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Effective Document and Data Management illustrates the operational and strategic significance of how documents and data are captured, managed and utilized. Without a coherent and consistent approach the efficiency and effectiveness of the organization may be undermined by less poor management and use of its information. The third edition of the book is restructured to take this broader view and to establish an organizational context in which information is management. Along the way Bob Wiggins clarifies the distinction between information management, data management and knowledge management; helps make sense of the concept of an information life cycle to present and describe the processes and techniques of information and data management, storage and retrieval; uses worked examples to illustrate the coordinated application of data and process analysis; and provides guidance on the application of appropriate project management techniques for document and records management projects. The book will benefit a range of organizations and people, from those senior managers who need to develop coherent and consistent business and IT strategies; to information professionals, such as records managers and librarians who will gain an appreciation of the impact of the technology and of how their particular areas of expertise can best be applied; to system designers, developers and implementers and finally to users. The author can be contacted at curabyte@gmail.com for further information.

This IBM Redbooks publication describes a sample implementation of a complex solution that addresses a key challenge being faced by many enterprises today. Document and record management has always been a difficult (and often manual) process. Enterprises need to address this challenge, not only to make their business, employees, partners, and customers more efficient, but also to comply with ever-increasing regulations.Addressing these requirements demands a flexible solution that can be integrated with current and future IT systems and applications. It is also critical that it is driven through controllable and automated business processes.This book describes a sample solution that integrates IBM DB2 Records Manager, IBM DB2 Content Manager, IBM WebSphere Application Server Enterprise Process Choreographer, IBM WebSphere Portal, IBM Tivoli Directory Server, and other software to provide a prototype solution. Though basic in its function, the solution and the steps to implement it can be used to help architects, IT specialists, and developers get started in creating a solution addressing their enterprise-specific requirements.

Effective Document and Data Management illustrates the operational and strategic significance of how documents and data are captured, managed and utilized. Without a coherent and consistent approach the efficiency and effectiveness of the organization may be undermined by less poor management and use of its information. The third edition of the book is restructured to take this broader view and to establish an organizational context in which information is management. Along the way Bob Wiggins clarifies the distinction between information management, data management and knowledge management; helps make sense of the concept of an information life cycle to present and describe the processes and techniques of information and data management, storage and retrieval; uses worked examples to illustrate the coordinated application of data and process analysis; and provides guidance on the application of appropriate project management techniques for document and records management projects. The book will benefit a range of organizations and people, from those senior managers who need to develop coherent and consistent business and IT strategies; to information professionals, such as records managers and librarians who will gain an appreciation of the impact of the technology and of how their particular areas of expertise can best be applied; to system designers, developers and implementers and finally to users. The author can be contacted at curabyte@gmail.com for further information.

Blockchain is a shared distributed digital ledger technology that can better facilitate data management, provenance and security, and has the potential to transform healthcare. Importantly, blockchain represents a data architecture, whose application goes far beyond Bitcoin – the cryptocurrency that relies on blockchain and has popularized the technology. In the health sector, blockchain is being aggressively explored by various stakeholders to optimize business processes, lower costs, improve patient outcomes, enhance compliance, and enable better use of healthcare-related data. However, critical in assessing whether blockchain can fulfill the hype of a technology characterized as ‘revolutionary’ and ‘disruptive’, is the need to ensure that blockchain design elements consider actual healthcare needs from the diverse perspectives of consumers, patients, providers, and regulators. In addition, answering the real needs of healthcare stakeholders, blockchain approaches must also be responsive to the unique challenges faced in healthcare compared to other sectors of the economy. In this sense, ensuring that a health blockchain is ‘fit-for-purpose’ is pivotal. This concept forms the basis for this article, where we share views from a multidisciplinary group of practitioners at the forefront of blockchain conceptualization, development, and deployment.

We use a social contagion lens to study the dynamic, temporal process of the diffusion of electronic medical records in the population of U.S. hospitals. Social contagion acknowledges the mutual influence among organizations within an institutional field and implicates information transmission through direct contact and observation as the mechanisms underlying influence transfer. We propose hypotheses predicting a hospital's likelihood of adopting electronic medical records as a function of its susceptibility to the influence of prior adopters, the infectiousness or potency of influence exerted by adopting hospitals, and its social and spatial proximity to prior adopters. Results obtained by fitting a heterogeneous diffusion model to data from a sample drawn from an annual survey, spanning 1975 to 2005, of almost 4,000 U.S. hospitals suggest that diffusion can be accelerated if specific attention is given to increasing social contagion effects. In particular, with respect to susceptibility to influence, greater hospital size and age are positively related to the likelihood of adoption for nonadopters, whereas younger hospitals are associated with greater infectiousness for adopters. A hospital's \"celebrity\" status also contributes to its infectiousness. We further find strong effects for social proximity and significant regional effects for spatial proximity and hospital size, suggesting that geographical covariates should be included in diffusion studies. Results also reinforce the importance of theorizing about and including interactions in examinations of social contagion.

