The Digital Patient: Advancing Healthcare, Research, and Education: An interview with the authors


  • Author: Statistics Views
  • Date: 10 Feb 2016

This month, Wiley is proud to publish The Digital Patient: Advancing Healthcare, Research, and Education, which is a  modern guide to computational models and constructive simulation for personalized patient care using the Digital Patient.

The healthcare industry’s emphasis is shifting from merely reacting to disease to preventing disease and promoting wellness. Addressing one of the more hopeful Big Data undertakings, The Digital Patient: Advancing Healthcare, Research, and Education presents a timely resource on the construction and deployment of the Digital Patient and its effects on healthcare, research, and education. The Digital Patient will not be constructed based solely on new information from all the “omics” fields; it also includes systems analysis, Big Data, and the various efforts to model the human physiome and represent it virtually.

The Digital Patient: Advancing Healthcare, Research, and Education addresses the international research efforts that are leading to the development of the Digital Patient, the wealth of ongoing research in systems biology and multiscale simulation, and the imminent applications within the domain of personalized healthcare. Chapter coverage includes:

  • The visible human
  • The physiological human
  • The virtual human
  • Research in systems biology
  • Multi-scale modeling
  • Personalized medicine
  • Self-quantification
  • Visualization
  • Computational modeling
  • Interdisciplinary collaboration

The Digital Patient: Advancing Healthcare, Research, and Education is a useful reference for simulation professionals such as clinicians, medical directors, managers, simulation technologists, faculty members, and educators involved in research and development in the life sciences, physical sciences, and engineering. The book is also an ideal supplement for graduate-level courses related to human modeling, simulation, and visualization.

Statistics Views talks to Co-Editor C. Donald Combs about this innovative new work.

thumbnail image: The Digital Patient: Advancing Healthcare, Research, and Education: An interview with the authors

1. Congratulations on the publication this month of the book The Digital Patient: Advancing Healthcare, Research, and Education which aims to provide a modern guide to computational models and constructive simulation for personalized patient care using the Digital Patient. How did the writing process begin?

We are all actively involved in the modelling and simulation community and intensely interested in how M&S can be more fully utilized to improve healthcare and health. Our research led us to the EU effort to develop a virtual human and that in turn led to our thinking it would be useful to assemble writings from an internationally diverse group of scholars currently working on topics related to the building of a digital database and a complex, interrelated series of human models.

2. What were your main objectives during the writing process?

To assemble as many of the leading international M & S scholars as possible and to get them to focus on providing state-of-the-art chapters on where things stand at the moment and where they are headed in terms of constructing a platform that could lead to the realization of the digital patient. In Dickens’ A Christmas Carol, he describes the inevitable intertwining of past, present and future in a hopeful homily. Imagine if we could all, without the ghosts, have the opportunity to revisit our past, understand clearly how it affects the present, and realize that the future can be changed into a more rounded, healthier human experience. In its essence, that is what the Digital Patient entails—the development of an evolving foundation for a better future in terms of personal and population health, in the validity of biological and social research, and in the development of more effective drugs and devices.

3. The book is described as being realized through the purposeful collaboration of patients as well as scientific, clinical, and policy researchers, from both their own research and through the development of an effective framework into which their research will fit. Please could you give us an example of such collaboration within the book?

Well, the chapter on self-quantification provides a good example of the steps individuals are taking to gather accurate, time-series data on their own physiology and health status with the aim of maintaining their health and detecting health threats at the earliest (and most treatable) time possible. There is, in fact, a worldwide movement of individuals pursuing self-quantification. The broader challenge is that the effort of individuals needs to be aggregated and integrated with other data if we are to realize the potential of the digital patient.

4. The book also addresses the international research efforts that are leading to the development of the Digital Patient, the wealth of ongoing research in systems biology and multi-scale simulation, and the imminent applications within the domain of personalized healthcare. Could you please tell us how the chapter breakdown works to cover such topics?

