What if the data could help predict the patient's prognosis, improve hospital operations or optimize human resources in medicine? The book is fresh from the shelves, “Health care analytics“It shows that this is already happening, and shows how to scale it.
Author by Dimitris Betsimas, Vice President of MIT Open Learning, along with two former Betsimas students – AGNI Orfanoudaki PhD '21, research on operational management at the University of Oxford Saïd Business School, as well as Holly Wiberg PhD '22 Analytyka. Emphasis on real use, the first part of the book establishes technical foundations-machinery and optimization-when the second part of the book presents integrated cases of cases that include various clinical specializations and types of problems using descriptive, predictive and order analysis.
Part of the wider series “The Analytics Edge in Healthcare” shows how to use data and models to make better decisions in the healthcare sector, and its predecessor “Edge of analytics“Neka in learning to use data to build models, improve decisions and add values ​​to institutions and people.
Betsimas, who is also a dean of business analytics and Boeing leaders in the global management professor at Mit Sloan School of Management, is an innovator behind him 15.071 (edge ​​of analysis)Open Learning's MIT course Mitx This attracted hundreds of thousands of students online and served as an inspiration for a series of books. Betsimas took a break from research and his work in the Open Learning myth to discuss how the field of analytics transforms the healthcare system and shares surprising ways of using analysis in hospitals.
Q: How does analytical field change the way hospitals provide care and manages their activities?
AND: As an academic, I have always tried to educate, write publications and use what we do in practice. That's why I founded Holistic hospital optimization (H20) In order to optimize hospital operations with machine learning to improve patient care. We have developed various tools in myth and implemented them in hospitals around the world. For example, we manage the length of patients' stay and their deterioration indexes (a computerized tool providing for the risk of clinical deterioration of the patient); We manage the optimization of a nurse and how hospitals can allocate human resources properly; And we optimize blocks for surgery. This is the beginning of a change in which analytical and AI methods are currently widely used. I hope that this work and this book will speed up the effect of using these tools.
In addition, I taught Nine -person course Twice from Agni and Holly at Hartford Hospital System, where I realized that these analytical methods – which are usually not taught in medical schools – can be demonstrated to doctors, including doctors, nurses and administrators. To influence, you must have the right methods, implement them and use them, but you also need to educate people on how to use them. This is well associated with my open learning role, where our goal is to educate students around the world. In fact, Open Learning begins this fall, Universal AI, dynamic online learning experience, which provides comprehensive knowledge of artificial intelligence, preparing the global audience of students to employ in our rapidly developing labor market.
Q: What are the surprising ways to use health care analysis that most people would not expect?
AND: Using the analyzes, we reduced the length of patients in the Hartford hospital from 5.67 days to five days. We have an algorithm that provides for the likelihood of releasing patients; That is why doctors prioritize patients with the highest probability, preparing them for discharge. This means that the hospital can treat many more patients and patients remain in the hospital less time.
In addition, when hospitals recorded a increase in the nurse's turnover during the Covid-19 pandemic, we have developed an analytical system that takes into account justice and honesty and reduces overtime, giving the preferred crevices of nurses and significantly reducing overall turnover. These are just two examples; There are many others in which the analytical prospect of healthcare and medicine made a significant difference.
Q: Looking to the future, how do you see artificial intelligence shaping the future of healthcare?
AND: In a very significant way – we use machine learning to make better forecasts, but generative artificial intelligence can explain them. I can see a move in this direction. This is really the evolution of artificial intelligence, which has enabled it and is exciting. It is also important for the world because of its possibilities of improving care and saving life.
For example, thanks to our program at Hartford Hospital System, we discovered that the patient is getting worse and predicted through analytics that it would be even worse. After our forecast, the doctors examined the patient more and discovered that the patient had an early sepsis, a life -threatening condition in which the body reacts improperly to an infection. If we had not detected sepsis before, the patient could die. This made a real difference in saving human life.
Q: If you had to describe the “edge of analytics in healthcare” in one or two words, what would be and why?
AND: The book is a stage transition in healthcare because it is able to influence the healthcare sector in a way that has not been made before. The book really presents my work in healthcare and its application in the last decade.
