MétaCan
Menu
Back to cohort
Record W3004991863 · doi:10.12927/hcq.2020.26050

National Patient Safety Consortium: Learning from Large-Scale Collaboration

2020· article· en· W3004991863 on OpenAlexaffvenueabout
Sandi Kossey, Chris Power, Leslee Thomson, Kathleen Morris, Shelagh Maloney, Lee Fairclough, Deborah Prowse, Hina Laeeque

Bibliographic record

VenueHealthcare Quarterly · 2020
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsCanada Health InfowayCanadian Standards AssociationCanadian Institute for Health InformationCanadian Patient Safety Institute
Fundersnot available
KeywordsSAFERPatient safetyAction planBest practiceScale (ratio)Plan (archaeology)Health careAction (physics)BusinessKey (lock)Public relationsNursingMedicineMedical educationPolitical scienceManagementComputer science

Abstract

fetched live from OpenAlex

From 2014 to 2018, the Canadian Patient Safety Institute brought together key partners and established the National Patient Safety Consortium to drive a shared action plan for safer healthcare.With ongoing consensus development on key priorities, an unprecedented level of collaboration and shared leadership with diverse stakeholders and patients and families as full partners, the Consortium and its Integrated Patient Safety Action Plan built a culture of engagement and improvement across Canada. National Leadership through a National Patient Safety ConsortiumEstablished by Health Canada in 2003, the Canadian Patient Safety Institute (CPSI) works with governments, health organizations, leaders, healthcare providers and patients to inspire extraordinary improvement in patient safety and healthcare quality (CPSI 2018).In 2013, CPSI made a commitment to deliver on its original mandate: to establish a national integrated patient safety strategy (Wade et al. 2002).CPSI and its members felt that the climate and the time were right to bring together key stakeholders in Canadian healthcare to focus on some of the biggest patient safety challenges and align their work around common goals.In CPSI's view, it was essential to start with creating a coalition of willing participants, knowing that any effort to drive real change in safety would have to be much bigger than one organization could manage and could not succeed if it were seen to be solely one organization's agenda.It would require commitment from multiple levels and organizations to enable the synergy and coordination needed to accelerate the pace of improvement.Thus, from 2014 to 2018, CPSI and partners established the National Patient Safety Consortium to drive a shared action plan for safer healthcare.The National Patient Safety Consortium was composed of 50 organizations from across Canada that came together around a shared purpose: to drive a shared action plan for safer healthcare for Canadians.Representatives from governments (federal, provincial and territorial), provincial quality and safety organizations and committees (e.g., Health Quality Council of Alberta, Health Quality Ontario, Atlantic Health Quality and Patient Safety Collaborative), pan-Canadian organizations (e.g., Accreditation Canada, Canadian Institute for Health Information, Canada Health Infoway, Mental Health Commission of Canada), healthcare delivery systems (e.g., Alberta Health Services, University Health Network, Health PEI), professional groups (e.g., Canadian Nurses Association, Canadian Medical Protective Association, Canadian Society of Hospital Pharmacists, IPAC Canada) and patient and family partners (e.g., Patients for Patient Safety Canada, Patients Canada) comprised the Consortium.

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)0.164
metaresearch head score (Gemma)0.169
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.164
Threshold uncertainty score0.869

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1640.169
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0270.015
Scholarly communication0.0260.024
Open science0.0070.043
Research integrity0.0090.021
Insufficient payload (model declined to judge)0.0160.006

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 head0.052
GPT teacher head0.399
Teacher spread0.347 · 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

Citations4
Published2020
Admission routes3
Has abstractyes

Explore more

Same venueHealthcare QuarterlySame topicMedical Malpractice and Liability IssuesFrench-language works237,207