Articles of Interest
Uncovering Latent Failures Using Human Factors Approach as a Diagnostic Tool for Quality Improvement in Orthopedic Surgery
Khan, A, Cohen, T, Shappell, S & Boquet, A. (2025). Uncovering Latent Failures Using Human Factors Approach as a Diagnostic Tool for Quality Improvement in Orthopedic Surgery. American Journal of Medical Quality, 40, 255-260. https://doi.org/10.1097/JMQ.0000000000000265
Abstract
Human factors significantly influence medical quality, especially in complex environments like orthopedic surgery, where latent failures can compromise patient safety. A total of 3168 intraoperative events were observed across 40 orthopedic procedures and classified using the Human Factors Analysis and Classification System (HFACS). Three trained coders independently applied HFACS across 4 tiers and 19 causal categories. Interrater reliability was measured through percent agreement and Fleiss' Kappa using unanimous, majority, and reconciled coding conditions. Nearly all observed disruptions (98.97%) were classified as preconditions to unsafe acts, most (68.75%) stemmed from crew resource management failures, distractions from personal electronic devices, poor communication, and sales representative presence. A total of 19.47% of disruptions were due to personal readiness, due to the sales representation supporting role in ensuring technologies. An additional 5.87% were due to physical environment issues like equipment noise.
Conclusions: The HFACS framework demonstrated strong reliability in identifying systemic weaknesses within orthopedic surgical workflows. These findings emphasize the urgent need for structured interventions that reduce distractions, improve team communication, and regulate vendor interactions in the operating room, all essential steps toward advancing safety and enhancing overall patient care quality.
When AI Becomes Overly Agreeable: New Research on the Risks of Sycophantic Chatbots
(2026). When AI Becomes Overly Agreeable: New Research on the Risks of Sycophantic Chatbots. Biomedical Safety & Standards, 56 (10), 185-186. doi: 10.1097/01.BMSAS.0001193568.10898.79.
Excerpt:
Artificial intelligence (AI) chatbots take a helpful, polite, and supportive tone. A new paper published in Science 1 suggests that agreeableness can become problematic when it becomes sycophancy. In “Sycophantic AI Decreases Prosocial Intentions and Promotes Dependence,”1 researchers from Stanford University Department of Computer Science investigated how frequently AI systems tell users what they want to hear, and what effect that has on human judgment and behavior.
It will not surprise users to learn that sycophantic AI appears to be widespread. But even brief interactions with it can reduce accountability, weaken interest in repairing relationships, and increase dependence on the chatbot.
The researchers define sycophancy as excessive agreement, affirmation, or flattery directed toward users. In ordinary conversation, that may seem harmless or even reassuring. But in emotionally charged situations, particularly interpersonal conflict, the chatbots can reinforce a one-sided interpretation of events. The paper1 focuses on a scenario that is already familiar to many users: asking a chatbot for advice about whether they were justified in an argument, breakup, betrayal, or family dispute. According to the study, leading AI models often validate the user's perspective rather than challenge it, even when the behavior described involves deception, illegality, or clear harm.
Potential applications of artificial intelligence with large datasets for predicting food biotoxicity
Xing, Kuoran , Wang, Qiang , Dadol, Glebert Cañete , et al
Potential applications of artificial intelligence with large datasets for predicting food biotoxicity, Food Quality and Safety, vol 26 no 10, February 2026.
Abstract
Food safety is a critical global concern, as toxic substances in food pose serious risks to public health. With the rise of novel
food products such as cell-cultured, fermented, and genetically modified items, there is an urgent need for more efficient
and accurate methods to assess food toxicity. Traditional testing approaches often lack the speed, scalability, and
sensitivity needed to detect emerging toxicants. Omics-based technologies now offer comprehensive insights into
biological responses, enabling the identification of subtle or unknown toxic effects. However, the complexity and scale
of omics data present significant challenges for interpretation. To address this, artificial intelligence (AI) has emerged as
a powerful tool to analyze large datasets and improve toxicity prediction. In this review, we summarize key categories of
food toxicants, introduce omics technologies and publicly available databases, outline general AI modeling workflows,
and highlight recent applications of AI in food safety. Together, AI with large amount of food-related data are shaping
the future of food safety strategies.
Generational Change in the Healthcare Workforce: Perspectives from Health System Leaders
White, Andrew A , Gallagher, Thomas H , Warren, Keegan D , et al
The Joint Commission Journal on Quality and Patient Safety
Abstract
Background
The healthcare workforce has never included so many different generations, creating both important opportunities and vexing challenges. Little is known about how health system leaders conceptualize generational differences among clinicians, respond to mismatched expectations, promote patient safety despite employee turnover, and minimize conflict.
