A special salute to all healthcare professionals whom I have interacted personally with and those I have not. Your dedication to caring for the sick and trying to cure life-changing medical events continues to ignite my passion to solve healthcare challenges as they arise. Finally, to my wife and children, thank you for brightening my life every day and allowing me to share yours.
– Michael N. Lewis
First, I would like to recognize my co-author, Michael N. Lewis, for his passion and patience writing this book with me. Mike brings the deep knowledge and insightful experience to make this book relatable. Second, I would like to recognize you, the reader of this book. Thank you for your interest to learn and be the agent of change in the healthcare industry. I am contributing the book proceeds to worthy charities that focus on technology and science to improve the world, from fighting hunger to advocating education to innovating social change.
There are many people who deserve heartfelt credit for assisting me in writing this book. This book would have not happened without the ultimate support and guidance from my esteemed colleagues and devoted customers. A sincere appreciation to my colleagues who encouraged me to share my personal experience and helped me to stay focused on what's relevant.
I owe a huge amount of gratitude to the people who reviewed and provided input word by word, chapter by chapter, specifically Lauree Shepard, Clark Bradley, Paul Segal, and Michael Lewis. Reading pages of healthcare jargon, trying to follow my thoughts, and translating my words in draft form can be an overwhelming challenge but you did it with swiftness and smiles. Thank you for the fantastic input that helped me to fine-tune the content for the readers.
A sincere appreciation goes to James Taylor, all healthcare professionals, IT specialists, and business professionals whom I have interacted with over the years. You have welcomed me, helped me to learn, allowed me to contribute, and provided real intelligence for this book. Finally, to all my family (the Nguyen and Dang crew), the St. Francis Episcopalian sponsors, the Rotary Club (the Jones Family, the Veale Family) – all of whom have contributed to my success – I would not be where I am today without them. To my wife and children, thank you for being the love of my life and bringing light and purpose to my day.
– Tho H. Nguyen
DISCLAIMER
The views expressed in this book are those of the individual authors representing their own personal views and not necessarily the position of either of their employers.
Foreword
by James Taylor 1
I have been working with advanced analytics for nearly 20 years. The market has matured dramatically to the point where analytics, machine learning, and AI are now common topics of conversation in every industry. Once, analytic models were handcrafted for a few high-value scenarios. Now, companies are automating the creation of advanced analytics and using them to solve a wide range of problems. The time to develop and deploy advanced analytics has gone from months to seconds, even as the amount of data being analyzed has exploded. Every industry is focused on being more data-driven and healthcare is no exception.
Tho and I met many years ago through our work as faculty members of the International Institute for Analytics. We have a shared interest in the technologies and approaches of analytics and in how organizations can truly take advantage of their data.
Healthcare is an industry that impacts everyone throughout their life. New drugs, new treatments, and new understanding drives continual and rapid innovation. Yet even as healthcare technology and treatments get more effective, populations in many countries are struggling with older populations and an epidemic of obesity. Drug resistance is an increasing problem and costs continue to rise. The healthcare industry needs to find ways to use data to tackle these and many other challenges.
Healthcare organizations have a particular challenge when it comes to analytics. Healthcare data is uniquely complex and uniquely sensitive. It must capture the state of a complex, living person. It is only imperfectly digitized and much of it is image related, time series related, or both – hard classes of data to manage and analyze. It is also intensely personal, so its use is regulated and controlled to protect people's privacy and prevent health-related discrimination. Taking advantage of this data to reduce costs and improve outcomes is both essential and complex.
Over the years I have worked with hundreds of organizations that are using analytics to improve their decision-making. Like Tho and Mike, I have come to see that people and process are as essential as technology – perhaps even more so. Building cross-functional teams, engaging a broad set of skills, and having a process that focuses on decision-making are all necessary if analytic technology is to be applied effectively.
Take one healthcare provider I was working with recently. A technical team had developed some potentially useful analytic models. But working alone they could get no traction. We engaged clinical and operations staff in a discussion of the current decision-making. We applied design thinking and decision modeling to see how that decision might be improved with the analytic. With this shared understanding the technical team could see what a minimum viable product would require and could execute a series of Agile sprints to deliver it. People, process, and (analytic) technology.
With this book, Tho and Mike hope to show healthcare professionals how to transform their industry with data and analytics. Right from the start, they emphasize the importance of people, process, and technology – not just the coolest, newest technology. Real-world stories of healthcare problems addressed by insight-driven decisions show healthcare professionals what's possible and what technology exists. The stories help bring to life how analytics might create a more effective future state in healthcare.
The core chapters on People, Process, and Technology are full of great advice. There is a discussion of the skills needed, especially in analysis and business understanding. The need to invest in a wide range of roles (not just hire unicorns) and the importance of changes in sponsorship culture are emphasized. Three critical elements of process are discussed next. Design Thinking – something we find very effective in defining how analytics can improve decision-making – Lean and Agile. Our experience is that the hardest problem is defining the business problem so analytics can be applied effectively. As the authors point out, success therefore requires process change and the creation of a repeatable, sustainable playbook. The technology chapter gives a succinct but complete overview of available technology. All of this is pulled together into a framework for integrating people, process, and technology to drive culture change and move up the analytic maturity curve. The authors talk about the importance of focusing on data as an asset, bringing together cross-functional teams, providing clear leadership, and investing in growing analytic talent. All of this is illustrated with real-world case examples. A final chapter lays out what's coming and how will it change healthcare, especially the growth in sensors and devices connected through the Internet of Things, the growth of the cloud, and the adoption of artificial intelligence.
If you are a healthcare professional concerned about applying data and analytics to improve your organization, this book will give you valuable insights. The advice and framework will help you organize, recruit, train, and develop the data analytics capability you need.
Healthcare needs to become more data-driven, more analytic. This book will show you how.
NOTE
1 1 James is CEO and Principal