better understanding of the impact of PPI must start with guideline question formation, which drives all subsequent development steps. The aim of this study was to investigate the effect of PPI on guideline question formation and validate a conceptual model of patient and public contributions to guidelines. METHODS: For development of a clinical practice guideline on the topic of using amyloid positron emission tomography in the diagnosis of dementia, we convened two parallel guideline development groups, one with and one without patient representatives. Participating physicians were randomized to group assignment. Each group developed Population, Intervention, Comparator, Outcome, Time (PICOT) questions and identified key benefits and harms to incorporate in guideline development. Analysis included a descriptive comparison of proposed PICOT questions, benefits, and harms between groups and a qualitative analysis of discussion themes from audio recordings of the question development retreats. RESULTS: Proposed guideline questions, benefits, and harms were largely similar between groups, but only the experimental group proposed outcomes relating to development of cognitive impairment at specific time points and rate of progression. The qualitative analysis of the discussions occurring during guideline question development demonstrated key differences in group conduct and validated the proposed conceptual model of patient and public contributions to guidelines. PPI influenced the conduct of guideline development, scope, inclusion of patient-relevant topics, outcome selection, and planned approaches to recommendation development, implementation, and dissemination with implications for both guideline developers and the guideline development process. CONCLUSIONS: Evidence of how PPI impacts guideline development underscores the importance of engaging patient stakeholders in guideline development and highlights developer- and guideline-specific outcomes of PPI, both of which have implications for guideline implementation. It also raises the question of whether guidelines developed without such input are acceptable for use. PPI should be considered an essential element of trustworthy guideline development for purposes of development and funding.

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)0.060
metaresearch head score (Gemma)0.164
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.940
Threshold uncertainty score0.318

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0600.164
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0020.002
Science and technology studies0.0050.005
Scholarly communication0.0030.005
Open science0.0020.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.540
GPT teacher head0.664
Teacher spread0.123 · 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.

Study designObservational
DomainMethods
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

Citations209
Published2018
Admission routes1
Has abstractyes

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