When Technology, Policy, and the Urgency to Change Converge
Our new book, The Digital Reconstruction of Healthcare, is about to be published by Taylor and Francis, as part of its HIMSS book series. We wanted to give readers a preview of what’s to come so we are posting the Preface of the book ahead of time.
In our last two books, we began the conversation discussing the power of words, including misdiagnosis, cynicism, and optimism.1,2 In this book, our focus is on reconstruction, and all its implications for healthcare. To some, it might suggest the tearing down of an existing structure, a complete replacement of the healthcare ecosystem as we know it. Neither of us believe that’s warranted. Our goal, instead, is to address the unsustainable situation that we currently face in the United States and around the globe, and the emerging digital tools that are transforming patient care.
These solutions are not intended to demolish the foundation upon which medicine is built, but neither are they designed to patch up crumbling walls or apply duct tape to the ineffective, cost-prohibitive practices currently in place. To extend the metaphor: The foundation of healthcare may remain solid but many of the walls, floors, windows, and doors that sit on this foundation are rotting and need to be replaced. The next eight chapters will provide evidence from multiple sources, including deep learning specialists, consultations with thought leaders and government officials around the world, peer-reviewed studies, unpublished data, and cutting edge initiatives at Mayo Clinic and several other healthcare leaders — in addition to our combined 60+ years of experience working in healthcare. The preponderance of evidence from all these sources makes a compelling argument: Business as usual is no longer an option; the digital reconstruction of healthcare is no longer on the world’s wish list. It’s becoming a sustainable reality — and one that is all the more necessary in light of the COVID-19 pandemic. That reality will include the partial shift from caring for patients in hospitals, clinics, and medical offices to meeting their needs through telemedicine, hospital-at-home programs, and remote patient monitoring.
In Chapter 1, we address the question: “Is digital reconstruction necessary?” and include a review of the evidence on the effectiveness of digital healthcare, the shortcomings of episodic patient care, diagnostic errors, and our inadequate infrastructure.
Chapter 2 looks at the merits and limitations of telemedicine, hospital and home, and remote patient monitoring. It offers advice on making informed telemedicine choices and the impact of COVID-19, and provides a review of the scientific evidence. We also take a closer look at Mayo Clinic’s Advanced Care at Home program.
Chapter 3 discusses the digital assault on COVID-19, including the development of better predictive and diagnostic tools, expanding the knowledge base to address the pandemic, and the importance of taking a holistic approach to the infection.
Chapter 4 once again explores the value of big data, artificial intelligence, and machine learning, a topic we have looked at in several previous books. The discussion analyzes the evidence in diabetes, cardiovascular disease, cancer, gastroenterology, and psychiatry. We also address one of the most difficult issues in medicine: when does correlation imply causality. Finally, we devote a section to advanced data analytics, including a summary of how Mayo Clinic’s Clinical Data Analytics Platform operates.
Chapter 5, “Exploring the Artificial Intelligence/Machine Learning Toolbox,” is a primer on artificial neural networks, random forest modeling, gradient boosting, clustering, and linear and logistic regression. We are working from the assumption that many readers do not have a background in statistics or data science and hope these brief tutorials translate these complex topics into plain English.
Chapter 6 dives into the many conversational technologies emerging in healthcare. We begin with the role of natural language processing and then discuss the potential of voice technology to help diagnose disease and the role of Siri, Google Assistant, Alexa, and other patient-facing tools. Finally, we emphasize the urgent need to fight misinformation — with truth and trust.
Chapter 7, “Securing the Future of Digital Health,” tackles one of healthcare’s most vexing problems: Cyberattacks. We outline the need for comprehensive risk analysis, staff education to reduce the risk of phishing attacks, along with several basic precautionary steps, including encryption, strong passwords, firewalls, and the like. We also include a section on one of the most vulnerable parts of the healthcare ecosystem: “The Internet of Medical Things.”
Finally, in Chapter 8, we explore international initiatives to digitally reconstruct healthcare. Specific programs in the United Kingdom, China, and the Netherlands are discussed, as are the needs of low-resource nations.
The emergence of the numerous digital health solutions discussed in the following pages does not imply that information technology will singlehandedly rebuild the healthcare ecosystem. Healthcare needs much more than that. Call it “intensive lifestyle management.” Unfortunately, too many IT enthusiasts see technology as a savior and are eager to invest billions of dollars setting up countless initiatives, platforms, and networks in the hope that they will create a more cost-effective system. That kind of magical thinking is doomed to failure over the long-term. If properly deployed, technology will augment other resources much like AI-fueled algorithms are now augmenting the diagnosis of eye disease and cancer. Society will still need to address the underlying cultural, financial, and clinical root causes behind our failing healthcare system — issues that are beyond the scope of this book. We both have the humility to recognize that digital health and all the tools it brings to bear, are only part of the solution. Our experience and research, nonetheless, demonstrate that they are a crucial part of that solution.
Paul Cerrato, MA
John Halamka, MD, MS
References
1. Cerrato, P. Halamka, J. Reinventing Clinical Decision Support: Data Analytics. Artificial Intelligence, and Diagnostic Reasoning. Taylor & Francis, HIMSS, 2020. Boca Raton, Fl.
2. Cerrato P, Halamka J. The Transformative Power of Mobile Medicine: Leveraging Innovation, Seizing Opportunities, and Overcoming Obstacles of mHealth. Academic Press/Elsevier. 2019, Cambridge, MA.
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