Today, it is not uncommon for practices and hospitals to be on their second or third EHR and/or contemplating a transition from the traditional on-premise model to a cloud-based system. As a follow-up to Complete Guide and Toolkit to Successful EHR Adoption ( (c)2011 HIMSS), this book builds on the best practices of the first edition, fast-forwarding to the latest innovations that are currently leveraged and adopted by providers and hospitals. We examine the role that artificial intelligence (AI) is now playing in and around EHR technology. We also address the advances in analytics and deep learning (also known as deep structured or hierarchical learning) and explain this topic in practical ways for even the most novice reader to comprehend and apply. The challenges of EHR to EHR migrations and data conversions will also be covered, including the use of the unethical practice of data blocking used as a tactic by some vendors to hold data hostage. Further, we explore innovations related to interoperability, cloud computing, cyber security, and electronic patient/consumer engagement. Finally, this book will deal with what to do with aging technology and databases, which is an issue rarely considered in any of the early publications on healthcare technology. What is the proper way to retire a legacy system, and what are the legal obligations of data archiving? Though a lot has changed since the 2011 edition, many of the fundamentals remain the same and will serve as a foundation for the next generation of EHR adopters and/or those moving on to their second, third, fourth, and beyond EHRs.

Today, it is not uncommon for practices and hospitals to be on their second or third EHR and/or contemplating a transition from the traditional on-premise model to a cloud-based system. As a follow-up to Complete Guide and Toolkit to Successful EHR Adoption ( (c)2011 HIMSS), this book builds on the best practices of the first edition, fast-forwarding to the latest innovations that are currently leveraged and adopted by providers and hospitals. We examine the role that artificial intelligence (AI) is now playing in and around EHR technology. We also address the advances in analytics and deep learning (also known as deep structured or hierarchical learning) and explain this topic in practical ways for even the most novice reader to comprehend and apply. The challenges of EHR to EHR migrations and data conversions will also be covered, including the use of the unethical practice of data blocking used as a tactic by some vendors to hold data hostage. Further, we explore innovations related to interoperability, cloud computing, cyber security, and electronic patient/consumer engagement. Finally, this book will deal with what to do with aging technology and databases, which is an issue rarely considered in any of the early publications on healthcare technology. What is the proper way to retire a legacy system, and what are the legal obligations of data archiving? Though a lot has changed since the 2011 edition, many of the fundamentals remain the same and will serve as a foundation for the next generation of EHR adopters and/or those moving on to their second, third, fourth, and beyond EHRs.