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Study Objective: This study aimed to apply a structured human factors analysis to understand conditions contributing to vaginal retained foreign objects (RFOs).Design: All potential vaginal RFO events from January 1, 2000, to May 21, 2019, were analyzed by trained human factors researchers. Each narrative was reviewed to identify contributing factors, classified using the Human Factors Analysis and Classification System for Healthcare.Setting: An 890-bed, academic medical center in Southern California.Patients: Patients who underwent a vaginal procedure in which a vaginal RFO-related event occurred were included in this study. However, no patient information was included, and only the relevant details from their procedures were included.Interventions: No interventions were developed or implemented.Measurements and Main Results: Over the 19-year period, 45 events were reported. The most common items were vaginal packing and vaginal sponges (53.33%). Less frequently retained items involved broken instruments (20.20%). Most cases were laparoscopic hysterectomies or vaginal deliveries. Based on the Human Factors Analysis and Classification System, 75 contributing factors were identified, consisting primarily of preconditions for unsafe acts (communication challenges, coordination breakdowns and issues with the design of tools/technology) and unsafe acts (errors).Conclusion: Although rare, vaginal RFOs do occur. The top 2 contributing factors were skill-based errors and communication breakdowns. Both types of errors can be addressed and improved with human factors interventions, including simulation, teamwork training, and streamlining workflow to reduce the opportunity for errors. [ABSTRACT FROM AUTHOR]

Background: The integration of high technology into health care systems is intended to provide new treatment options and improve the quality, safety, and efficiency of care. Robotic-assisted surgery is an example of high technology integration in health care, which has become ubiquitous in many surgical disciplines. Objective: This study aims to understand and measure current robotic-assisted surgery processes in a systematic, quantitative, and replicable manner to identify latent systemic threats and opportunities for improvement based on our observations and to implement and evaluate interventions. This 5-year study will follow a human factors engineering approach to improve the safety and efficiency of robotic-assisted surgery across 4 US hospitals. Methods: The study uses a stepped wedge crossover design with 3 interventions, introduced in different sequences at each of the hospitals over four 8-month phases. Robotic-assisted surgery procedures will be observed in the following specialties: urogynecology, gynecology, urology, bariatrics, general, and colorectal. We will use the data collected from observations, surveys, and interviews to inform interventions focused on teamwork, task design, and workplace design. We intend to evaluate attitudes toward each intervention, safety culture, subjective workload for each case, effectiveness of each intervention (including through direct observation of a sample of surgeries in each observational phase), operating room duration, length of stay, and patient safety incident reports. Analytic methods will include statistical data analysis, point process analysis, and thematic content analysis. Results: The study was funded in September 2018 and approved by the institutional review board of each institution in May and June of 2019 (CSMC and MDRH: Pro00056245; VCMC: STUDY 270; MUSC: Pro00088741). After refining the 3 interventions in phase 1, data collection for phase 2 (baseline data) began in November 2019 and was scheduled to continue through June 2020. However, data collection was suspended in March 2020 due to the COVID-19 pandemic. We collected a total of 65 observations across the 4 sites before the pandemic. Data collection for phase 2 was resumed in October 2020 at 2 of the 4 sites. Conclusions: This will be the largest direct observational study of surgery ever conducted with data collected on 680 robotic surgery procedures at 4 different institutions. The proposed interventions will be evaluated using individual-level (workload and attitude), process-level (perioperative duration and flow disruption), and organizational-level (safety culture and complications) measures. An implementation science framework is also used to investigate the causes of success or failure of each intervention at each site and understand the potential spread of the interventions. International Registered Report Identifier (IRRID): DERR1-10.2196/25284 JMIR Res Protoc 2021;10(2):e25284 doi:10.2196/25284 We help JMIR researchers to raise funds to pursue their research and development aimed at tackling important health and technology challenges. If you would like to show your support for this author, please donate using the button below. The funds raised will directly benefit the corresponding author of this article (minus 8% admin fees). Your donations will help this author to continue publishing open access papers in JMIR journals. Donations of over $100 may also be acknowledged in future publications. Submit Suggested contribution levels: $20/$50/$100 [ABSTRACT FROM AUTHOR]