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Background: Surgical volume is known to influence failure to rescue (FTR), defined as death following a complication. Robotic lung surgery continues to expand and there is variability in outcomes among hospitals. We sought to estimate the contribution of hospital-based factors on outcomes and FTR following robotic right upper lobectomy (RRUL). Methods: Using the Centers for Medicare and Medicaid Services inpatient claims database, we evaluated all patients age ≥65 years with a diagnosis of lung cancer who underwent RRUL between January 2018 and December 2020. We excluded patients who had undergone segmentectomy, sublobar, wedge, or bronchoplastic resection; had metastatic or nonmalignant disease; or had a history of neoadjuvant chemotherapy. Primary outcomes included FTR rate, length of stay (LOS), readmissions, conversion to open surgery, complications, and costs. We analyzed hospitals by tertiles of volume and Medicare Mortality Index (MMI). Defined as the institutional number of deaths per number of survivors, MMI is a marker of overall hospital performance and quality. Propensity score models were adjusted for confounding using goodness of fit. Results: Data for 4317 patients who underwent robotic right upper lobectomy were analyzed. Hospitals were categorized by volume of cases (low, 20) and MMI (low, 0.13). After propensity score balancing, patients from tertiles of lowest volume and highest MMI had higher costs ($34,222 vs $30,316; P = .006), as well as higher mortality (odds ratio, 7.46; 95% confidence interval, 2.67-28.2; P

We developed an American Sign Language (ASL) learning platform in a Virtual Reality (VR) environment to facilitate immersive interaction and real-time feedback for ASL learners. We describe the first game to use an interactive teaching style in which users learn from a fluent signing avatar and the first implementation of ASL sign recognition using deep learning within the VR environment. Advanced motion-capture technology powers an expressive ASL teaching avatar within an immersive three-dimensional environment. The teacher demonstrates an ASL sign for an object, prompting the user to copy the sign. Upon the user’s signing, a third-party plugin executes the sign recognition process alongside a deep learning model. Depending on the accuracy of a user’s sign production, the avatar repeats the sign or introduces a new one. We gathered a 3D VR ASL dataset from fifteen diverse participants to power the sign recognition model. The proposed deep learning model’s training, validation, and test accuracy are 90.12%, 89.37%, and 86.66%, respectively. The functional prototype can teach sign language vocabulary and be successfully adapted as an interactive ASL learning platform in VR.

Abstract Background Community-based health interventions have been an integral part of recent health gains globally. An innovative approach to delivering community health care combines the Census-Based, Impact-Oriented (CBIO) Approach with Care Groups and Community Birthing Centers called Casas Maternas Rurales. CBIO+ was adopted by Curamericas/Guatemala in its Maternal and Child Health Project, 2011–2015. Here, we describe the opinions of Project staff and local government health care workers about the strengths and challenges of CBIO+. Methods Self-administered questionnaires, key informant interviews, and focus group discussions were used to obtain the views of 21 staff members from Curamericas/Guatemala as well as 15 local government health workers. The evaluation focused on four primary areas: (1) advisability of integrating the CBIO+ Approach into the government’s rural health system, (2) staff knowledge of the CBIO+ Approach, (3) advantages, disadvantages and challenges of the CBIO+ Approach, and (4) proposed improvements to the CBIO+ Approach. The data were coded into categories and from these categories themes were derived. Results The most commonly mentioned advantage of CBIO+ was the inclusion of the community in program planning, which improved participation. Many respondents noted that the CBIO+ Approach was challenging to implement in communities with internal conflicts. Among other challenges mentioned were coordinating (both among the Project staff and with others in the communities), maintenance of a high level of community participation, and overcoming opposition of men to women’s participation in Care Groups. The staff mentioned a number of possible changes, including increasing male involvement, raising salaries for community-level paid staff, providing volunteers with incentives, and improving coordination both internally and externally. There was a strong demand among the local Ministry of Public Health and Social Welfare staff for the Project to continue. Conclusion The CBIO+ Approach and its implementation by Curamericas/Guatemala was overall embraced by local staff. By eliciting feedback while the project was ongoing, actionable areas for improvement were identified.

