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Introduction: Nursing homes throughout the U.S. have faced unprecedented challenges in recent years because of staffing shortages, and under-investment, especially since the COVID-19 pandemic. To gain insight into the current state of nursing homes, this study examined nursing home characteristics, quality, and accessibility from a national, regional and state perspective. Methods: This cross-sectional study used secondary data from the Centers for Medicare and Medicaid Services, American Community Survey, Medicare Beneficiary, and the Tennessee Department of Health. Nursing home characteristics and quality were assessed through bivariate and multivariate regression in the U.S. Assessment of HHS Region 4 nursing home characteristics and quality by state cut points were conducted with bivariate analysis. Finally, spatial analysis was conducted to determine nursing home accessibility in Tennessee. Results: In multivariate analyses of all U.S. facilities, non-metropolitan facilities are at 1.27 higher odds of being a 1-star overall rated facility and 0.86 lower odds of being a 5-star facility as compared to metropolitan facilities. When weighted health inspection scores were recategorized by more strict state cut points, 42.45% of HHS Region 4 facilities decreased in health inspection star ratings, while those that were recategorized by more lenient state cut points lead to a 26.64% increase in star ratings. Finally, in the state of Tennessee a mean of 14.9% of county areas are not within 30-minute drive to any nursing home facilities, with 66.4% of county areas being further than a 30-minute drive to a 5-star rated (highest quality) facility. Discussion: Findings from this study show that differences exist in nursing home characteristics that relate to facility quality. Additionally, health inspection 5-star ratings can vary across states, which can make comparison of quality challenging from a consumer perspective. And finally, accessibility to nursing homes can vary throughout a state by metropolitan and non-metropolitan status of the county. An understanding of nursing homes in metropolitan and non-metropolitan communities along with nursing home quality, characteristics of the facility, and characteristics of county populations can enable policymakers to create more equitable policy solutions for nursing homes and the communities they serve.

This qualitative phenomenological study examined central Florida's nursing home administrators' knowledge and perception of cultural competence and how they perceive that their knowledge and perceptions impact residents, families, and healthcare. The theoretical framework for this study was explained through Campinha-Bacote's interdisciplinary model of The Process of Cultural Competence in the Delivery of Healthcare Services. The theoretical framework was used to guide research questions, and individual interview questions to obtain nursing home administrator's knowledge and perception of cultural competence. The study explored the level of cultural competence reported by nursing home administrators, their individual perception of cultural competence, their degree of confidence in cultural competence, and how nursing home administrators describe their proficiencies and skills in cultural competence. Interviews with six nursing home administrators included licensed nursing home administrators (NHA) and assistant nursing home administrators, and the director of nursing (DON). The findings identified and analyzed the diverse levels of nursing home administrator's knowledge and perception of cultural competence. Some participants demonstrated difficulty expressing their knowledge and perception of cultural competence. Findings indicate that various factors influenced participants' overall degree of confidence in their knowledge and perception of cultural competence. Nursing home administrators also had a difficult time articulating particular skills that demonstrate their ability to adapt to the diverse residents in their facilities, and how they promote cultural competence in their nursing home facilities. This study identified the need for additional research and continuing education about cultural competence in healthcare.

