Technology and data will save lives: analytics can help deliver improved healthcare - new book
Lives could be saved and treatment times cut, with data-driven decision-making, according to the book, written by an international team. Analytics Edge in Healthcare, was written for health professionals, policymakers and decision-makers, by Holly Wiberg from Carnegie Mellon University's Heinz College of Information Systems and Public Policy, Agni Orfanoudaki from the University of Oxford and their former academic supervisor, Dimitris Bertsimas, Vice Provost for Open Learning and Associate Dean of Business Analytics at MIT Sloan School Of Management.
"We have taught analytics in different executive environments and have seen first-hand the power of equipping industry domain experts with these tools to solve real-world problems. We want to bring this education into healthcare. And given the unique opportunities and challenges in the clinical setting, we saw a need to develop a new resource that introduces these methods in context, with tailored approaches and examples," said Wiberg.
"Our goal in writing this book was to bridge that gap. Every case study we present stems from our own research and collaborations in the field. These examples show how analytics can drive meaningful change in healthcare settings—and this book is our way of helping bring that vision to life," Orfanoudaki continued.
While many concerns have been voiced about the perceived detrimental impact of AI, on jobs and on consumers' experience, the team argues there is much to gain, for patients and clinicians, through the use of AI in healthcare management.
Not only could technology manage more effectively hospital bed and appointment allocation, potentially easing squeeze points in the system, but the use of data would result in improved treatment and better health outcomes.
The book includes case studies spanning clinical and operational applications with demonstrated practical impact. "Take transplant care in the U.S.—data-driven techniques helped the national transplant agency improve the fairness and efficiency of organ allocation. That translated into lives saved each year," said Orfanoudaki.
The team explained how these methods can also be used for care efficiency - with managing bed allocation or capacity managing.
"Optimisation and machine learning are being used to solve these classic operations problems that are not directly clinically oriented, but have far reaching implications for how smoothly a hospital runs, which impacts a patient's experience and outcomes," Wiberg said.
The book is packed with examples of how analytics have helped healthcare management, largely drawn from the author team's own work with collaborators across various health systems. The authors attribute their successful track record to these clinical partnerships, and they hope their book will enable similar opportunities for other teams.
Provided by Carnegie Mellon University's Heinz College
