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Record W3187789380 · doi:10.2147/copd.s313498

CONQUEST Quality Standards: For the Collaboration on Quality Improvement Initiative for Achieving Excellence in Standards of COPD Care

2021· article· en· W3187789380 on OpenAlexfundno aff
Rachel Pullen, Marc Miravitlles, Anita Sharma, Dave Singh, Fernando J. Martínez, John R. Hurst, Luís Alves, Mark Dransfield, Rongchang Chen, Shigeo Muro, Tonya Winders, Christopher Blango, Hana Muellerova, Frank Trudo, Paul Dorinsky, Marianna Alacqua, Tamsin Morris, Victoria Carter, Amy Couper, Rupert Jones, Κonstantinos Κostikas, Ruth Murray, David Price

Bibliographic record

VenueInternational Journal of COPD · 2021
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsnot available
FundersSanofi GenzymeNovartis PharmaRegeneron PharmaceuticalsMylanNational Institutes of HealthEfficacy and Mechanism Evaluation ProgrammeOtsuka PharmaceuticalEisaiAstellas PharmaBoston Scientific CorporationU.S. Department of DefenseKyorin PharmaceuticalSanofiBiogenYork UniversityRespiratory Effectiveness GroupAstraZenecaDartmouth CollegeAKL Research and DevelopmentMeiji Seika PharmaAmerican Thoracic SocietyNovartis Pharmaceuticals CorporationGlaxoSmithKlineGenentechVeracyteTeva Pharmaceutical IndustriesGilead Sciences
KeywordsExcellenceCONQUESTQuality (philosophy)Quality managementCenter of excellenceBusinessMedicinePolitical scienceMarketingHistoryPhilosophy

Abstract

fetched live from OpenAlex

Background: Chronic obstructive pulmonary disease (COPD) are managed predominantly in primary care. However, key opportunities to optimize treatment are often not realized due to unrecognized disease and delayed implementation of appropriate interventions for both diagnosed and undiagnosed individuals. The COllaboratioN on QUality improvement initiative for achieving Excellence in STandards of COPD care (CONQUEST) is the first-of-its-kind, collaborative, interventional COPD registry. It comprises an integrated quality improvement program focusing on patients (diagnosed and undiagnosed) at a modifiable and higher risk of COPD exacerbations. The first step in CONQUEST was the development of quality standards (QS). The QS will be imbedded in routine primary and secondary care, and are designed to drive patient-centered, targeted, risk-based assessment and management optimization. Our aim is to provide an overview of the CONQUEST QS, including how they were developed, as well as the rationale for, and evidence to support, their inclusion in healthcare systems. Methods: The QS were developed (between November 2019 and December 2020) by the CONQUEST Global Steering Committee, including 11 internationally recognized experts with a specialty and research focus in COPD. The process included an extensive literature review, generation of QS draft wording, three iterative rounds of review, and consensus. Results: Four QS were developed: 1) identification of COPD target population, 2) assessment of disease and quantification of future risk, 3) non-pharmacological and pharmacological intervention, and 4) appropriate follow-up. Each QS is followed by a rationale statement and a summary of current guidelines and research evidence relating to the standard and its components. Conclusion: The CONQUEST QS represent an important step in our aim to improve care for patients with COPD in primary and secondary care. They will help to transform the patient journey, by encouraging early intervention to identify, assess, optimally manage and followup COPD patients with modifiable high risk of future exacerbations.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.428
Threshold uncertainty score0.889

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
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 head0.044
GPT teacher head0.436
Teacher spread0.393 · 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

Citations26
Published2021
Admission routes1
Has abstractyes

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