Healthcare systems are becoming increasingly complex, requiring coordination among multiple professionals, technologies and information sources. While radio-frequency identification (RFID) technologies have traditionally been adopted for asset tracking and inventory management, their potential contribution to patient safety extends beyond operational efficiency. This commentary proposes a conceptual framework that positions RFID-enabled visualization as a mechanism that may link healthcare technology, teamwork, psychological safety and shared decision-making. Drawing on experiences from RFID implementation in surgical instrument management, emerging applications in medication safety and principles from TeamSTEPPS, the author argues that visualization may support the development of shared mental models among healthcare professionals. Improved visibility of clinical information may enhance communication, situation monitoring, mutual support and organizational learning. Furthermore, visualization may facilitate patient participation by enabling clearer communication and more consistent information sharing between healthcare teams and patients. The evolution of RFID-enabled smart infusion pumps, interoperability, predictive safety and digital twin technologies illustrates how healthcare systems are shifting from retrospective incident management towards proactive and learning-oriented safety approaches. This commentary argues that the value of RFID should be considered not only in terms of tracking assets, but also in terms of supporting shared understanding and safer decision-making. RFID-enabled visualization may therefore serve as one foundation for future patient safety and quality improvement initiatives.
A lack of compliance with professional privileging and training requirements is the most common cause of dental malpractice. In hospital dentistry, some dental specialties are trained to treat patients in the operating room, whereas others, including restorative dentists, endodontists, prosthodontists, and periodontists, are occasionally required for dental management under general anesthesia, yet typically hold no operating room privileges. This creates a gap in standardized care and patient-safety compliance. To address this gap, this narrative review proposes a conceptual model that enables non-OR-privileged dental specialists to participate safely in the care of patients requiring multidisciplinary management in the Saudi Arabian healthcare context. The review was developed following the Scale for the Assessment of Narrative Review Articles (SANRA). The model was developed through thematic synthesis of the included literature and gray documents. It comprises four interdependent domains: Governance, Regulatory OR-Safety Requirements, Institutional Privileging, and Proficiency-based Training, collectively termed the GRIP model. These domains interlock through four shared patient-safety outcomes: improved OR efficiency, reduced inappropriate practice, monitoring of potential malpractice, and improved clinical effectiveness. By clarifying the competencies, documentation, and accountabilities of non-OR-privileged dental specialists, the GRIP model might enable their management with the same rigor as that applied to other medical staff, while maintaining efficient hospital-based dental services and patient safety. This conceptual model is intended to guide practice rather than prescribe a single protocol. Yet it can serve as an adaptable reference for health systems in countries seeking to promote patient-centered care across their healthcare settings.
Background The Making Healthcare Safer III report in 2020 found moderate strength of evidence that sepsis prediction tools improve process measures, but the impact on clinical outcomes was unclear. This rapid review aimed to determine the effectiveness of recent sepsis prediction and recognition systems. Methods We searched PubMed and the Cochrane Library for systematic reviews and primary studies published from January 2018 through August 2023. We included reviews and studies of sepsis prediction and recognition interventions reporting measures of clinical process (e.g. timeliness of diagnosis), patient outcomes (e.g. mortality), implementation (e.g. use of system recommendations), or costs. Results We found seven systematic reviews and eight original studies. The studies involved multicomponent interventions in pediatric and adult populations in pre-hospital, emergency department, intensive care unit (ICU), and hospital ward settings. The interventions improved clinical process measures in the neonatal population (low strength of evidence), but not in the adult population. In neonates, the evidence was insufficient about length of stay or mortality outcomes. For adults, interventions did not impact hospital length of stay or mortality outcomes. Sepsis alert systems struggled with poor predictive value, alert overload, delays, mistrust, and software limitations. Such challenges can be overcome with frequent communication, iterative improvement, clinician involvement, and training with test versions. Conclusion Recent studies do not show that sepsis prediction and recognition interventions are effective at reducing mortality or length of stay or improving clinical processes in adults, but may improve clinical process outcomes in neonatal ICUs. Several implementation barriers and facilitators were identified.
