• DocumentCode
    2665
  • Title

    The Role of Technology and Engineering Models in Transforming Healthcare

  • Author

    Pavel, Misha ; Jimison, Holly B. ; Wactlar, H.D. ; Hayes, Tamara L. ; Barkis, W. ; Skapik, J. ; Kaye, Jeff

  • Author_Institution
    Dept. of Biomed. Eng., Oregon Health & Sci. Univ., Portland, OR, USA
  • Volume
    6
  • fYear
    2013
  • fDate
    2013
  • Firstpage
    156
  • Lastpage
    177
  • Abstract
    The healthcare system is in crisis due to challenges including escalating costs, the inconsistent provision of care, an aging population, and high burden of chronic disease related to health behaviors. Mitigating this crisis will require a major transformation of healthcare to be proactive, preventive, patient-centered, and evidence-based with a focus on improving quality-of-life. Information technology, networking, and biomedical engineering are likely to be essential in making this transformation possible with the help of advances, such as sensor technology, mobile computing, machine learning, etc. This paper has three themes: 1) motivation for a transformation of healthcare; 2) description of how information technology and engineering can support this transformation with the help of computational models; and 3) a technical overview of several research areas that illustrate the need for mathematical modeling approaches, ranging from sparse sampling to behavioral phenotyping and early detection. A key tenet of this paper concerns complementing prior work on patient-specific modeling and simulation by modeling neuropsychological, behavioral, and social phenomena. The resulting models, in combination with frequent or continuous measurements, are likely to be key components of health interventions to enhance health and wellbeing and the provision of healthcare.
  • Keywords
    behavioural sciences computing; biocybernetics; biomedical engineering; geriatrics; health care; information technology; learning (artificial intelligence); mobile computing; neurophysiology; patient care; patient diagnosis; physiological models; psychology; sensors; social sciences; aging population; behavioral modeling; behavioral phenotyping; biomedical engineering models; chronic diseases; computational models; continuous medical measurements; disease detection; evidence-based healthcare; healtcare inconsistent provision; health behaviors; health enhancement; health interventions; healthcare escalating costs; healthcare system crisis; healthcare transformation motivation; information technology; machine learning technique; mathematical modeling approaches; medical networking; medical research technical overview; medical technology roles; mobile computing technology; neuropsychological modeling; patient centered healthcare; patient-specific modeling and simulation; preventive healthcare; quality-of-life improvization; sensor technology advances; social phenomena model; sparse sampling; wellbeing; Costs; Economics; Information technology; Medical information systems; Medical services; Medical treatment; Patient rehabilitation; Computational modeling; medical information systems; medical robotics; pervasive computing; remote monitoring; smart home; Activities of Daily Living; Biomedical Engineering; Computer Simulation; Delivery of Health Care; Health Care Costs; Humans; Medical Informatics; Models, Theoretical; Remote Sensing Technology; Robotics;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Reviews in
  • Publisher
    ieee
  • ISSN
    1937-3333
  • Type

    jour

  • DOI
    10.1109/RBME.2012.2222636
  • Filename
    6490450