We organized the book in three main sections—vision, state of the art, and challenges. That organization seems well-suited to the topic. What is the Digital Patient and how can it help us, both individually and collectively, to have better health and more effective healthcare? Where do we stand in the cycle of development of the Digital Patient—what research is on-going, what areas are lacking, how are the pieces being assembled, from the molecular to the social environment of individual patients, what efforts are being made to ensure validity and reliability of the models, how much uncertainty remains and is tolerable? What challenges need to be addressed and what are the most likely to be effective ways to proceed?

5. If there is one piece of information or advice that you would want your reader to take away and remember after reading your book, what would that be?

The emerging era of Big Data provides an exceptional opportunity to customize diagnosis and treatment of disease, to improve the effectiveness of healthcare delivery, to integrate a multitude of different data sources, and to develop a digital patient (really an infinite number of them) that can not only mirror each of us individually, but also the particular social groups in which we live. The Digital Patient will not be constructed based solely on new information from all the “omics” fields, from the various efforts to model the human physiome and represent it virtually, from systems analysis, or from Big Data. It will only be realized through the purposeful collaboration of researchers (whether they are patients or scientific, clinical, or policy researchers) on both their own research and the framework into which their research will fit. The Digital Patient will continue to depend on the efforts of a wide variety of individual researchers and modellers across many disciplines worldwide. It is inevitably an emergent phenomenon, governable only by sustained cooperation among those with an interest in its development and with guiding principles of openness, flexibility, rigorous validation and reliability processes, and respect for patient privacy. Realizing the tremendous potential of the Digital Patient is, as this concluding discussion has shown, going to be difficult, requiring us, as Thompson implies, to quickly set about deducing how the Digital Patient can be completed and used to help us work, meditate and create health as envisioned by the World Health Organization. The chapters in this book collectively serve as the basis for our understanding of the collaborative research agenda for constructing the Digital Patient.

The Digital Patient research agenda requires the establishment of an enduring, voluntary collaborative mechanism, much like the W3 Consortium governing the web, that involves an academically broad, international cadre of researchers, patients and clinicians capable, over time, of addressing the fundamental challenges identified in this chapter: taxonomic clarity, useable ontologies, protection of privacy, integration of data and models with differing temporal and spatial characteristics, standards, and a process for accrediting the validity and reliability of the constituent models of the Digital Patient.

6. Who should read the book and why?

Anyone interested in their personal health, in Big Data, in modelling and simulation, and in using analytics to improve drug and device development as well as the efficacy of population health initiatives. Historically, understanding in detail and with certainty what is going on within the human body has been an elusive quest. Partial glimpses and general understanding are the best we have been able to do with the data we have at our disposal and within the limitations of population-normed theories of what the data mean for the diagnosis and treatment of individuals. In the not-too-distant future, however, that will change as the Digital Patient is developed. The capacity to measure one’s personal physiological and social metrics, compare those metrics with the metrics of millions of other humans, personalize needed therapeutic interventions and measure the resulting changes will realize the vision of personalized medicine. The capacity to aggregate and integrate data from millions of individuals will provide a means to improve health across populations with differing cultures and behaviours.

7. Why is this book of particular interest now?

Now is the pivot point where we can decide to work more effectively to realize the Digital Patient in the next 15-20 years versus continuing to work more or less alone and only realize the Digital Patient potential in 50 years and then only in part.

8. Were there areas of the book that you found more challenging to write, and if so, why?

It is always challenging to write about technically complex topics in a manner that balances accuracy and sophistication with readability. So, trying to ground the more technical chapters on multi-scale modelling in a way that is clearly relevant to the health of individuals and to the practice of healthcare on a daily basis proved challenging.

9. What is it about the area of advancing healthcare that fascinates you?

We all have an interest in ensuring that healthcare continues to improve, meaning that the likelihood of any particular treatment applied to any particular patient actually working grows. That is sadly not often the case today where most treatments have less than a fifty per cent chance of being successful for any particular patient.

