55,900 research outputs found

    Healthcare Analytics Leadership: Clinical & Business Intelligence Plan Development

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    Future healthcare leaders require expert knowledge and practical capabilities in the evaluation, selection, application and ongoing oversight of the best types of analytics to create continuous learning healthcare systems. These systems may result in continuously improving the demonstrable quality, safety and efficiency of healthcare organizations. Data is an asset for organizations. However, many companies do not know how to establish analytical road maps for future action. Population Health Intelligence describes a new discipline whose role is to collect, organize, harmonize, analyze, disseminate and act upon the data available to clinicians, health system leaders, the pharmaceutical and biotechnology industry, and healthcare payers. This webinar on Analytics Leadership will demonstrate how to create and implement Clinical & Business Intelligence Plans that transform data into actionable organizational insights. Agenda Introduction Healthcare Analytics Leadership: Clinical & Business Intelligence Plan Development Population Health Intelligence Presentation: 53:3

    Big data analytics in the healthcare industry: A systematic review and roadmap for practical implementation in Nigeria

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    Introduction: The introduction of digitization of healthcare data has posed both challenges and opportunities within the industry. Big Data Analytics (BDA) has emerged as a powerful tool, facilitating data-driven decision-making and revolutionizing patient care. Purpose: The research aimed to analyze diverse perspectives on big data in healthcare, assess BDA's application in the sector, examine contexts, synthesize findings, and propose an implementation roadmap and future research directions. Methodology: Using an SLR protocol by Nazir et al. (2019), sources like Google Scholar, IEEE, ScienceDirect, Springer, and Elsevier were searched with 18 queries. Inclusion criteria yielded 37 articles, with five more added through citation searches, totaling 42. Results: The study uncovers diverse healthcare viewpoints on big data's transformative potential, precision medicine, resource optimization, and challenges like security and interoperability. BDA empowers clinical choices, early disease detection, and personalized medicine. Future areas include ethics, interpretable AI, real-time BDA, multi-omics integration, AI-driven drug discovery, mental health, resource constraints, health disparities, secure data sharing, and human-AI collaboration. Conclusion: This study illuminates Big Data Analytics' transformative potential in healthcare, revealing diverse applications and emphasizing ethical complexities. Integrated data analysis is advocated for patient-centric services. Recommendation: Balancing BDA's power with privacy, guidelines, and regulations is vital. Implementing the Nigerian healthcare roadmap can optimize outcomes, address challenges, and enhance efficiency. Future research should focus on ethics, interpretable AI, real-time BDA, and mental health integration

    A Tutorial on Using Qlik Analytics Platform for Business Analytics

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    Business Analytics focuses on how businesses, non-profits, and governments use data to gain insights and improve organizational decision-making skills. Due to an increasing availability of large data sets from a variety of sources (Big Data), employees with business analytic skills are in-demand in many industries throughout the world. There are numerous analytics platforms that can be brought into the classroom to introduce students to business analytics concepts. The goal of this tutorial is to familiarize the audience with key aspects of using the Qlik (pronounced Click ) analytics platform - one of the leading commercial business analytics tools on the market according to Gartner\u27s 2018 Magic Quadrant for analytics and business intelligence platforms (Howson, Sallam, & Richa, 2018). The tutorial will be organized into 3 parts: (1) discussion of pros and cons of the top 3 business intelligence platforms - Microsoft\u27s Power BI, Tableau, and Qlik, (2) brief introduction to Qlik and a quick review of its functionality, and (3) a hands-on walk through of an exemplar class project using simple linear regression on healthcare insurance data. The tutorial will conclude with best practices and suggestions for incorporating the Qlik Analytics platform into information systems curriculum at the undergraduate and graduate level

    Necessity of Analytics in Today’s Healthcare Revenue Cycle

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    Because of the recently growing pressures to improve quality and reduce costs, healthcare organizations are rapidly adopting IT in order to improve their operations and clinical care. As a result, an accumulation of vast amounts of data are becoming available for use. It is important for healthcare to use this data. Strome (2010) states that healthcare analytics is the application of statistical tools and techniques to healthcare-related data in order to study past situations (i.e., operational performance or clinical outcomes) to improve the quality and efficiency of clinical and business processes and performance. With the introduction of healthcare analytical tools, can the healthcare industry take its huge and exponentially growing amounts of data and learn from it? The purpose of this paper is to review the available literature on the use of analytical tools in the healthcare industry with a focus on the revenue cycle. Most literature available to be reviewed is centered around discussions and theories on the use of analytical tools in the industry. A survey of revenue cycle leaders was conducted to determine the prevalence and importance of analytical tools in conjunction with the revenue cycle. This information will be valuable to revenue cycle leaders in determining if others in the industry are adopting these tools and the potential benefits of using analytical tools in their own departments

    Healthcare Data Analytics on the Cloud

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    Meaningful analysis of voluminous health information has always been a challenge in most healthcare organizations. Accurate and timely information required by the management to lead a healthcare organization through the challenges found in the industry can be obtained using business intelligence (BI) or business analytics tools. However, these require large capital investments to implement and support the large volumes of data that needs to be analyzed to identify trends. They also require enormous processing power which places pressure on the business resources in addition to the dynamic changes in the digital technology. This paper evaluates the various nuances of business analytics of healthcare hosted on the cloud computing environment. The paper explores BI being offered as Software as a Service (SaaS) solution towards offering meaningful use of information for improving functions in healthcare enterprise. It also attempts to identify the challenges that healthcare enterprises face when making use of a BI SaaS solution

    Data analytics based positioning of health informatics programs

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    The Master of Science in Computer Information Systems (CIS) with concentration in Health Informatics (HI) at Metropolitan College (MET), Boston University (BU), is a 40-credit degree program that are delivered in three formats: face-to-face, online, and blended. The MET CIS-HI program is unique because of the population of students it serves, namely those interested in gaining skills in HI technology field, to serve as data analysts and knowledge-based technology drivers in the thriving health care industry. This set of skills is essential for addressing the challenges of Big Data and knowledge-based health care support of the modern health care. The MET CIS-HI program was accredited by the Commission on Accreditation for Health Informatics and Information Management Education (CAHIIM) in 2017
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