Framework for Patient Service Queue System for Decision Support System on Smart Health Care

  • Abstract
  • Keywords
  • References
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  • Abstract

    Improving the service of patient care in hospitals is important for all, prioritizing patient safety in the event of a sudden or catastrophic attack, in which case the priority is to provide services to the patient. In such situations a decision system is needed, in order for the system to be right and not wrong to do a decision because the handling of this issue is closely related to the patient's life. The patient handling technology supports highly smart healthcare technology, which of course is part of the Smart city. The purpose of this research is to get Smart Health Care model with Decision Support System model approach in public health service, where Decision Support System model for Smart Health Care can solve health service problem in order to make maximum service for patient


  • Keywords

    Decision Support System, Smart Health Care, Queue

  • References

      [1] X. Chen, L. Wang, J. Ding, and N. Thomas, “Patient Flow Scheduling and Capacity Planning in a Smart Hospital Environment,” IEEE Access, vol. 4, pp. 135–148, 2016.

      [2] C. Tekin, O. Atan, and M. Van Der Schaar, “Discover the Expert: Context-Adaptive Expert Selection for Medical Diagnosis,” IEEE Trans. Emerg. Top. Comput., vol. 3, no. 2, pp. 220–234, 2015.

      [3] F.-Z. Younsi, A. Bounnekar, D. Hamdadou, and O. Boussaid, “SEIR-SW, Simulation Model of Influenza Spread Based on the Small World Network,” Tsinghua Sci. Technol., vol. 20, no. 5, pp. 460–473, 2015.

      [4] S. P. Mohanty, U. Choppali, and E. Kougianos, “Everything you wanted to know about smart cities,” IEEE Consum. Electron. Mag., vol. 5, no. 3, pp. 60–70, 2016.

      [5] A. Alaiad and L. Zhou, “Patients’ adoption of WSN-Based smart home healthcare systems: An integrated model of facilitators and barriers,” IEEE Trans. Prof. Commun., vol. 60, no. 1, pp. 4–23, 2017.

      [6] L. Lapointe, J. Ramaprasad, and I. Vedel, “Collaborating through social media to create health awareness,” in Proceedings of the Annual Hawaii International Conference on System Sciences, 2013, pp. 792–801.

      [7] A. Solanas et al., “Smart health: A context-aware health paradigm within smart cities,” IEEE Commun. Mag., vol. 52, no. 8, pp. 74–81, 2014.

      [8] T. J. Kakiay, Dasar Teori Antrian Untuk Kehidupan Nyata. Yogyakarta: Andi, 2004.

      [9] A. M. H. Pardede, H. Mawengkang, and Z. Situmorang, “SIMULASI ANTRIAN KEDATANGAN BERKELOMPOK DENGAN PELAYANAN WEIBULL OLEH BANYAK SERVER,” J. Teknol. Inf. dan Komun., vol. 3, no. 1, pp. 1–10, 2014.

      [10] A. M. H. Pardede, Novriyenni, and R. Hartono, “SIMULASI ANTRIAN PELAYANAN NASABAH BANK MENGGUNAKAN METODE HYPEREXPONENTIAL,” J. Inf. Syst. Dev., vol. 3, no. 1, pp. 33–43, 2018.

      [11] P. G. W. Keen, “Decision support systems: a research perspective,” Decis. Support Syst. Issues Challenges Proc. an Int. Task Force Meet., pp. 23–44, 1980.

      [12] H. Demirkan, “A smart healthcare systems framework,” IT Prof., vol. 15, no. 5, pp. 38–45, 2013.

      [13] V. Chichernea, “THE USE OF DECISION SUPPORT SYSTEMS (DSS) IN SMART CITY PLANNING AND MANAGEMENT,” J. Inf. Syst. Oper. Manag., pp. 1–14, 2014.

      [14] I. Adan and J. Resing, “Queueing Theory,” Technology, vol. 15, no. x, p. 180, 2002.




Article ID: 16915
DOI: 10.14419/ijet.v7i2.13.16915

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