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Electronics and Telecommunications Research Institute (한국전자통신연구원)
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Personalized Healthcare System for Chronic Disease Care in Cloud Environment

  • Received : 2014.02.06
  • Accepted : 2014.09.15
  • Published : 2014.10.01
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Abstract

The rapid increase in the number of patients with chronic diseases is an important public healthcare issue in many countries, which accelerates many studies on a healthcare system that can, whenever and wherever, extract and process patient data. A patient with a chronic disease conducts self-management in an out-of-hospital environment, particularly in an at-home environment, so it is important to provide integrated and personalized healthcare services for effective care. To help provide effective care for chronic disease patients, we propose a service flow and a new cloud-based personalized healthcare system architecture supporting both at-home and at-hospital environments. The system considers the different characteristics of at-hospital and at-home environments, and it provides various chronic disease care services. A prototype implementation and a predicted cost model are provided to show the effectiveness of the system. The proposed personalized healthcare system can support cost-effective disease care in an at-hospital environment and personalized self-management of chronic disease in an at-home environment.

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References

  1. R. March, "Delivering on the Promise of Personalized Healthcare," Personalized Med., vol. 7, no. 3, May 2010, pp. 327-337. https://doi.org/10.2217/pme.10.17
  2. S. Jeong et al., "An Integrated Healthcare System for Personalized Chronic Disease Care in Home-Hospital Environments," IEEE Trans. Inf. Technol. Biomed., vol. 16, no. 4, July 2012, pp. 572-585. https://doi.org/10.1109/TITB.2012.2190989
  3. S. Ahmed and A. Abdullah, "Telemedicine in a Cloud - A Review," IEEE Symp. Comput. Informat., Kuala Lumpur, Malaysia, Mar. 20-23, 2011, pp. 776-781.
  4. A. Kuo, "Opportunities and Challenges of Cloud Computing to Improve Health Care Services," J. Med. Internet Res., vol. 13, no. 3, July-Sept. 2011, pp. e67. https://doi.org/10.2196/jmir.1867
  5. H. Yang, K. Liu, and W. Li, "Adaptive Requirement-Driven Architecture for Integrated Healthcare System," J. Comput., vol. 5, no. 2, Feb. 2010, pp. 186-193.
  6. Y. Han and C.-H. Youn, "A New Grid Resource Management Mechanism with Resource-Aware Policy Administrator for SLAConstrained Applications," Future Generation Comput. Syst., vol. 25, no. 7, July 2009, pp. 768-778. https://doi.org/10.1016/j.future.2008.11.005
  7. C.-H. Youn, B. Kim, and E.B. Shim, "Resource Reconfiguration Scheme Based on Temporal Quorum Status Estimation for Grid Management," IEICE Trans. Commun., vol. 88, no. 11, Nov. 2005, pp. 4378-4381.
  8. S. Jeong et al., "A Personalized Healthcare System for Chronic Disease Care in Home-Hospital Cloud Environments," IEEE Int. Conf. ICT Convergence, Jeju, Rep. of Korea, Oct. 14-16, 2013, pp. 371-376.
  9. S. Jeong et al., "A Novel Model for Metabolic Syndrome Risk Quantification Based on Areal Similarity Degree," IEEE Trans. Biomed. Eng., vol. 61, no. 3, Mar. 2014, pp. 665-679. https://doi.org/10.1109/TBME.2013.2286197
  10. S. Jeong, C.-H. Youn, and Y.-W. Kim, "A Method for Identifying Temporal Progress of Chronic Disease Using Chronological Clustering," IEEE Int. Conf. E-Health Netw., Appl. Services, Lisbon, Portugal, Oct. 9-12, 2013, pp. 329-333.
  11. HL7 Std. HL7 Version 3, HL7 Version 3: Reference Information Model (RIM), HL7 International, Ann Arbor, MI, USA, 2012.
  12. R. Dolin et al., "HL7 Clinical Document Architecture, Release 2," J. American Med. Informat. Association, vol. 13, no. 1, Jan.-Feb. 2006, pp. 30-39. https://doi.org/10.1197/jamia.M1888
  13. IEEE Std. 802.15.4, Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (LR-WPANs), Piscataway, NJ, USA, 2003.
  14. S. Jeong et al., "Temporal Progress Model of Metabolic Syndrome for Clinic Decision Support System," Innovation and Res. Biomed. Eng., 2014.
  15. R. Zhang and L. Liu, "Security Models and Requirements for Healthcare Application Clouds," IEEE Int. Conf. Cloud Comput., Miami, EL, USA, July 5-10, 2010, pp. 268-275.
  16. C.R. McGhee et al., "Forecasting Health Care Expenditures and Utilization Based on a Markov Process and a Deterministic Cost Function in Managed Care Settings," Lecture Notes-Monograph Series, vol. 43, no. 4, Oct. 2003, pp. 229-238.
  17. S. Jeong, C.-H. Youn, and Y.-W. Kim, "Predicted Cost Model for Integrated Healthcare Systems Using Markov Process," Int. Conf. Ubiquitous Inf. Technol. Appl., Danang, Vietnam, Dec. 18-20, 2013, pp. 181-187.
  18. S.M. Ross, Introduction to Probability Models, San Diego, USA: Academic Press, 1997, pp. 180-270.
  19. J.G. Kemeny and J.L. Snell, Finite Markov Chains, Princeton, USA: D. Van Nostrand Company, 1960, pp. 24-105.

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