THINKING LEAN: Improving Vitreoretinal Clinic Efficiency by Decentralizing Optical Coherence Tomography.

PURPOSE: Patients in vitreoretinal clinic have long wait times that could be reduced by improving the efficiency of patient flow. The objective of this study was to determine whether decentralizing optical coherence tomography (OCT) into the technicians' room would reduce patient wait times and improve clinic efficiency. METHODS: Randomized, single-center, clinical trial for 1 month without follow-up at Byers Eye Institute at Stanford. Subjects were return patients of three vitreoretinal specialists in March 2013. The intervention consisted of decentralizing OCT devices from the central photography suite into the technician screening rooms. Total clinic times and total wait times throughout subject appointments were recorded and compared with the control group (centralized photography suite). Secondary outcomes included frequency of injections, procedures, and primary diagnosis codes. RESULTS: Decentralized OCT reduced patient wait times by 74% and reduced total clinic appointment time by 36%. Subjects in the intervention arm experienced significantly reduced total wait time (mean difference = 15.9 minutes, P < 0.0001) and total time in clinic (mean difference = 22.9 minutes, P < 0.0001). CONCLUSION: Decentralized OCT represents the application of lean process concepts to improve vitreoretinal clinic efficiency. Decentralized OCT reduced both the total wait time and total time in clinic for return patients in a vitreoretinal clinic.

Machine Learning to Delineate Surgeon and Clinical Factors That Anticipate Positive Surgical Margins After Robot-Assisted Radical Prostatectomy.

Purpose: Automated performance metrics (APMs), derived from instrument kinematic and systems events data during robotic surgery, are validated objective measures of surgeon performance. Our previous studies showed that APMs are strong outcome predictors of urinary continence after robot-assisted radical prostatectomy (RARP). We now use machine learning to investigate how surgeon performance (i.e., APMs) and clinical factors can predict positive surgical margins (PSMs) after RARP. Methods: We prospectively collected data of patients undergoing RARP at our institution from 2016 to 2019. Random Forest model predicted PSMs based on 15 clinical factors and 38 APMs from 11 standardized RARP steps. Out-of-bag Gini impurity index determined the top 10 variables of importance (VOI). APMs in the top 10 VOI were assessed for confounding effects by extracapsular extension (ECE) and pathologic T (pT) through Poisson regression with Generalized Estimating Equation. Results: 55/236 (23.3%) cases had PSMs. Of the 55 cases with PSMs, 9 (16.4%) were pT2 and 46 (83.6%), pT3. The full model, including clinical factors and APMs, achieved area under the curve (AUC) 0.74. When assessing clinical factors or APMs alone, the model achieved AUC 0.72 and 0.64, respectively. The strongest PSM predictors were ECE and pT stage, followed by APMs in specific steps. After adjusting for ECE and pT stage, most APMs remained as independent predictors of PSM. Conclusion: Using machine learning methods, we found that the strongest predictors of PSMs after RARP are nonmodifiable, disease-driven factors (ECE and pT). While APMs provide minimal additional insight into when PSMs may occur, they are nonetheless capable of independently predicting PSMs based on objective measures of surgeon performance.

Development and validation of an objective scoring tool to evaluate surgical dissection: Dissection Assessment for Robotic Technique (DART).

Purpose: Evaluation of surgical competency has important implications for training new surgeons, accreditation, and improving patient outcomes. A method to specifically evaluate dissection performance does not yet exist. This project aimed to design a tool to assess surgical dissection quality. Methods: Delphi method was used to validate structure and content of the dissection evaluation. A multi-institutional and multi-disciplinary panel of 14 expert surgeons systematically evaluated each element of the dissection tool. Ten blinded reviewers evaluated 46 de-identified videos of pelvic lymph node and seminal vesicle dissections during the robot-assisted radical prostatectomy. Inter-rater variability was calculated using prevalence-adjusted and bias-adjusted kappa. The area under the curve from receiver operating characteristic curve was used to assess discrimination power for overall DART scores as well as domains in discriminating trainees (≤100 robotic cases) from experts (>100). Results: Four rounds of Delphi method achieved language and content validity in 27/28 elements. Use of 3- or 5-point scale remained contested; thus, both scales were evaluated during validation. The 3-point scale showed improved kappa for each domain. Experts demonstrated significantly greater total scores on both scales (3-point, p< 0.001; 5-point, p< 0.001). The ability to distinguish experience was equivalent for total score on both scales (3-point AUC= 0.92, CI 0.82-1.00, 5-point AUC= 0.92, CI 0.83-1.00). Conclusions: We present the development and validation of Dissection Assessment for Robotic Technique (DART), an objective and reproducible 3-point surgical assessment to evaluate tissue dissection. DART can effectively differentiate levels of surgeon experience and can be used in multiple surgical steps.

Building a Novel Health Curriculum for Survivors of Intimate Partner Violence Residing at a Transitional Housing Program.

We used a community-based participatory research approach to develop, implement, and evaluate one of the first health curricula for female intimate partner violence (IPV) survivors residing at a transitional housing program. The curriculum comprised 12 workshops that were developed based on the survivors' experiences, needs, and interests. Evaluation participants included 20 of the 37 women who attended at least one workshop, 12 workshop facilitators, and two housing center staff. Participants found the curriculum to be engaging, interactive, and helpful in building a supportive community. Suggestions for curricular improvement as well as opportunities for further research and curricular development are discussed.