Abstract Background The Curamericas/Guatemala Maternal and Child Health Project, 2011–2015, included implementation research designed to assess the effectiveness of an approach referred to as CBIO+ , composed of: (1) the Census-Based, Impact-Oriented (CBIO) Approach, (2) the Care Group Approach, and (3) the Community Birthing Center Approach. This is the second paper in a supplement of 10 articles describing the implementation research and its findings. Paper 1 describes CBIO+ , the Project Area, and how the Project was implemented. Objective This paper describes the implementation research design and details of how it was carried out. Methods We reviewed the original implementation research protocol and the methods used for all data collection related to this Project. The protocol and methods used for the implementation research related to this Project were all standard approaches to the monitoring and evaluation of child survival projects as developed by the United States Agency for International Development Child Survival and Health Grants Program (CSHGP) and the CORE Group. They underwent independent peer review supervised by the CSHGP before the implementation research began. Results The study area was divided into two sets of communities with a total population of 98,000 people. Project interventions were implemented in Area A from 2011 until the end of the project in 2015 (44 months) and in Area B from late 2013 until 2015 (20 months). Thus, Area B served as a quasi-comparison area during the first two years of Project implementation. The overarching study question was whether the CBIO+ Approach improved the health and well-being of children and mothers. The outcome indicators included (1) changes in population coverage of evidence-based interventions, (2) changes in childhood nutritional status, (3) changes in the mortality of children and mothers, (4) quality of care provided at Community Birthing Centers, (5) the impact of the Project on women’s empowerment and social capital, (6) stakeholder assessment of the effectiveness of the CBIO+ Approach, and (7) the potential of wider adoption of the CBIO+ Approach. Conclusion The implementation research protocol guided the assessment of the effectiveness of the CBIO+ Approach in improving the health and well-being of children, mothers, and their communities.

Purpose: Anatomical changes and patient setup uncertainties during intensity modulated proton therapy (IMPT) of head and neck (HN) cancers demand frequent evaluation of delivered dose. This work investigated a cone-beam computed tomography (CBCT) and deformable image registration based therapy workflow to demonstrate the feasibility of proton dose calculation on synthetic computed tomography (sCT) for adaptive IMPT treatment of HN cancer. Materials and Methods: Twenty-one patients with HN cancer were enrolled in this study, a retrospective institutional review board protocol. They had previously been treated with volumetric modulated arc therapy and had daily iterative CBCT. For each patient, robust optimization (RO) IMPT plans were generated using ±3 mm patient setup and ±3% proton range uncertainties. The sCTs were created and the weekly delivered dose was recalculated using an adaptive dose accumulation workflow in which the planning computed tomography (CT) was deformably registered to CBCTs and Hounsfield units transferred from the planning CT. Accumulated doses from ±3 mm/ ±3% RO-IMPT plans were evaluated using clinical dose-volume constraints for targets (clinical target volume, or CTV) and organs at risk. Results: Evaluation of weekly recalculated dose on sCTs showed that most of the patient plans maintained target dose coverage. The primary CTV remained covered by the V95 ≥ 95% (95% of the volume receiving more than 95% of the prescription dose) worst-case scenario for 84.5% of the weekly fractions. The oral cavity accumulated mean dose remained lower than the worst-case scenario for all patients. Parotid accumulated mean dose remained within the uncertainty bands for 18 of the 21 patients, and all were kept lower than RO-IMPT worst-case scenario for 88.7% and 84.5% for left and right parotids, respectively. Conclusion: This study demonstrated that RO-IMPT plans account for most setup and anatomical uncertainties, except for large weight-loss changes that need to be tracked throughout the treatment course. We showed that sCTs could be a powerful decision tool for adaptation of these cases in order to reduce workload when using repeat CTs.