Sandeep Reddy
Sandeep is a certified medical informatician with a background in Medicine, Public Health and Healthcare Management. He is currently engaged in research in medical informatics and program evaluation.
Sandeep is a certified medical informatician with a background in Medicine, Public Health and Healthcare Management. He is currently engaged in research in medical informatics and program evaluation.
As the costs and resources of delivering health services have increased over the years, the importance of evaluating health services and interventions has become essential. An evaluation provides a systematic process of assessing the efficacy and efficiency of health services, including an assessment of their impact on beneficiaries, whether it be individuals or communities. Evaluation in the health sector includes the evaluation of burden disease where human and economic costs resulting from poor health are measured.In this book, various evaluation studies are detailed, providing an excellent resource for both evaluation practitioners and academics alike. The geographical range and variety of case studies showcase how evaluation has become integral for health service planning and assessment and to assist public health policy makers decide how to use limited resources to minimize burden and inequity. This book will act as a ready resource for both workers experienced in health service evaluation and those intending to learn about burden of disease of evaluation.
Go to the bookEdited by Sandeep Reddy
In recent years, there has been an amplified focus on the use of artificial intelligence (AI) in various domains to resolve complex issues. Likewise, the adoption of artificial intelligence (AI) in healthcare is growing while radically changing the face of healthcare delivery. AI is being employed in a myriad of settings including hospitals, clinical laboratories, and research facilities. AI approaches employing machines to sense and comprehend data like humans has opened up previously unavailable or unrecognised opportunities for clinical practitioners and health service organisations. Some examples include utilising AI approaches to analyse unstructured data such as photos, videos, physician notes to enable clinical decision making; use of intelligence interfaces to enhance patient engagement and compliance with treatment; and predictive modelling to manage patient flow and hospital capacity/resource allocation. Yet, there is an incomplete understanding of AI and even confusion as to what it is? Also, it is not completely clear what the implications are in using AI generally and in particular for clinicians? This chapter aims to cover these topics and also introduce the reader to the concept of AI, the theories behind AI programming and the various applications of AI in the medical domain.
Part of the book: eHealth