Theses and Dissertations at Montana State University (MSU)
Permanent URI for this collectionhttps://scholarworks.montana.edu/handle/1/733
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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 Rural healthcare assessment: identifying gaps between service and expectations(Montana State University - Bozeman, College of Engineering, 2020) Dorsey, Robert Kenneth; Chairperson, Graduate Committee: David ClaudioThis research project aims to improve patient satisfaction for customers in same-day clinics in rural areas, with emphasis on healthcare services and facilities at Native American Reservations. This project examined potential gaps between clinical staff services and the expectations of the patients. Due to the remote location and low-income level of the community, it is critical for patients to receive care at local healthcare facilities and not have to travel to other facilities for the same care. The low Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) satisfaction scores also lead to less funding to the facility as well as lower-ranking in accreditation by Centers for Medicare and Medicaid Services (CMS). Utilizing survey tools and statistical analysis from Industrial and Management Systems Engineering the study looked to understand expectations on both sides. The initial phase used four open-ended questions along with a series of multiple-choice questions that were given to participants, both patients and staff. Data collected in the first phase showed a possible disconnect between the patients and staff from their responses. It also allowed the patients to rate service prior to the visit. Results showed some areas could have potential improvement but also the performance of staff is overall doing well with what they can control. The second phase revealed a more aligned view between the patients and staff in a ranking survey compiled from the first phase of the research. The ranking information allowed nonparametric testing to see if there existed statistically significant differences between the two groups. Results showed one significantly different item and two others that were borderline. The Service Value Gaps are not as prominent in this single clinic to warrant an in-depth improvement process. More information should be collected through other clinics to allow larger sample size to gain additional insight if multiple gaps exist. The items of actual or near significance were not a higher priority to either group.