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Record W2072077413 · doi:10.1177/0969733013509042

Patient safety and quality in healthcare

2014· editorial· en· W2072077413 on OpenAlexaff
Ebin J Arries

Bibliographic record

VenueNursing Ethics · 2014
Typeeditorial
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPatient safetyHealth careMedicineSAFERNursingBusinessMedical emergencyPublic relationsPolitical scienceComputer security

Abstract

fetched live from OpenAlex

Globally, health systems face constraints and challenges around patient safety and quality, lack of human resources, and rising moral distress among nurses. This concern about the gap in quality and patient safety and the need for improvement was highlighted more than a decade ago in two landmark studies by the Institute of Medicine (IOM): To Err Is Human: Building a Safer Health System and Crossing the Quality Chasm: A New Health System for the 21st Century. These reports were followed by a staggering number of scholarly publications, improvement initiatives, and the establishment of various institutions on patient safety. In 2004, the World Alliance for Patient Safety was launched to advance the goal of patient safety, to coordinate patient safety initiatives globally, and to reduce the impact of unsafe healthcare through a number of systemic programs (e.g. mobilizing patients and organizations for patient safety, addressing taxonomy, research, development, and reporting of learning systems). Additionally, an ad hoc expert group of the Alliance produced a report summarizing the evidence on patient safety, which highlighted structural, process, and outcome gaps in need of further research (e.g. safety culture, organizational determinants, structural accountability, lack of patient involvement in patient safety, adverse events, injuries related to drug treatment, and medical devices). Furthermore, the report highlighted the burden in terms of morbidity and mortality posed by unsafe healthcare globally, lack of available data from developing countries around structural and process factors contributing to unsafe care, and the applicability of data derived predominantly from developed countries to local conditions in developing countries. Recommendations were made for a better understanding of the epidemiology of adverse events and processes contributing to them in developing countries. In nursing, the response from the profession to the call for patient safety and quality has been remarkable. In an evidence-based handbook for nurses, Hughes highlighted nursing’s contributions to patient safety and quality, evidence-based practice, patient-centered care, improvement in working conditions, and the work environment for nurses, and discussed a number of opportunities for further improvement and research. Furthermore, nurses’ continuing contributions span a broad range of initiatives in practice (e.g. patient advocacy and attentiveness training and nurse-led quality improvement), education (e.g. curriculum changes to target core competencies such as evidence-based practice, informatics, and quality improvement), and research using a number of conceptual and empirical methodologies to explicate, analyze, and synthesize data and to implement and evaluate interventions (e.g. nurse-led clinics, tele-health, and care pathways). In addition, nurse leaders and nursing governing bodies responded with a number of position papers, revision of policies and Code of Ethics, and accreditation and regulatory initiatives, to demonstrate the profession’s commitment to patient safety and quality. Although there has been some progress, more still needs to be done.

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)0.033
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.176

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.049
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.005
Science and technology studies0.0060.033
Scholarly communication0.0190.012
Open science0.0020.013
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0120.002

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 head0.226
GPT teacher head0.576
Teacher spread0.350 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations79
Published2014
Admission routes1
Has abstractyes

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