10. Professors Sokolowski and Banks have also written many other books for Wiley including Modeling and Simulation in the Medical and Health Sciences and the Handbook of Real-World Applications in Modeling and Simulation. What will be your next book-length undertaking?

We are going to take a break after having done six books in the last decade. Dr. Combs is considering whether to write a follow-on book laying out a realizable roadmap toward the digital patient that identifies the things to be done and who is best suited to do them.

11. Please could you tell us more about your individual backgrounds and what inspired you to pursue your careers in your chosen subject areas?

C. Donald Combs, Ph.D. serves as Vice President and Dean, School of Health Professions, at the Eastern Virginia Medical School (EVMS). His responsibilities include collaborative partnerships, oversight of EVMS’ regional and specialty accreditation compliance programs and all health professions degree programs as well as medical modeling and simulation activities, program development, governmental and community relations, and educational outreach programs. Dr. Combs holds faculty appointments as tenured Professor of Health Professions at EVMS, Professor of General Medicine at the State Medical and Pharmaceutical University “Nicolae Testemitsanu”, Visiting Professor of Medical Simulation at University of Paris—Descartes and as Adjunct Professor of Modeling, Simulation and Visualization Engineering at Old Dominion University. From 1996 to 2002, he also served as a Senior Fellow at the U.S. Naval Postgraduate School.
He has long-standing research interests in health and human services management, peer review and accreditation, educational program development, health services research, health professions regulation, strategic planning, and medical modeling and simulation. During the past decade he has worked with a number of academic health centers in the areas of faculty workload, accreditation, and strategic planning. He currently serves on several regional, state, and national boards and task forces that address national and international issues, including the Society for Simulation in Healthcare (SSIH), the National Modeling and Simulation Coalition (NMSC), and the Society for Computer Simulation. In the international arena, Dr. Combs has worked with colleagues at the Naval Postgraduate School to develop and implement the International Health Resource Management executive education program that served some 20 nations, including Moldova, Bulgaria, Macedonia, Nepal, Botswana and El Salvador.

John A. Sokolowski, Ph.D. is the Executive Director of the Virginia Modeling, Analysis and Simulation Center and Associate Professor of Modeling, Simulation, and Visualization Engineering, both at Old Dominion University. He has been with the Center since 2001 and previously served as its Director of Research. He holds a Bachelor of Science in Computer Science from Purdue University, a Master of Engineering Management from Old Dominion University (ODU), and a Ph.D. in Engineering with a Concentration in Modeling and Simulation also from ODU. His research interests include human behavior modeling, decision system modeling, multiagent system simulation, and modeling and simulation representation of social systems. He has published five books on modeling and simulation and is the author of numerous journal articles and conference papers. He is a member of the Society for Modeling and Simulation International (President), American Association of Artificial Intelligence, Association of Computing Machinery, Phi Kappa Phi, and Phi Beta Kappa.
Catherine M. Banks, PhD, is Research Associate Professor at the Virginia Modeling, Analysis, and Simulation Center (VMASC) at Old Dominion University. Dr. Banks received her Ph.D. in International Studies at Old Dominion University in Norfolk, Virginia. She is working on two medical training tools: an ultrasound simulator trainer and a tablet app for teaching patient blood management. Her research also includes modeling states and their varied histories of revolution and insurgency, political economy and state volatility, and human behavior/ human modeling with applications in population displacement and insider threat. Dr. Banks is the co-editor of Principles of Modeling and Simulation: A Multidisciplinary Approach published in 2009; co-author of Modeling and Simulation for Analyzing Global Events published in 2009; co-editor of Modeling and Simulation Fundamentals: Theoretical Underpinnings and Practical Domains published in 2010; and co-editor of Modeling and Simulation for Medical and Health Sciences published in 2011.

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