Methods
We conducted semi-structured interviews with 17 key informants in executive leadership roles, including chief officers for operations, medicine, nursing, human resources, and academic affairs. We performed a qualitative analysis using a thematic content approach.
Results
All participants and their institutions were wrestling with tensions arising from a multi-generational clinical workforce, including differing perspectives on complex issues such as burnout, well-being, and clinical expectations. Some issues represented aftershocks from major events or trends, such as trainee duty hour regulation, the corporatization of medicine, and the Covid-19 pandemic. Respondents described both reactive and proactive adaptations, and expressed interest in developing organizational frameworks and solutions to minimize intergenerational conflict around work duties, manage end-of-career transitions, and address issues caused by rapid employee turnover. Human resource professionals demonstrated expertise in managing turnover and benefits, but felt underutilized by clinical leaders.
Conclusions
Generational change in the healthcare workforce is an urgent but under-studied area for clinical and safety leaders given worsening stresses on the healthcare system. Respondents recommended strategies to enhance the value of multigenerational workforces, including tighter collaboration with human resource professionals, new retention strategies for early-career clinicians, and creative job design for senior health professionals.
“The Process Is Built for Psychological Safety”: Behavioral Health Providers’ Experiences Using a Systems-Based Information Integration Tool for Critical Incident Review
McGladrey, M. , Lindsey, T. , Fairhurst, S. , Andriola, C. , Riley, E. , Meyers, C. & Cull, M. (2026). “The Process Is Built for Psychological Safety”: Behavioral Health Providers’ Experiences Using a Systems-Based Information Integration Tool for Critical Incident Review. Journal of Patient Safety, 22 (4), 245-250. doi: 10.1097/PTS.0000000000001452.
Abstract
Objectives:
Learning from critical incidents is a major component of efforts to improve patient safety that increasingly center on system-level factors rather than individual errors to both address root causes of critical incidents and promote psychological safety in health care and social service agency cultures. However, there are limited studies of professionals’ experiences with system-level critical incident review processes and how these experiences influence practice in behavioral health settings.
Methods:
This mixed-methods study explores how practitioners at the largest behavioral health agency in California perceived the use of the Safe Systems Improvement Tool to learn from critical incidents, including deaths by suicide, overdoses, and near misses.
Results:
Survey and interview data from behavioral health practitioners indicated that for critical incident reviews, empathetic facilitation, deliberate preparation, and expectation-setting before meetings support psychological safety and systems change. Participants recommended including front-line as well as clinical and supervisory staff in critical incident reviews and developing clear timelines for implementing follow-up recommendations.
Conclusions:
The application of critical incident reviews in behavior health agencies can be effective not only in identifying root causes and quality improvement opportunities through the aggregation of data across events, but also in fostering cultures of psychological safety to reduce individual blame and defensiveness while promoting transparent system-wide assessment and transformation.
Implementing Participation-level Goals to Improve Patient-Centeredness in Pediatric Rehabilitation
Tanner, K. , Boster, J. , Gates, E. , Rospert, A. , Coleman Casto, S. , O’Rourke, S. , Gillespie, J. & Bican, R. (2026). Implementing Participation-level Goals to Improve Patient-Centeredness in Pediatric Rehabilitation. Pediatric Quality and Safety, 11 (2), e874. doi: 10.1097/pq9.0000000000000874.
Abstract
Introduction:
The global goal of pediatric rehabilitation services is to increase the ability of children to participate in meaningful life activities. Services that do not include a participation-centered goal are unlikely to achieve this impact. In this study, a participation component was operationally defined as a reference to a person or place outside the therapy context, regardless of the practice setting or discipline. The aim was to increase the use of participation-level goals among patients seen across all departments in the Division of Clinical Therapies from 50% to 80% by December 31, 2022, and sustain this level for 6 months.
Methods:
We implemented Plan-Do-Study-Act cycles in accordance with the Model for Improvement endorsed by the Institute for Healthcare Improvement. We tailored interventions for 6 participating departments. Strategies included audit and feedback, targeted communication with teams, and the use of champions. Then, we sampled charts across departments. We analyzed data using a statistical process control chart with a baseline mean of 32.5% and a target of 80%.
Results:
The goal of 80% of charts containing a rehabilitation goal with a participation-level component was achieved after 24 months of interventions, reaching a new centerline of 82% and sustaining this level for 6 months.
Conclusions:
We implemented patient goals with a participation component across multiple rehabilitation departments within a large division of a major pediatric hospital, using quality improvement methodology. Departments benefited from general strategies (eg, reminders) and tailored interventions (eg, targeted communication) to achieve and maintain 80% compliance.
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