The current revolution in software, and the regulations that have evolved to address it, have increasingly caused companies to turn to off-the-shelf software for electronic record keeping. Data captured in computerized systems must be as reliable, if not more so, than data on paper. Electronic Record Keeping: Achieving Compliance with 21 CFR Part 11 and 45 CFR Parts 160, 162, and 164 explores how to evaluate, select, implement, and document an e-system that will keep your organization in compliance. Covering Title 21 of the Code of Federal Regulations (CFR) Part 11 and the parallel, recently passed Title 45 CFR Parts 160, 162, and 164 of the Health Insurance Portability and Accountability Act (HIPAA), this book provides guidance for selecting, purchasing, installing, validating, and managing commercial off-the-shelf software for data collection and retention. It takes a number of years for industry standards for a new regulation to develop from dialog between companies and the regulating agency. These standards are in place for Part 11, which was passed into law in 1997. Healthcare providers who must implement electronic record keeping can learn how to best do it by understanding the parallel between the new HIPAA regulations and the industry standards for Part 11. Further, certain FDA-driven activities, such as patient record keeping in clinical trials, now must comply with the new HIPAA regs as well. To help companies achieve and maintain compliance, the authors cover audit trails, validation, documentation, training, and security and accountability. They discuss what the regulations say and what they mean. Compliance may be mandatory, but it also makes good business sense. Companies that are compliant will always be poised to move forward, and they will avoid the grief that comes from poor or faulty record keeping and documentation. This book gives you the tools you need to keep your company both compliant and competitive.

Whether you are brand new to data mining or working on your tenth predictive analytics project, "Commercial Data Mining" will be there for you as an accessible reference outlining the entire process and related themes. In this book, you'll learn that your organization does not need a huge volume of data or a Fortune 500 budget to generate business using existing information assets. Expert author David Nettleton guides you through the process from beginning to end and covers everything from business objectives to data sources, and selection to analysis and predictive modeling.

"Commercial Data Mining" includes case studies and practical examples from Nettleton's more than 20 years of commercial experience. Real-world cases covering customer loyalty, cross-selling, and audience prediction in industries including insurance, banking, and media illustrate the concepts and techniques explained throughout the book.
Illustrates cost-benefit evaluation of potential projects Includes vendor-agnostic advice on what to look for in off-the-shelf solutions as well as tips on building your own data mining tools Approachable reference can be read from cover to cover by readers of all experience levelsIncludes practical examples and case studies as well as actionable business insights from author's own experience