This book was written to demystify critical standards related to information security, records management privacy information management for the modern librarian and archival professional. In the digital age, librarians and archival professionals play a crucial role in safeguarding the world's knowledge. A Librarian's Guide to ISO Standards for Information Governance, Privacy, and Security is a curated resource for librarians, presenting core ISO standards related to information governance, data privacy, and security. The book provides detailed summaries of these standards, along with case studies and advice on applying them in the modern digital age. It empowers library staff and patrons to prioritize data security and privacy, ensuring trust and confidentiality in their services. The purpose is to demystify critical standards related to information security, records management privacy information management for the modern librarian and archival professional. Inside, you will find detailed summaries of the core ISO standards, descriptions, and case studies illustrating how these standards can apply to librarians in the modern digital age, advice on how to cultivate a culture of data security, and privacy awareness among library staff and patrons.

With the expansion of technology and governance, the information governance industry has experienced dramatic and often, sudden changes. Among the most important shifts are the proliferation of data privacy rules and regulations, the exponential growth of data and the need for removing redundant, obsolete, and trivial information and the growing threat of litigation and regulatory fines based on a failure to properly keep records and manage data. At the same time, longstanding information governance standards and best practices exist, which transcend the sudden vicissitudes of the day. This volume focuses on these core IG principles, with an emphasis on how they apply to our target audience, which includes law librarians, legal and research staff and other individuals and departments in both the public and private sectors who engage deeply with regulatory compliance matters. Core topics that will be addressed include: * the importance of implementing and maintaining cohesive records management workflows that implement the classic principles of capturing, checking, recording, consolidation, and review; * the classic records management principles of Accountability, Transparency, Integrity, Protection, Compliance, Accessibility, Retention and Disposition; and * archives Management and the two principles of Providence and Original Order.

Purpose Drawing on the resource-based theory and dynamic capability view, this paper aims to examine the mechanisms by which business analytics (BA) capabilities (i.e. the effective use of data aggregation, analytics and data interpretation tools) in healthcare units indirectly influence decision-making effectiveness through the mediating role of knowledge absorptive capacity. Design/methodology/approach Using a survey method, this study collected data from the hospitals in Taiwan. Of the 155 responses received, three were incomplete, giving a 35.84 per cent response rate with 152 valid data points. Structural equation modeling was used to test the hypotheses. Findings This study conceptualizes, operationalizes and measures the BA capability as a multi-dimensional construct that is formed by capturing the functionalities of BA systems in health care, leading to the conclusion that healthcare units are likely to obtain valuable knowledge through using the data analysis and interpretation tools effectively. The effective use of data analysis and interpretation tools in healthcare units indirectly influence decision-making effectiveness, an impact that is mediated by absorptive capacity. Originality/value This study adds values to the literature by conceptualizing BA capabilities in healthcare and demonstrating how knowledge absorption matters when implementing BA to the decision-making process. The mediating role of absorptive capacity not only provides a mechanism by which BA can contribute to decision-making practices but also offers a new solution to the puzzle of the IT productivity paradox in healthcare settings.

This paper quantifies the effect of state privacy regulation on the diffusion of electronic medical records (EMRs). EMRs allow medical providers to store and exchange patient information using computers rather than paper records. Hospitals may be more likely to adopt EMRs if they can reassure patients that their confidentiality is legally protected. Alternatively, privacy protection may inhibit adoption if hospitals cannot benefit from easily exchanging patient information. We find that state privacy regulation restricting hospital release of health information reduces aggregate EMR adoption by hospitals by more than 24%. We present evidence that suggests that this is due to the suppression of network externalities.

The use of Electronic Health Records (EHR)/Electronic Medical Records (EMR) data is becoming more prevalent for research. However, analysis of this type of data has many unique complications due to how they are collected, processed and types of questions that can be answered. This book covers many important topics related to using EHR/EMR data for research including data extraction, cleaning, processing, analysis, inference, and predictions based on many years of practical experience of the authors. The book carefully evaluates and compares the standard statistical models and approaches with those of machine learning and deep learning methods and reports the unbiased comparison results for these methods in predicting clinical outcomes based on the EHR data. Key Features: Written based on hands-on experience of contributors from multidisciplinary EHR research projects, which include methods and approaches from statistics, computing, informatics, data science and clinical/epidemiological domains. Documents the detailed experience on EHR data extraction, cleaning and preparation Provides a broad view of statistical approaches and machine learning prediction models to deal with the challenges and limitations of EHR data. Considers the complete cycle of EHR data analysis. The use of EHR/EMR analysis requires close collaborations between statisticians, informaticians, data scientists and clinical/epidemiological investigators. This book reflects that multidisciplinary perspective.