Background

Natural hazards, such as earthquakes, pose a significant risk to both the public and healthcare professionals, jeopardising patient safety due to the disruption of healthcare systems and services. This study aimed to explore the lived experiences of healthcare professionals concerning patient safety during natural hazards, specifically earthquakes.

Methods

Employing a descriptive phenomenological approach, the study followed the Consolidated Criteria for Reporting Qualitative Research guidelines. 23 participants, including doctors, nurses and paramedics, were interviewed using purposive sampling. Data were gathered through semistructured interviews, which were audio recorded and transcribed. Ethical approval was obtained, and Colaizzi’s method was used for data analysis, with findings validated through researcher consensus and participant feedback.

Results

Nine overarching themes emerged, such as the emotional toll of communication breakdowns, struggles with patient identification, stress due to resource scarcity, operational chaos, ethical dilemmas and psychological impacts on both patients and staff. The study found that these factors collectively influenced patient safety during the earthquake.

Conclusion

The emotional strain caused by communication failures, patient identification issues and resource shortages compounded the challenges of providing safe care during the earthquake. Strengthening disaster preparedness through improved communication systems, resource management, psychological support, interagency coordination and regular realistic disaster drills is essential for safeguarding patient safety in future disasters.

Importance

Patients with poor glycaemic control have a high risk for major cardiovascular events. Improving glycaemic monitoring in patients with diabetes can improve morbidity and mortality.

Objective

To assess the effectiveness of a patient portal message in prompting patients with poorly controlled diabetes without a recent glycated haemoglobin (HbA1c) result to have their HbA1c repeated.

Design

A pragmatic, randomised clinical trial.

Setting

A large academic health system consisting of over 350 ambulatory practices.

Participants

Patients who had an HbA1c greater than 10% who had not had a repeat HbA1c in the prior 6 months.

Exposures

A single electronic health record (EHR)-based patient portal message to prompt patients to have a repeat HbA1c test versus usual care.

Main outcomes

The primary outcome was a follow-up HbA1c test result within 90 days of randomisation.

Results

The study included 2573 patients with a mean (SD) HbA1c of 11.2%. Among 1317 patients in the intervention group, 24.2% had follow-up HbA1c tests completed within 90 days, versus 21.1% of 1256 patients in the control group (p=0.07). Patients in the intervention group were more likely to log into the patient portal within 60 days as compared with the control group (61.2% vs 52.3%, p<0.001).

Conclusions

Among patients with poorly controlled diabetes and no recent HbA1c result, a brief patient portal message did not significantly increase follow-up testing but did increase patient engagement with the patient portal. Automated patient messages could be considered as a part of multipronged efforts to involve patients in their diabetes care.

Objective

Overconfidence is an important source of medical error. This review analyses experimental studies of confidence in medical diagnosis to identify factors affecting clinicians’ confidence in their diagnoses and how confidence impacts patient care.

Method

A scoping review of medical and psychological literature was conducted. Articles were categorised according to methodology and clinical specialty. Findings were analysed thematically. Our review methodology adheres to the JBI’s Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist.

Data sources

We searched SCOPUS, MEDLINE, PsycINFO and Global Health. We then performed citation tracking within these papers’ references to identify additional articles.

Eligibility criteria

Papers were included if they reported quantitative results from an empirical study in which participants reported their confidence or certainty during a diagnostic decision. Studies comprised several medical subdisciplines.

Results

77 articles met the inclusion criteria. Across these articles, confidence was not found to be well-calibrated to true diagnostic accuracy regardless of clinician experience. We organised articles under two main themes: the determinants of confidence and the uses of confidence during the patient’s care pathway. Confidence is found to be affected by several factors, including case complexity, early diagnostic differentials and the healthcare environment. Factors that affect confidence, but not accuracy, demonstrate how the two can become decoupled, resulting in overconfidence/underconfidence. Confidence is found to affect patient testing, medication administration and referral rates, among other clinical actions.

Conclusions

Improving the calibration of confidence should be a priority for medical education and clinical practice (eg, via decision aids). We propose a theoretical model of factors that affect diagnostic confidence/certainty. Such a model can inform future work on how appropriate diagnostic confidence can be prompted and communicated among clinicians.

