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No description available.

Studies suggest that the majority of hospital errors go unreported. Equally disturbing is that data surrounding near miss events that could have harmed patients has been found to be even sparser. At the core of any medical error reporting effort is a desire to obtain data that can be used to reduce the frequency of errors, reveal the cause of errors, and empower those involved in the healthcare delivery system with the insight required to design methods to prevent the flaws that allow mistakes to occur. Aligned with the adage that “we can’t fix what we don’t know is broke”, the question is raised why does underreporting exist? The likelihood of reporting medical errors is explored as a manifestation of culture. Factors studied include communication and feedback, teamwork, fear of retribution, and leadership support (top management and supervisor). Data is presented using a nationally recognized instrument—the Agency for Healthcare Research and Quality (AHRQ) Culture of Safety survey. Findings from the research are mixed with little positive relationship between the model and number of events reported although each factor is found to be positively associated with an employee’s perceived frequency by which near miss and no harm events are reported. While advances in patient safety have materialized, the act of employees’ actually reporting events still pales in comparison to the number of errors that have likely occurred, regardless of efforts to advance culture. To explore influencers beyond those found in the AHRQ Culture of Safety survey, an overlapping model is presented. This includes studying various underlying factors, such as understanding what constitutes a reportable event, ease of reporting, and knowledge of the processes supporting data submission, along with attempting to better assess the impact of the direct supervisor and incentives in influencing behavior. Findings suggest that these additional factors do contribute, albeit modestly, to the act of reporting errors. When adding tenure and patient interaction to the model, a higher percentage of the variance is explained. In terms of perceived frequency of reporting near misses and no harm events, this model yields similar results to the first, explaining approximately 28% of the variance. The two factors most positively associated with perceived frequency of reporting near miss and no harm events are communication and feedback and infrastructure —suggesting that some unexplored relationship may exist between the overlapping models. / Business Administration/Interdisciplinary

As the percentage of elderly adults within the U.S. continues to grow, long-term care options will increase. Facing increased competition from other forms of long-term care, many nursing homes are seeking innovative models to enhance management and clinical care practices. The Teaching Nursing Home model, first established in the 1970s, is one in which academic institutions partner with nursing homes to create information exchanges between the nursing home and the school. Currently, nursing schools throughout the country work with nursing homes to create clinical training sites for nursing students. The partnership is also used to encourage research among school faculty and to assist nursing homes in their management of best practices. This study examined the impact of these relationships on nursing home quality. Twenty teaching nursing homes were matched with twenty nursing homes that are not engaged in this practice. Using nursing home quality scores published by the Centers for Medicare and Medicaid Services, mean outcomes for the matched pairs were compared using T-tests. Regression analyses were also performed to test whether quality improves over time within a teaching nursing home. The results from the T-tests performed did not show overall quality differences between the matched pairs. However, when analyzed regionally, some significance was observed for teaching nursing homes in the Upstate NY region (p<0.1). The study discusses some of the differences in design of the teaching nursing homes within that region and the impact that may have on results. Time as a teaching nursing home did not appear to affect quality for nursing homes in this study. Possible explanations for these insignificant results are discussed in the Summary, Discussion and Limitations section of the study. Overall, the findings from this study suggest that the Teaching Nursing Home model can add value to nursing homes by offering them research and professional training opportunities with academic institutions. Within the study, recommendations are made to further explore the impact of these partnerships on nursing home quality and to encourage the development and use of the model through policy changes. / Business Administration

In the setting of the health care field, multiple decisions must be made on each patient’s care from a variety of viewpoints on the medical team. In these settings, Interprofessional Decision Making is becoming a tool that can incorporate shared decision making with the patients and multiple care team members’ goals in order to optimize and keep an ethical focus on clinical outcomes. By reviewing a patient case below and evaluating the body of literature at the present, it can be determined that a disassembly of the current medical hierarchical structure and the barriers to team based interaction it creates, with a move toward open and ethical interactions, collaborations, and discussions will result in shared consensus on a patients management and care. While this may be difficult to achieve, interventions such as multidisciplinary team building and medical training, prior to matriculation, may provide a foundation for improved Interprofessional Decision Making and overall collaboration. / Urban Bioethics

Undocumented immigrants in the United States currently do not have the same access to health care as their legal and citizen counterparts. This is wrong, and both state and national governments bear responsibility in remedying this situation by expanding policies to include them to protect their rights, especially undocumented immigrant children as a special vulnerable population. In order to demonstrate this, I will discuss the historical barriers that immigrants have encountered when trying to access to health care. I will review the laws and policies that have excluded them from welfare programs and inflicted fear into discouraging them from using what is available. I will examine the ways in which children have been treated at the Southern border detention centers and show evidence that they have been historically abused and traumatized at these facilities while the government continues to promote discrimination, injustice, and hostility in the ways that immigrants are portrayed and treated. I will explore the ethical problems surrounding these issues by considering ideas of influential philosophers and bioethicists regarding health care as a right for all and question the philosophical basis for treating undocumented immigrants differently than the rest of the population. With the support of international law and bioethics I will argue that children are a vulnerable population that deserves special protection regardless of immigration laws. Finally, I will discuss the importance of intervening in this situation and describe ways in which the government, health care providers, and the general population can all contribute to promoting equality for all. / Urban Bioethics

This research paper examines the innovation adoption of technology, specifically Artificial Intelligence (AI) implementations in hospitals by exploring the capabilities that enables AI innovations using the dynamic capabilities (sensing, seizing and reconfiguring) framework and clinicians’ intentions to use AI innovations for patient care by applying the technology adoption/acceptance framework Unified Theory of Acceptance and Use of Technology (UTAUT) utilizing qualitative case study analysis and quantitative survey methodology respectively. This multi-disciplinary research has considerable relevance to both healthcare business leaders and clinical practitioners by identifying the key factors that drives the decisions to adopt innovations to improve healthcare organizations' competitiveness to enhance patient care as well as to reduce overall healthcare costs. The main findings are: (1) On an organizational level, healthcare organizations with strong and versatile dynamic capabilities, who build on their existing knowledge and capabilities are better able to integrate the innovations into their internal operations and existing services. The identified barriers provide a clear sense of organizational barriers and resistance points for innovation adoption (2) On an individual level, the impact of quality of care and organization leadership support are the key factors that facilitates the adoption of innovation among the clinicians. (3) Current trends and key impact areas of AI technology in the healthcare industry are identified Key words: Innovation, Innovation Adoption, Dynamic Capabilities, Healthcare, Artificial Intelligence, AI, Technology, Strategic Management / Business Administration/Management Information Systems

People with dementia account for a growing number of patients requiring end-of-life medical care each year in the United States. The clinical application of bioethical principles is rarely more important than in the context of end-of-life decision making, and determining the appropriate clinical treatment plan can be difficult and complex for clinicians, patients, and medical proxies. While the current bioethical literature offers a wealth of information on the principles underlying ethical medical practice, real-world clinical scenarios are often fraught with confusion, complexity, and conflicting understandings of best practices. There is a need for clinical decision-making tools that are both comprehensive yet simple, and broadly-applicable enough to be clinically useful. This thesis explores the cultural factors that necessitate further discussion and understanding of the issues surrounding end-of-life care for people with dementia, uses a clinical case to demonstrate a real-world approach to the ethical complexities surrounding such care, and proposes a basic ethical decision-making algorithm with the potential for broad application by students and clinicians encountering complex ethical scenarios. / Urban Bioethics