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A marketing analysis of how baby boomers can manage their chronic health conditions through digital health information technologiesNettleton, Laura Jeanne 15 July 2011 (has links)
This paper explores chronic health issues as it relates to baby boomers and their use of digital technology. After considering how baby boomers use mobile devices and Internet technologies and what types of information they seek out within these platforms, further examination is done on health related topics such as healthcare, health literacy, and chronic health conditions. In recognition of baby boomers' likely development of one chronic condition or multiple occurring ones (known as comorbidity), three new health technologies are analyzed based on their ability to help individuals manage their chronic conditions. From these three technologies, smart pills, the Health Journal for Pain, and lx Conversations, individual marketing plans are recommended according to how they will benefit baby boomers in regards to better self health management in later adulthood years. / text
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Digital transformation of the healthcare organizations: The resilience of developing countries post-Covid-19 : How digital transformation builds stronger resilience abilities for healthcare organizations in developing countries in the post-COVID-19 outbreak?An, Nguyen, Tuong, Ho, Hien, Bui January 2022 (has links)
Background: Covid-19 is disrupting the healthcare industry. Policies and regulatory changes in general necessitate adaptation from the healthcare industry, particularly those affecting the payment system, clients, and the environment. On the other hand, as policymakers around the world look to digital transformation to make healthcare systems more resilient, affordable, and accessible, a rare and remarkable opportunity for the information systems research community to leverage its in-depth knowledge to both advance theory and influence practice and policy has emerged. Problem discussion: The changes brought by Covid necessitate resilience in the healthcare industry, which most countries are not yet prepared for, as it will necessitate a large number of workers and effective policies for the recovery process in the post of Covid 19. Crucially, many people lack the resources to scale up health interventions as well as the financial resources to implement support measures and improve resilience. This research will answer the following considerable question, how can countries now build more resilient healthcare systems capable of withstanding pandemics? What role can technology play in these efforts? Purpose: The thesis will aim to discover how the healthcare industry in developing countries will be resilient as they digitize their operations in the post of Covid disruption situations. The finding in this research will be identified by the combination of the HIT framework following four major sectors of health information technology: financial, functional, user, and environmental, and the resilience capabilities such as anticipating, monitoring, responding, and learning. The result of the finding will be involved in chapter 4. Method: In this paper, a qualitative method was used to answer the research question. Inductive and deductive techniques were used to expand the research by moving from individual data to broader generalizations and ideas. The detail of all the methodology steps will be explained in chapter 3. First, we began with specific observations and measurements by interviewing organizations and individuals related to the healthcare industry in one highlighted developing country for the primary data and used reliable websites such as Google Scholar, Microsoft Academic, Academic databases, etc for the secondary data. Due to the limitation of the interview responses, we chose Vietnam as our sample. Then we started noticing the HIT strategies, then we went a step further with interpretation to explain these preliminary discoveries that we wanted to investigate, and finally ended up developing some general digital conclusions or theories. Conclusion: Putting these innovations in place now helps the healthcare sector build a stronger resilience health ability, allowing it to be better prepared for future peaks and valleys. In conclusion, some innovative technology solutions from HIT strategies have been proposed, such as the top-down governance system which has been used to support the leaders to reach all levels of government. Aside from that, the effectiveness of the information system's preparation and the role of the surveillance system are critical in the early stages of resilience. All of the detail from the HIT recommendation strategies will be explained in chapter 5.
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Data mining methods applied to healthcare problemsEspinoza, Sofia Elizabeth 02 July 2012 (has links)
Growing adoption of health information technologies is allowing healthcare providers to capture and store enormous amounts of patient data. In order to effectively use this data to improve healthcare outcomes and processes, clinicians need to identify the relevant measures and apply the correct analysis methods for the type of data at hand. In this dissertation, we present various data mining and statistical methods that could be applied to the type of datasets that are found in healthcare research. We discuss the process of identification of appropriate measures and statistical tools, the analysis and validation of mathematical models, and the interpretation of results to improve healthcare quality and safety.
We illustrate the application of statistics and data mining techniques on three real-world healthcare datasets. In the first chapter, we develop a new method to assess hydration status using breath samples. Through analysis of the more than 300 volatile organic compounds contained in human breath, we aim to identify markers of hydration. In the second chapter, we evaluate the impact of the implementation of an electronic medical record system on the rate of inpatient medication errors and adverse drug events. The objective is to understand the impact on patient safety of different information technologies in a specific environment (inpatient pediatrics) and to provide recommendations on how to correctly analyze count data with a large amount of zeros. In the last chapter, we develop a mathematical model to predict the probability of developing post-operative nausea and vomiting based on patient demographics and clinical history, and to identify the group of patients at high-risk.
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