Scholarship & Research
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Item Risk mitigation focused on surgical care using process improvement methodologies in rural health systems(Montana State University - Bozeman, College of Engineering, 2023) Sitar, Nejc; Chairperson, Graduate Committee: Bernadette J. McCrory; This is a manuscript style paper that includes co-authored chapters.Rural healthcare is represented by approximately one-third of community hospitals in the United States primarily in the Midwest and Western United States. Due to the lack of resources and the demographic characteristics of rural populations, rural community hospitals are under constant pressure to meet Center for Medicare & Medicaid Services (CMS) quality requirements. Meeting CMS quality requirements is particularly challenging in surgical care, due to the lower volumes and research opportunities, in addition to a shortage of qualified surgical specialists. The perioperative surgical home (PSH) model was established as a health management concept in a rural community hospital located in the Northwest of the United States to improve the quality of care by providing a longitudinal approach to patient treatment. The main opportunities for PSH improvement were identified in the "decision for surgery," "preoperative," and "postoperative" stages of the PSH model. To improve PSH clinic performance this thesis proposes an improved National Surgical Quality Improvement Program (NSQIP) calculator User Interface (UI), as well as a new prediction model for predicting total joint arthroplasty (TJA) Length of Stay (LOS). The improved layout of the NSQIP calculator was developed based on two approved surveys by card sorting and Borda count methodology, while the new prediction model for predicting TJA patients' LOS was based on the Decision Tree (DT) machine learning model. A usability study of the NSQIP calculator UI identified opportunities for future improvements, such as the reorganized layout of postoperative complications and the addition of a supporting tool that would clearly define postoperative complications. The new DT prediction model outperformed a currently used NSQIP calculator in the prediction accuracy of TJA LOS, as it resulted in lower Root-mean-Square-Error values. Furthermore, the structure of the DT model allowed better interpretability of the decision-making process compared to the NSQIP calculator, which increased the trust and reliability of the calculated prediction. Despite some limitations such as a small sample size, this study provided valuable information for future improvements in rural healthcare, that would enable Rural Community Hospitals to better predict future outcomes and meet the strict CMS quality standard.Item Investigating high-risk biomechanics in agricultural work(Montana State University - Bozeman, College of Engineering, 2022) Doud, Devon Michael; Chairperson, Graduate Committee: Scott Monfort; This is a manuscript style paper that includes co-authored chapters.Statement of Purpose: Osteoarthritis, a debilitating disease resulting in cartilage degradation and loss of mobility, is often instigated by injury or excessive loading of unconditioned articular cartilage. Although agricultural laborers are especially at risk of developing osteoarthritis, quantitative characterizations of occupation-specific activities have not previously been established. Deep flexion movements common to these groups (e.g., squatting or kneeling) may cause excessive contact forces on unconditioned cartilage, potentially initiating osteoarthritis development. Additionally, although cognitive loads can significantly alter gait mechanics, the effects of dual-task conditions (e.g., visual Stroop tests while walking) on contact forces have not previously been established. The purpose of this thesis is to better understand potential factors of osteoarthritis development in agricultural laborers by investigating occupational-specific movement patterns and joint loading during common occupational tasks. Methods: The first study evaluated seasonal differences in activity levels for farmers and ranchers by measuring movement intensity via wearable triaxial accelerometers. We hypothesized that ranchers would exhibit consistently high activity levels and that both groups would show an increase in movement intensity in their respective high seasons. The second study sought to establish the effects of cognitive challenges on tibiofemoral contact forces during normal gait and kneel-to-stand transitions in healthy adults. We hypothesized that dual-task conditions would correspond with increased peak tibiofemoral contact forces and that these forces would be positioned farther from the joint center along the mediolateral axis during dual-task conditions. Results: The first study findings largely supported the hypothesis: increased movement intensity during high seasons were recorded for both groups, with farmers exhibiting a larger seasonal fluctuation for moderate intensity activities. The second study did not support the hypothesis: cognitive loading did not significantly affect the magnitude of peak contact forces, and peak contact forces occurred closer to the joint center during dual-task conditions than during single-task conditions. However, post hoc analysis suggested that other portions of the contact force time series during stance phase were affected by cognitive challenges. Conclusions: This thesis provides foundational steps in understanding potential contributing factors of osteoarthritis development in agricultural laborers, directing future investigations towards transitional contact forces in movements simulating livestock handling.