Statistical process control (SPC) charts provide a natural approach to analysing time series data for healthcare quality improvement (QI) initiatives. A problem arising in practice is that having established baseline control limits, there is no accepted objective and transparent approach to deciding when to establish new control limits for a given chart. We present the Stable Shift Algorithm, a new algorithm to aid analysts by identifying when control limits should be re-established, partitioning a control chart of time series data into distinct time periods. The algorithm aims to achieve this while (1) using only the theory of SPC, familiar to many QI practitioners, (2) avoiding re-establishing limits prematurely and (3) remaining flexible to choice of basic parameters of typical control chart use in QI. This is achieved through the commonly used shift rule of control charts, applied to establish whether shifts warrant new control limits or not. We conducted a simulation study to evaluate the effectiveness of the algorithm in achieving its aims, and a case study demonstrating application of the algorithm to 557 time series of accident and emergency care measures for providers in England and Scotland. Simulation results show that the algorithm avoids premature re-establishment of limits more often than simply re-establishing at every shift rule break. Application of the algorithm to the accident and emergency measures demonstrates this is not achieved at the cost of excessive additional rule breaks that might indicate control limits do not represent the underlying process. The Stable Shift Algorithm offers a potentially highly valuable tool for QI practitioners and researchers undertaking SPC analyses, providing an automated, consistent and rigorous approach facilitating large-scale analyses.

Introduction

The role of quality and safety professionals and leaders in realising the potential and managing the risks of artificial intelligence (AI) tools has not been well defined. We suggest these leaders focus on three areas: using quality, safety and implementation sciences to increase the likelihood of beneficial AI adoption; using AI to enhance and support the methods of quality and safety management; and serving as experts and champions for AI tool use that promotes health and equity (figure 1).

Background and approach

We used 90-day research and development cycles1 to examine AI topics and the role of quality and safety leaders with respect to AI integration, including applying AI tools for quality improvement (QI) use cases,2 the broad application of AI in quality management systems, the implications of AI for patient safety3 and the use of AI...

Trividia recommends that device users who receive an E-5 error code and are experiencing symptoms of high glucose should seek medical care immediately  

Medline updates use instructions for Electronic Homecare Beds due to risk of electrical fires and entrapment.

AirLife is removing Broselow Rainbow Tapes due to incorrectly printed medication dosing information.

FT. LAUDERDALE, FL) – February 6, 2026 – Trividia Health, Inc., announced today that it is initiating a labeling correction which requires a modification of the Owner’s Booklets/System Instructions for Use for all TRUE METRIX, TRUE METRIX AIR, TRUE METRIX GO, and TRUE METRIX PRO Blood Glucose Monit

MedTech/CERENOVUS is removing CEREPAK Detachable Coil Systems due to a higher than expected failure to detach rate

Certain Abbott Diabetes Care Continuous Glucose Monitor sensors may incorrect or lower than actual glucose readings

Certain Abbott Diabetes Care Continuous Glucose Monitor sensors may incorrect or lower than actual glucose readings

FDA is alerting health care providers and lab staff of reports of false positives when using certain Micro Capillary Blood Collection tubes with the LeadCare Testing Systems.

The differential pressure sensor in certain Impella devices may malfunction and cause sensor values to drift.

Olympus is removing certain High Flow Insufflation Unit models due to software issues that may lead to overpressure events.

Integra is removing all MediHoney Wound and Burn products and certain lots of CVS Wound Gel that may have breached sterile barriers

Despite decades of progress in global child health, neonatal mortality remains high, accounting for nearly half of all under-five deaths worldwide.1 Most of these deaths occur in low- and middle-income countries and are preventable with timely, high-quality care for small and sick newborns.2 The WHO has called for every newborn to receive essential, high-impact interventions,3 yet the challenge lies not only in knowing what works, but in implementing those interventions at scale, with quality, and within real-world health systems. Quality improvement (QI) and implementation science (IS) offer complementary strategies to address this challenge. QI focuses on local, iterative problem solving to adapt and improve evidence-based or locally generated care processes,4 5 while IS provides structured, theory-driven methods to promote their uptake and sustainability.6 7 Yet too often, these fields operate independently rather than in a...

