The implementation of Safety Management Systems in healthcare: a systematic review and international comparison
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".