Preface

As the quality, applicability, and speed of digital systems in healthcare continue to increase, and as costs continue to decrease, a myriad of advances in healthcare applications continue to appear. The wide adoption of large and complex electronic health record (EHR) systems by healthcare institutions along with the vast amount of publicly available medical information through the Internet have significantly increased public expectations for higher quality healthcare. In addition, the overwhelming flow of information through a variety of sources causes distractions and challenging situations for care provisioning. Fortunately, recent advances in science and technology, high-performance computing platforms, and more attention to social aspects of computing can help the situation. This book addresses such issues through scientific and practical solutions and future research pathways.

The scope of digital systems in healthcare spans telemedicine, homecare provisioning, life-support systems, and public health management. The success of these systems is highly dependent on the targeted specialty, the systems' accuracy and usability, and quality of information. The use of proper information technology, user experience, computing power, and Internet access has been challenged in the design of such systems. Recently, the influence and success of machine learning science and technologies empowered by fast computing cores have provided new opportunities to develop decision systems that will improve usefulness through more adoption and retention.

This volume includes chapters that elaborate on the success of decision systems in different sectors of healthcare and medical domains and report on a number of these advances. In the first section on Digital Technology for Healthcare Management, Chapter 1 by Lyons et al. reports on the implementation of a national home telehealth program by the US Veterans Health Administration, noted for its advanced use of digital systems to support veterans. In Chapter 2, Andrès et al. provide a review of technologies and non-invasive devices for optimal management of diabetes mellitus, chronic heart failure, and related comorbidities. In Chapter 3, Edoh discusses primary healthcare service delivery and accessibility through digital technologies. Finally, in Chapter 4, Taddei et al. outline the telemedicine network for pediatric cardiology that is in use throughout thirteen hospitals located in the Tuscany region in Italy.

In the second section on Clinical Decision Support Systems (CDSS), Chapter 5 by Littlejohn et al. addresses the need to use human factors engineering to improve CDSS human interfaces. In Chapter 6, Siu et al. report on an intelligent CDSS that helps care managers to develop plans for better quality care in-home and institutional elderly care. In Chapter 7, Roham et al. present a systematic review of big data visualization to support more informative user interactions with CDSS. The section ends with Chapter 8 in which Segura et al. describe a system that supports gathering data from multiple sources on infections caused by resistant bacteria. Their system provides decision support to multi-institutional teams for fighting these threats.

> **Kamran Sartipi** East Carolina University, USA

> > **Thierry Edoh** University of Bonn, Germany

> > > Section 1

Digital Technology for

Healthcare Management

Section 1
