The application of objective clinical human reliability analysis (OCHRA) in the assessment of basic robotic surgical skills.

BACKGROUND: Using a validated, objective, and standardised assessment tool to assess progression and competency is essential for basic robotic surgical training programmes. Objective clinical human reliability analysis (OCHRA) is an error-based assessment tool that provides in-depth analysis of individual technical errors. We conducted a feasibility study to assess the concurrent validity and reliability of OCHRA when applied to basic, generic robotic technical skills assessment. METHODS: Selected basic robotic surgical skill tasks, in virtual reality (VR) and dry lab equivalent, were performed by novice robotic surgeons during an intensive 5-day robotic surgical skills course on da Vinci® X and Xi surgical systems. For each task, we described a hierarchical task analysis. Our developed robotic surgical-specific OCHRA methodology was applied to error events in recorded videos with a standardised definition. Statistical analysis to assess concurrent validity with existing tools and inter-rater reliability were performed. RESULTS: OCHRA methodology was applied to 272 basic robotic surgical skills tasks performed by 20 novice robotic surgeons. Performance scores improved from the start of the course to the end using all three assessment tools; Global Evaluative Assessment of Robotic Skills (GEARS) [VR: t(19) = - 9.33, p < 0.001] [dry lab: t(19) = - 10.17, p < 0.001], OCHRA [VR: t(19) = 6.33, p < 0.001] [dry lab: t(19) = 10.69, p < 0.001] and automated VR [VR: t(19) = - 8.26, p < 0.001]. Correlation analysis, for OCHRA compared to GEARS and automated VR scores, shows a significant and strong inverse correlation in every VR and dry lab task; OCHRA vs GEARS [VR: mean r = - 0.78, p < 0.001] [dry lab: mean r = - 0.82, p < 0.001] and OCHRA vs automated VR [VR: mean r = - 0.77, p < 0.001]. There is very strong and significant inter-rater reliability between two independent reviewers (r = 0.926, p < 0.001). CONCLUSION: OCHRA methodology provides a detailed error analysis tool in basic robotic surgical skills with high reliability and concurrent validity with existing tools. OCHRA requires further evaluation in more advanced robotic surgical procedures.

COVID-19 disease in hospitalized young adults in India and China: Evaluation of risk factors predicting progression across two major ethnic groups.

Data pertaining to risk factor analysis in coronavirus disease 2019 (COVID-19) is confounded by the lack of data from an ethnically diverse population. In addition, there is a lack of data for young adults. This study was conducted to assess risk factors predicting COVID-19 severity and mortality in hospitalized young adults. A retrospective observational study was conducted at two centers from China and India on COVID-19 patients aged 20-50 years. Regression analysis to predict adverse outcomes was performed using parameters including age, sex, country of origin, hospitalization duration, comorbidities, lymphocyte count, and National Early Warning Score 2 (NEWS2) score at admission. A total of 420 patients (172 East Asians and 248 South Asians) were included. The predictive model for intensive care unit (ICU) admission with variables NEWS2 Category II and higher, diabetes mellitus, liver dysfunction, and low lymphocyte counts had an area under the curve (AUC) value of 0.930 with a sensitivity of 0.931 and a specificity of 0.784. The predictive model for mortality with NEWS2 Category III, cancer, and decreasing lymphocyte count had an AUC value of 0.883 with a sensitivity of 0.903 and a specificity of 0.701. A combined predictive model with bronchial asthma and low lymphocyte count, in contrast, had an AUC value of 0.768 with a sensitivity of 0.828 and a specificity of 0.719 for NEWS2 score (5 or above) at presentation. NEWS2 supplemented with comorbidity profile and lymphocyte count could help identify hospitalized young adults at risk of adverse COVID-19 outcomes.