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
Link To Document :
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