The implementation of Safety Management Systems in healthcare: a systematic review and international comparison
Notice bibliographique
Résumé
Background: In health care, errors could have serious consequences for patients and staff. High-risk industries, such as aviation, have improved safety by taking a systems approach, known as safety management systems. Safety management systems are generally considered to have four key components: leadership commitment and safety policy; safety risk management; safety assurance; and safety culture. Safety management systems need to be context-specific to be effective. Evidence on the use of safety management systems in health care is therefore needed to inform policy decisions. Objectives: To investigate the application of safety management systems to patient safety in terms of effectiveness, implementation and experience. Methods: We conducted a systematic review of research and other evidence from high-income countries that have publicly funded healthcare systems with universal coverage and key evidence available in English. We included Australia, Canada, Ireland, New Zealand and the Netherlands. We searched the websites of, and contacted experts from, patient safety organisations in each country, and searched MEDLINE (December 2023) and EMBASE (via Ovid), Cumulative Index to Nursing and Allied Health Literature (EBSCO) and Web of Science (February 2024). We included policy documents, research and other evidence relating to the effectiveness, implementation or experience of the safety approach in each country. We summarised and mapped included evidence onto an initial framework based on analysis of safety management systems in high-risk industries. We shared drafts with experts in each country for comment. No standardised quality appraisal was conducted but those studies evaluating impact were critically examined for risk of bias. Results: Fifty-three publications were included, from Australia (5), Canada (7), Ireland (8), New Zealand (9) and the Netherlands (24). The Netherlands was the only country with a patient safety programme explicitly based on a safety management system approach. The programme was associated with improvement in some aspects of patient safety in hospitals but there was significant variation in its implementation and outcomes. The main components of a safety management system were also identified to some extent in the patient safety approaches of the other four countries, along with evidence of influence from high-risk industries and 'safety science' more widely. Limitations: Although we followed best practice for conducting systematic reviews, some limitations should be acknowledged. We did not conduct formal quality appraisal, but the risk of bias in studies evaluating impact was examined. We also tried to mitigate the risk of partial understanding (from the use of policy documents) by talking to experts from each country. Conclusions: Only the Dutch patient safety programme was explicitly based on a safety management system approach. Concepts from high-risk industries and broader safety science had influenced the patient safety approach in the other countries, and the ongoing approach in the Netherlands, but this was less systematic and explicit. Approaches to patient safety in all countries reflect increasing awareness that for an initiative to be successful, it needs to be context-specific. Future work: Using realist methods to identify mechanisms underpinning the success of different patient safety approaches could allow better understanding of how and to what extent such initiatives work in specific circumstances. Methods for evaluation of impact also require further development to allow better understanding and comparison of different approaches. Study registration: This study is registered as PROSPERO CRD42023487512. Funding: ; Vol. 13, No. 7. See the NIHR Funding and Awards website for further award information.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».