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Smart Healthcare Service Model for Efficient Management of Patient at a Hospital Outpatient Visits

Affiliations

  • Department of Multimedia, Hannam University, 70 Hannamro, Daedeok-Gu Daejeon 34430, Korea
  • Department of Information Communication Engineering, Mokwon University, 88 Doanbuk-ro, Seo-gu, Daejeon 35349, Korea

Abstract


Objectives: In the present paper, a smart healthcare service management model is proposed that will enable automatic recognition of critically ill patients attached with implantable devices in their bodies without any additional administrative process when they visit hospitals as outpatients so that the patients can be provided with medical services without inconvenience. Methods/Statistical Analysis: The proposed model uses biometric RFID (Radio Frequency Identification) devices so that medical staff can identify patients’ disease types and conditions in advance. Findings: The proposed model has an advantage of shortening the time required for medical services and medical administrative work by grafting RFID technology onto biometric devices. In addition, to provide security for important information related to patient treatment, the proposed model applied probability based multiple property values to patients’ medical information to improve safety. Improvements/Applications: The proposed model was evaluated in comparison with existing medical systems in terms of service delay time, work efficiency, and patients’ satisfaction with medical services. According to the results of the performance evaluation, the proposed model improved service delay time by 16.5% on average, work efficiency by 27% on average, and patients’ satisfaction with services by 22.4% on average compared to existing models.

Keywords

Healthcare Service, Hospital, Implantable Device, Medical Service, Patient, Smart Healthcare.

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References


  • Weinstein R. RFID: A technical overview and its application to the enterprise. IEEE Journals and Managines: IT Professional. 2015 May/Jun; 7(3):27–33.
  • Jeong YS. Parallel Processing Scheme for Minimizing Computational and Communication Cost of Bioinformatics Data. Indian Journal of Science and Technology. 2015 Jul; 8(15):1–8.
  • Moon WH, Park HS.Reuse Intention Associated with the Selection Factors and Satisfaction: Focused on Spine Specialty Hospitals in Korea. Indian Journal of Science and Technology. 2015 Oct; 8(26):1–7.
  • Yao W, Chu C, Li Z. The adoption and implementation of RFID technologies in healthcare: A literature review. Journal of Medical System. 2012 Dec; 36(6):3507–25.
  • Atzori L, Iera A, Morabito G. The Internet of Things: A survey. ELSEVIER: Computer Networks. 2010 May; 54(15):2787–805.
  • Yu HY, Chen JJ. An intelligent space location identification system based on passive RFID tags. Proceedings of International Conference on Machine Learning and Cybernetics, China. 2014.428–33.
  • Fazlagic S. Delegating signing capability in workflow systems. Proceedings of 2nd International Conference on Computer Engineering and Technology, China.IEEE; 2010.324 –27.
  • Penttila K, Sydanheimo L, Kivikoski M. Performance development of a high-speed automatic object identification using passive RFID technology. Proceedings of IEEE International Conference on Robotics and Automation, USA. 2004.4864–8.
  • Katz J, Rice R.Public views of mobile medical devices and services: A US national survey of consumer sentiments towards RFID healthcare technology. International Journal of Medical Information. 2009 Feb; 78(2)104–14.
  • Choi JS, Lee H, Elmasri R, Engels DW. Localization Systems Using Passive UHF RFID. Proceedings of 5th International Joint Conference on INC, IMS and IDC, Korea. 2009.1727–32.
  • Liao Y, Hsiao C. A secure ECC-based RFID authentication scheme integrated with ID-verifier transfer protocol. Ad Hoc Networks. 2014 Jul; 18:133–46.
  • Chou JS.An efficient mutual authentication RFID scheme based on elliptic curve cryptography. The Journal of Super Computing. 2014 Oct; 70(1):75–94.
  • Zhao Z. A secure RFID authentication protocol for healthcare environments using elliptic curve cryptosystem. Journal of Medical Systems. 2014 May; 38(5):46.
  • Zhang Z, Qi Q. An efficient RFID authentication protocol to enhance patient medication safety using elliptic curve cryptography. Journal of Medical Systems. 2014 May; 38(5):47.
  • Khattak ZA, Sulaiman S, Manan JA. A study on threat model for federated identities in federated identity management system. Proceedings of International Symposium in Information Technology (ITSim), Malaysia. 2010.618–23.
  • Gao H, Yan J, Mu Y. Dynamic Trust Model for Federated Identity Management. Proceedings of 4th International Conference on Network and System Security, Australia. 2010.55–61.
  • Zhou Y, Cao Z, Lu R. Provably secure proxy-protected signature schemes based on factoring. Applied Mathematics and Computation. 2005 May; 164(1):83–98.
  • Saraswat V, Sahu RA. A secure anonymous proxy multi-signature scheme. Proceedings of 11th International Conference on Security and Cryptography, Austria. 2014.1–12.
  • Junru H, Yi D. An efficient signcryption scheme with shortened ciphertext. Proceedings of International Conference on Computer Application and System, Taiyuan. 2010.12:404–07.

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