This article explores the \'the moment of patient safety\'-the period around 2000 when patient safety became a key policy concern of the British National Health Service (NHS), and other healthcare systems. While harm caused by medical care (iatrogenic injury) had long been acknowledged by clinicians and scientists, from 2000 a new systemic language of patient safety emerged in the NHS that promoted novel managerial and regulatory approaches to patient harm. This language reflected the state\'s increasing role in regulating healthcare, as well as the erosion of medical autonomy and the rise of new forms of bureaucratic management. Acknowledging a transnational, intellectual context behind the rise of policy interest in patient safety-for example, the application of insights from the industrial safety sciences-this article examines the role played by domestic cultural factors, such as medical negligence litigation and healthcare scandals, in helping to define the new language in Britain.

UNASSIGNED: Debriefing improves care and reduces error. To be effective, debriefs should be facilitated by trained individuals utilising structured and validated tools. Currently, in UK ambulance services there is no published evidence that structured processes utilising validated tools are being consistently delivered by trained facilitators, potentially impacting clinical practice.
UNASSIGNED: A pre-intervention survey related to debriefing was sent to 1000 clinicians within a specific geographical area of the trust via e-mail. In addition, 12 senior or advanced paramedics were recruited from the same area to participate in a training day and 12-week trial, utilising the Debrief Diamond as part of post-event debriefing. Following the trial period, all facilitators and participants of any recorded debriefs were invited to complete a post-intervention survey.
UNASSIGNED: A total of 130 staff responded to the pre-intervention survey, with 22% reporting that previous debriefs had not identified areas for learning, and 13% reporting that previous debriefs had not identified good practice, learning opportunities or near misses. Post-intervention, 89% believed the process of debriefing was improved utilising a structured framework, 85% stated trained individuals improved the process, 93% reported the identification of good practice, 70% identified team level learning and 100% of facilitators reported improvements in identifying and supporting learning.
UNASSIGNED: Improvements in identifying good practice and learning opportunities were reported by both clinicians and facilitators in this evaluation, reflecting current evidence that structured and facilitated debriefs support safer care through the identification and subsequent reduction of human error. Consequently, the evaluation of appropriate debrief frameworks to provide consistency and validity to clinical debriefs in the pre-hospital environment should be considered to support safer clinical care.

BACKGROUND: Artificial intelligence (AI) provides opportunities to identify the health risks of patients and thus influence patient safety outcomes.
OBJECTIVE: The purpose of this systematic literature review was to identify and analyze quantitative studies utilizing or integrating AI to address and report clinical-level patient safety outcomes.
METHODS: We restricted our search to the PubMed, PubMed Central, and Web of Science databases to retrieve research articles published in English between January 2009 and August 2019. We focused on quantitative studies that reported positive, negative, or intermediate changes in patient safety outcomes using AI apps, specifically those based on machine-learning algorithms and natural language processing. Quantitative studies reporting only AI performance but not its influence on patient safety outcomes were excluded from further review.
RESULTS: We identified 53 eligible studies, which were summarized concerning their patient safety subcategories, the most frequently used AI, and reported performance metrics. Recognized safety subcategories were clinical alarms (n=9; mainly based on decision tree models), clinical reports (n=21; based on support vector machine models), and drug safety (n=23; mainly based on decision tree models). Analysis of these 53 studies also identified two essential findings: (1) the lack of a standardized benchmark and (2) heterogeneity in AI reporting.
CONCLUSIONS: This systematic review indicates that AI-enabled decision support systems, when implemented correctly, can aid in enhancing patient safety by improving error detection, patient stratification, and drug management. Future work is still needed for robust validation of these systems in prospective and real-world clinical environments to understand how well AI can predict safety outcomes in health care settings.

Clinical negligence claims are on the rise, with lawyers often playing a leading part in ascertaining what went wrong, why it went wrong and what lessons can be learned. I present a schema which may help lawyers better understand what goes wrong in clinical negligence cases.

