This book is dedicated to population health management and how it can be used to improve the health care and outcomes for patients with poly chronic conditions. The book uses an integrated approach guided by a transdisciplinary orientation that incorporates both a macro and a micro-theoretical framework for promoting population health management. Thus, policy decision makers can prioritize how limited resources can be used to optimize health service needs of the chronically ill and disabled in the nation as well as in the globe. The book also identifies appropriate applications of health information technology that can facilitate interoperability, data sharing and effective communication to ensure that applicable knowledge is derived from the available information. Multiple implications of population health management for poly chronic conditions suggest that concerted efforts in promoting preventive strategies can yield numerous benefits. Continuous improvement efforts through impact evaluation and a commitment to the adoption of the health information technology resources needed are also critical aspects of this process. Patients with poly chronic conditions have complex needs and are often high-utilizers of health services. Great potential exists to improve the health and health care of these individuals through improved coordination integrating multiple domains of the population health management approach. Population Health Management is needed now more than ever due to the current challenges facing the health care system that were not present in previous decades. This book points out strategic directions suggested by empirical evidence and experts' opinions on innovative care management solutions observed in many advanced countries.

Evidence-Based Health Care Management introduces the principles and methods for drawing sound causal inferences in research on health services management. The emphasis is on the application of structural equation modeling techniques and other analytical methods to develop causal models in health care management. Topics include causality, theoretical model building, and model verification. Multivariate modeling approaches and their applications in health care management are illustrated. The primary goals of the book are to present advanced principles of health services management research and to familiarize students with the multivariate analytic methods and procedures now in use in scientific research on health care management. The hope is to help health care managers become better equipped to use causal modeling techniques for problem solving and decision making. Evidence-based knowledge is derived from scientific replication and verification of facts. Used consistently and appropriately, it enables a health care manager to improve organizational performance. Causal inference in health care management is a highly feasible approach to establishing evidence-based knowledge that can help navigate an organization to high performance. This book introduces the principles and methods for drawing causal inferences in research on health services management.

As the public in the U.S. has grown increasingly concerned over the gaps in the health care system's attention to quality, and as the health care industry itself struggles for stability in a volatile environment, a historic opportunity presents itself. This book reviews a variety of quality monitoring approaches, identifies critical issues pertaining to assessment, measurement, implementation, and evaluation of quality initiatives, and suggests scientific approaches to put in place a core set of performance measures that reliably identify the value-added clinical and managerial behaviors in health care - for both quality and cost efficiency. The key to quality improvement has to focus on physicians and other health professionals. This book is designed to identify issues pertaining to health care quality and to formulate appropriate approaches for improving quality. It can be used by risk managers and hospital executives to guide their development, implementation, and evaluation of quality improvement programs.

As the public in the U.S. has grown increasingly concerned over the gaps in the health care system's attention to quality, and as the health care industry itself struggles for stability in a volatile environment, a historic opportunity presents itself. This book reviews a variety of quality monitoring approaches, identifies critical issues pertaining to assessment, measurement, implementation, and evaluation of quality initiatives, and suggests scientific approaches to put in place a core set of performance measures that reliably identify the value-added clinical and managerial behaviors in health care - for both quality and cost efficiency.

The key to quality improvement has to focus on physicians and other health professionals. This book is designed to identify issues pertaining to health care quality and to formulate appropriate approaches for improving quality. It can be used by risk managers and hospital executives to guide their development, implementation, and evaluation of quality improvement programs.

Evidence-Based Health Care Management introduces the principles and methods for drawing sound causal inferences in research on health services management. The emphasis is on the application of structural equation modeling techniques and other analytical methods to develop causal models in health care management. Topics include causality, theoretical model building, and model verification. Multivariate modeling approaches and their applications in health care management are illustrated. The primary goals of the book are to present advanced principles of health services management research and to familiarize students with the multivariate analytic methods and procedures now in use in scientific research on health care management. The hope is to help health care managers become better equipped to use causal modeling techniques for problem solving and decision making. Evidence-based knowledge is derived from scientific replication and verification of facts. Used consistently and appropriately, it enables a health care manager to improve organizational performance. Causal inference in health care management is a highly feasible approach to establishing evidence-based knowledge that can help navigate an organization to high performance. This book introduces the principles and methods for drawing causal inferences in research on health services management.