The decision to vertically integrate services and deliver care has both management and policy concerns for healthcare in the United States. The change in reimbursement, which was enacted with the Balanced Budget Act of 1997, influenced the availability of post acute services for acute hospital inpatients. Prior to this change, post acute services were reimbursed based on cost similar to the pre DRG era of Medicare reimbursement. The change in payment had the potential to make discharging patients more difficult resulting in a prolonged length of stay without additional payment and at increased costs for hospitals. As a result of this change hospitals made arrangements to provide care for this population. The choices included vertical integration, contracting or hybrid arrangement and simply relying on the spot market. This makes or buy decision is a focus of this study. Were hospital decisions different after the BBA, than before this legislation?This study utilizes Oliver Williamson's transaction cost economics theory as the framework for the study and is a replication of a prior study by Chiu (1995) hybrid arrangement and simply relying on the spot market. This makes or buy decision is a focus of this study. Were hospital decisions different after the BBA, than before this legislation?This study utilizes Oliver Williamson's transaction cost economics theory as the framework for the study and is a replication of a prior study by Chiu (1995) The Williamsons theory is based on the proposition that three transaction dimensions determine the most efficient method of operation for a firm: uncertainty, frequency, and asset specificity. Depending on the "market", organizations may elect to arrange services through the spot market, contract for services, or vertically integrate the service. The study uses data from the American Hospital Association survey as well as the Area Resources files to determine if individual hospitals have made contract arrangements, vertically integrated, or relied on the spot market to provide skilled nursing services. Data is collected before and after the BBA and analyzed using multiple regression analysis and then subjected to significance testing. Sixteen hypotheses are tested that focus on the three dimensions of transaction cost theory. Findings support the importance of transaction frequency and asset specificity, while only weak support is offered for transaction uncertainty. The results differ from the Chiu study, which found strong support for uncertainty and weak support for frequency. This study is unique in that it examines data from two time periods surrounding a major reimbursement change in Medicare. It makes an important contribution to the empirical testing of transaction cost economics and the decision to vertically integrate in health care.

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<p dir="ltr">Recurrent stroke, infection, and seizure are some of the most common complications in stroke survivors. Recurrent stroke leads to death in 38.6% of survivors, and infections are the most common risk factor for seizures, with stroke survivors that experience an infection being at greater risk of experiencing a seizure. Two predictive models were generated, recurrent stroke and post-infection seizure, to determine stroke survivors at greatest risk to help providers focus on prevention in higher risk residents.</p><p dir="ltr">Predictive models were generated from a retrospective study of the Long-Term Care Minimum Data Set (MDS) 3.0 (2014-2018, n=262,301). Techniques included three data balancing methods (SMOTE for up sampling, ENN for down sampling, and SMOTEENN for up and down sampling) and three feature selection methods (LASSO, RFE, and PCA). The resulting datasets were then trained on four machine learning models (Logistic Regression, Random Forest, XGBoost, and Neural Network). Model performance was evaluated with AUC and accuracy, and interpretation used SHapley Addictive exPlanations.</p><p dir="ltr">Using data balancing methods improved the prediction performances of the machine learning models, but feature selection did not remove any features or affect performance. With all models having a high accuracy (78.6% to 99.9%), interpretation on all four models yielded the most holistic view. For recurrent stroke, SHAP values indicated that treatment combinations of occupational therapy, physical therapy, antidepressants, non-medical intervention for pain, therapeutic diet, anticoagulants, and diuretics contributed more to reducing recurrent stroke risk in the model when compared to individual treatments. For post-infection seizure, SHAP values indicated that therapy (speech, physical, occupational, and respiratory), independence (activities of daily living for walking, mobility, eating, dressing, and toilet use), and mood (severity score, anti-anxiety medications, antidepressants, and antipsychotics) features contributed the most. Meaning, stroke survivors who received fewer therapy hours, were less independent, and had a worse overall mood were at a greater risk of having a post-infection seizure.</p><p dir="ltr">The development of a tool to predict recurrent stroke and post-infection seizure in stroke survivors can be interpreted by providers to guide treatment and rehabilitation to prevent complications long-term. This promotes individualized plans that can increase the quality of resident care.</p>

Little is known regarding registered nurse (RN) information management practice in long-term care (LTC) settings. This study identifies LTC RNs’ information management practice and needs, which are important for designing and implementing health information technology (HIT) in LTC settings. Methods: This descriptive qualitative study combines direct observations and semi-structured interviews, conducted at Alberta’s LTC facilities between May 2014 and August 2015. The constant comparative method of joint coding was used for data analysis. Results: Nine RNs from six nursing homes participated in the study. Based on the RNs’ existing information management system requirements, a graphic information flow model was constructed. Conclusion: This baseline study identified key components of LTC RNs’ information management system. The information flow model may assist HIT developers with future design and development of HIT solutions for LTCs, serve as a communication tool between RNs and developers to refine requirements and support further LTC HIT research. / Graduate

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