BACKGROUND: Cognitive bias is an important source of diagnostic error yet is a challenging area to understand and teach. Our aim was to determine whether a cognitive forcing tool can reduce the rates of error in clinical decision making. A secondary objective was to understand the process by which this effect might occur.
METHODS: We hypothesised that using a cognitive forcing tool would reduce diagnostic error rates. To test this hypothesis, a novel online case-based approach was used to conduct a single blinded randomized clinical trial conducted from January 2017 to September 2018. In addition, a qualitative series of \"think aloud\" interviews were conducted with 20 doctors from a UK teaching hospital in 2018. The primary outcome was the diagnostic error rate when solving bias inducing clinical vignettes. A volunteer sample of medical professionals from across the UK, Republic of Ireland and North America. They ranged in seniority from medical student to Attending Physician.
RESULTS: Seventy six participants were included in the study. The data showed doctors of all grades routinely made errors related to cognitive bias. There was no difference in error rates between groups (mean 2.8 cases correct in intervention vs 3.1 in control group, 95% CI -0.94 - 0.45 P = 0.49). The qualitative protocol revealed that the cognitive forcing strategy was well received and a produced a subjectively positive impact on doctors\' accuracy and thoughtfulness in clinical cases.
CONCLUSIONS: The quantitative data failed to show an improvement in accuracy despite a positive qualitative experience. There is insufficient evidence to recommend this tool in clinical practice, however the qualitative data suggests such an approach has some merit and face validity to users.

Adverse events (incidents that harm a patient) can also produce emotional hardship for the professionals involved (second victims). Although a few international pioneering programs exist that aim to facilitate the recovery of the second victim, there are no known initiatives that aim to raise awareness in the professional community about this issue and prevent the situation from worsening.
The aim of this study was to design and evaluate an online program directed at frontline hospital and primary care health professionals that raises awareness and provides information about the second victim phenomenon.
The design of the Mitigating Impact in Second Victims (MISE) online program was based on a literature review, and its contents were selected by a group of 15 experts on patient safety with experience in both clinical and academic settings. The website hosting MISE was subjected to an accreditation process by an external quality agency that specializes in evaluating health websites. The MISE structure and content were evaluated by 26 patient safety managers at hospitals and within primary care in addition to 266 frontline health care professionals who followed the program, taking into account its comprehension, usefulness of the information, and general adequacy. Finally, the amount of knowledge gained from the program was assessed with three objective measures (pre- and posttest design).
The website earned Advanced Accreditation for health websites after fulfilling required standards. The comprehension and practical value of the MISE content were positively assessed by 88% (23/26) and 92% (24/26) of patient safety managers, respectively. MISE was positively evaluated by health care professionals, who awarded it 8.8 points out of a maximum 10. Users who finished MISE improved their knowledge on patient safety terminology, prevalence and impact of adverse events and clinical errors, second victim support models, and recommended actions following a severe adverse event (P<.001).
The MISE program differs from existing intervention initiatives by its preventive nature in relation to the second victim phenomenon. Its online nature makes it an easily accessible tool for the professional community. This program has shown to increase user\'s knowledge on this issue and it helps them correct their approach. Furthermore, it is one of the first initiatives to attempt to bring the second victim phenomenon closer to primary care.

BACKGROUND: Obstetrics remains the largest medico-legal liability in healthcare. Neither an increasing awareness of patient safety nor a long tradition of reporting obstetric outcomes have reduced either rates of medical error or obstetric litigation. International debate continues about the best approaches to measuring and improving patient safety. In this study, we set out to assess the feasibility and utility of measuring the process of maternity care provision rather than care outcomes.
OBJECTIVE: To report the development, application and results of a tool designed to measure the process of maternity care.
METHODS: A dedicated audit tool was developed, informed by local, national and international standards guiding best practice and then applied to a convenience sample of individual healthcare records as proof of function. Omissions of care were rated in order of severity (low, medium or high) based on the likelihood of serious consequences on patient safety and outcome.
RESULTS: The rate of high severity omissions of care was less that 2%. However, overall rates of all omissions varied from 0 to 99%, highlighting key areas for clinical practice improvement.
CONCLUSIONS: Measuring process of care provision, rather than pregnancy outcomes, is feasible and insightful, effectively identifying gaps in care provision and affording opportunities for targeted care improvement. This approach to improving patient safety, and potentially reducing litigation burden, promises to be a useful adjunct to the measurement of outcomes.