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Record W2102689557 · doi:10.12927/hcq.2014.23951

Improving Safety: Engaging With Patients and Families Makes a Difference!

2014· article· en· W2102689557 on OpenAlexaffabout
Carol Kushner, Donna Davis

Bibliographic record

VenueHealthcare Quarterly · 2014
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsCanadian Patient Safety Institute
Fundersnot available
KeywordsBest practiceNursingBusinessPublic relationsMedicinePsychologyMedical emergencyMedical educationEnvironmental healthPolitical science

Abstract

fetched live from OpenAlex

Following a brief review of the history and context for patient and family member involvement in healthcare safety improvements, a variety of tools and mechanisms for patient engagement will be offered along with specific examples from Patients for Patient Safety Canada (a patientled program of the Canadian Patient Safety Institute) to illustrate the impact of involving patients and family members in safety work.Barriers and facilitators to patient engagement in safety will also be examined. History and ContextPatient safety became an issue of deep concern in Canada when the Baker-Norton Adverse Events Study (Baker et al. 2004) was released a few years after the Institute of Medicine's published To Err Is Human, which established that medical error was between the fourth and eighth leading cause of preventable death in the United States (Kohn et al. 1999).It has now been 10 years since the World Health Organization (WHO) 1 made patient safety a priority in October 2004 and called on the healthcare community to welcome patients and their family members as partners in creating a safer system.The WHO's Patients for Patient Safety (PFPS) program stream was created to support this initiative and the following year, invited a small group of 21 patients and family members who had experienced harm from healthcare to a meeting in London, England.This is where The London Declaration 2 was conceived, and it continues to be used to underpin the commitment and aspirations of PFPS Champions around the world as they work to make the system safer.To become a PFPS Champion, candidates must attend a WHO-approved patient safety workshop, must endorse The London Declaration and must sign an agreement, signifying their willingness to work in collaboration with the health system and its providers.Today there are more than 300 WHO PFPS Champions 3 in more than 50 countries, including 43 in Canada, most of whom are also members of Patients for Patient Safety Canada (PFPSC), a patient-led program of the Canadian Patient Safety Institute (CPSI).The rationale for involving patients and family members in safety work is to recognize that the perspectives of patients and family members may often differ from those who work in the system and can be valuable in planning and implementing safety improvements that are truly patient-and family-centred. Strategies and ToolsOver the past decade, a great deal of work has been done to advance the involvement of patients and families in patient safety work both here in Canada and around the world.In the United States, for example, the Institute for Patient-and Family-Centered Care has developed a package of resources for health organizations wanting to advance patient engagement.This package includes a variety of specific strategies and tools tailored to specific healthcare settings including hospitals, primary care and other ambulatory settings.4 These materials are available for free downloading and provide useful guidance for getting started and expanding and sustaining the work.Other helpful resources are available from the Institute for Healthcare Improvement (IHI), Planetree and the Joint Commission. 5 In Canada, the CPSI has demonstrated a strong commitment to patient engagement since 2006 by providing staff support to help create and sustain PFPSC's volunteer network.CPSI also

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)0.016
metaresearch head score (Gemma)0.023
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 score0.017
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0120.009
Scholarly communication0.0100.017
Open science0.0020.010
Research integrity0.0110.016
Insufficient payload (model declined to judge)0.0170.005

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 head0.029
GPT teacher head0.310
Teacher spread0.281 · 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

Citations3
Published2014
Admission routes2
Has abstractyes

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