Digital Twins and Automation of Care in the Intensive Care Unit

J. Geoffrey Chase, Cong Zhou, Jennifer L. Knopp, Knut Moeller, Balázs Benyo, Thomas Desaive, Jennifer H.K. Wong, Sanna Malinen, Katharina Naswall, Geoffrey M. Shaw, Bernard Lambermont, Yeong S. Chiew

Research output: Chapter in Book/Report/Conference proceedingChapter (Book)Otherpeer-review

3 Citations (Scopus)

Abstract

Healthcare is under increasing demand pressure as societies age and expectations rise, multiplied by increasing incidence of chronic diseases and decreasing available funding. The fundamental issue is the signal lack of productivity gains in medical care over the last four decades with the advent of digital technologies compared to many other fields of human endeavor. There is thus a need to bring digital technologies and automation to improve productivity and personalize care, improving costs and outcomes for patients and providers. Cyber–physical–human system s (CPHS), mixing digital technologies, computation, clinical staff, and patient physiology, offer a route forward. Critical care is one of the most technology-laden areas of healthcare, one of the biggest areas of patient growth with demographic change, and one of the costliest areas of care. Consuming 8–10% of healthcare expenditure (0.8–1.5% GDP) for less than 1% of patients, the intensive care unit (ICU) presents a major opportunity for CPHS systems to have an impact in creating the productive, next-generation care required to meet the demand for improved productivity and care. Personalized care, moving from today's one size fits all protocolized care to adaptive, model-based one method fits all care through model-based automation or clinician in the loop semiautomation is the means by which CPHS can enter this realm to positive impact. More specifically, digital twins or virtual patient models, personalized at the bedside in real-time, provide the means to optimize care by linking sensor measurements to outcome focused care actions, enabling personalized control. Digital twins and the so-called “hyper-automation” solutions have been leading technology trends for the last few years, but have yet to come to medicine. This review covers the increasing development of digital twins for medicine, and intensive care in particular, as the foundation for CPHS medical automation to improve care and productivity to meet rising demand. It covers the integrated role played by social sciences in the development, translation, and adoption of innovation, where medicine is historically conservative in adopting innovative solutions and technologies. It ends with a vision of the future from technical, social-behavioral, and combined overall perspectives for digital twins in this domain. CPHS solutions founded on digital twins offer the potential for a step change in ICU care, simultaneously increasing productivity, personalization, and quality of outcomes, while reducing the cost of care. Where the ICU is technology laden and thus most susceptible to this form of automation and disruption, the approach is general and will eventually spread to further areas of healthcare.

Original languageEnglish
Title of host publicationCyber–Physical–Human Systems
Subtitle of host publicationFundamentals and Applications
EditorsAnuradha M. Annaswamy, Pramod P. Khargonekar, Françoise Lamnabhi-Lagarrigue, Sarah K. Spurgeon
Place of PublicationHoboken NJ USA
PublisherWiley-Academy
Chapter17
Pages457-489
Number of pages33
ISBN (Electronic)9781119857433
ISBN (Print)9781119857402
DOIs
Publication statusPublished - 2023

Keywords

  • Automation
  • CPHS
  • Critical care
  • Cyber–physical–human systems
  • Decision support
  • Digital twins
  • ICU
  • Innovation
  • Model-based control
  • Personalized care
  • Technology adoption

Cite this