The number of complaints received by healthcare organisations from patients and families is on an upward trajectory.1 For example, in 2023–2024, the NHS in England received 241 922 complaints,2 an increase of 5% on the previous year and 37% since 2013–2014. Moreover, while relatively few NHS patient encounters result in a formal complaint (approximately 0.4%), just 9% of patients who report poor healthcare experiences actually submit one.3

Although the motivation for complainants can vary—for instance, some patients seek redress, and others want resolution of ongoing problems—they nearly always request organisational learning.4 Furthermore, while complaints can be incorrect or ill-intentioned, leading to concerns about their validity,5 the collective scale of the information they provide is hard to dismiss. They are, in effect, a massive rolling compendium of ethnographies from patients and families at the sharp end of treatment delivery, revealing perceived...

Background

Improving small and sick newborn care (SSNC) is crucial in resource-limited settings. Newborn Essential Solutions and Technologies (NEST360), a multicountry alliance, aims to reduce newborn mortality through evidence-based interventions. NEST360 developed a multipronged approach to improving quality. We use implementation research (IR) to describe this approach and report emerging implementation outcomes.

Methods

The implementation research logic model (IRLM) was applied to link contextual factors, implementation strategies, mechanisms and implementation outcomes, capturing successes and challenges of the improving quality approach. Data sources included programme data, peer-reviewed publications and team input. Contextual factors were organised by the NEST360-UNICEF SSNC implementation toolkit. Strategies were grouped by the Expert Recommendations for Implementation Change list, and implementation outcomes were measured using Proctor’s implementation outcomes.

Results

We developed an IRLM to describe the implementation of NEST360’s improving quality model. This IRLM included 33 contextual factors; 42% were barriers, 42% were facilitators, and 15% were both a barrier and facilitator. Additionally, we identified 10 implementation strategies that NEST360 used. The logic model also describes the connections between the contextual factors, the strategies that address them, and the preliminary implementation outcomes. Examples of the outcomes measured include Reach with 100% of units logging into the NEST360-Implementation Tracker (NEST-IT) at least once (October 2023 to March 2024), Adoption with 100% of units conducting a quality improvement (QI) project (April 2024 to June 2024), and Feasibility with 93% of units reporting NEST-IT data in their QI project documentation (April 2024 to June 2024). Finally, this study identified sustainability strategies as a critical need.

Conclusions

Integrating IR and QI enhances SSNC in resource-limited settings. Addressing barriers, leveraging facilitators and using structured IR frameworks advanced QI efforts, thereby improving intervention reach, adoption and feasibility while building scalable systems for high-quality healthcare.

Background

Since 2015, the National Institute for Health and Care Excellence (NICE) guidelines have recommended antenatal magnesium sulfate (MgSO4) for mothers in preterm labour (<30 weeks’ gestation) to reduce the risk of cerebral palsy (CP) in the preterm baby. However, the implementation of this guideline in clinical practice was slow, and MgSO4 use varied between maternity units. In 2018, the PRrevention of Cerebral palsy in PreTerm labour (PReCePT) programme, an evidence-based quality improvement (QI) intervention to improve use of MgSO4, was rolled out across England. Earlier evaluation found this programme to be effective and cost-effective over the first 12 months. We extended the original evaluation to determine the programme’s longer-term impact over 4 years, its impact in later preterm births, the impact of the COVID-19 pandemic, and to compare MgSO4 use in England (where PReCePT was implemented) to Scotland and Wales (where it was not).

Methods

Quasi-experimental longitudinal study using data from the National Neonatal Research Database on babies born <30 weeks’ gestation and admitted to a National Health Service neonatal unit. Primary outcome was the percentage of eligible mothers receiving MgSO4, aggregated to the national level. Impact of PReCePT on MgSO4 use was estimated using multivariable linear regression. The net monetary benefit (NMB) of the programme was estimated.

Results

MgSO4 administration rose from 65.8% in 2017 to 85.5% in 2022 in England. PReCePT was associated with a 5.8 percentage points improvement in uptake (95% CI 2.69 to 8.86, p<0.001). Improvement was greater when including older preterm births (<34 weeks’ gestation, 8.67 percentage points, 95% CI 6.38 to 10.96, p<0.001). Most gains occurred in the first 2 years following implementation. PReCePT had a NMB of £597 000 with 89% probability of being cost-effective. Following implementation, English uptake appeared to accelerate compared with Scotland and Wales. There was some decline in use coinciding with the onset of the pandemic.

Conclusions

The PReCePT QI programme cost-effectively improved use of antenatal MgSO4, with anticipated benefits to the babies who have been protected from CP.