Research Article
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Year 2020, , 41 - 50, 25.04.2020
https://doi.org/10.33457/ijhsrp.670597

Abstract

References

  • [1] I. Foster, C. Kesselmann, “The Grid: Blueprint for a New Computing Infrastructure”, Morgan Kaufmann Publishers, USA, 1999. [16].M.L. Bote-Lorenzo,
  • [2] Hashemi, S. M., & Bardsiri, A. K. (2012). Cloud computing vs. grid computing. ARPN journal of systems and software, 2(5), 188-194.
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  • [5] Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M. (2015). Internet of things: A survey on enabling technologies, protocols, and applications. IEEE Communications Surveys & Tutorials, 17(4), 2347-2376.
  • [6] Sterritt, R., & Hinchey, M. (2005, April). Why computer-based systems should be autonomic. In 12th IEEE International Conference and Workshops on the Engineering of Computer-Based Systems (ECBS'05) (pp. 406-412). IEEE.
  • [7] Wan, J., Zou, C., Zhou, K., Lu, R., & Li, D. (2014). IoT sensing framework with inter-cloud computing capability in vehicular networking. Electronic Commerce Research, 14(3), 389-416.
  • [8] Aloi, G., Caliciuri, G., Fortino, G., Gravina, R., Pace, P., Russo, W., & Savaglio, C. (2017). Enabling IoT interoperability through opportunistic smartphone-based mobile gateways. Journal of Network and Computer Applications, 81, 74-84.
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  • [10] Madakam, S., Ramaswamy, R., & Tripathi, S. (2015). Internet of Things (IoT): A literature review. Journal of Computer and Communications, 3(05), 164.
  • [11] Naik, N. (2017, October). Choice of effective messaging protocols for IoT systems: MQTT, CoAP, AMQP and HTTP. In 2017 IEEE international systems engineering symposium (ISSE)(pp. 1-7). IEEE.
  • [12] Tsang, L., Kracov, D. A., Mulryne, J., Strom, L., Perkins, N., Dickinson, R., et al. (2017). The impact of artificial intelligence on medical innovation in the european union and united states. Intellectual Property & Technology Law Journal, 29(8), 3-11.
  • [13] Keleş, A., Keleş, A., & Yavuz, U. (2011). Expert system based on neuro-fuzzy rules for diagnosis breast cancer. Expert Systems with Applications, 38(5), 5719-5726.
  • [14] Paydar, S., Pourahmad, S., Azad, M., Bolandparvaz, S., Taheri, R., Ghahramani, Z., ... & Abbasi, H. R. (2015). The Evolution of a Malignancy Risk Prediction Model for Thyroid Nodules Using the Artificial Neural Network. Middle East Journal of Cancer, 7(1), 47-52.
  • [15] Krupitzer, C., Roth, F. M., VanSyckel, S., Schiele, G., & Becker, C. (2015). A survey on engineering approaches for self-adaptive systems. Pervasive and Mobile Computing, 17, 184-206.
  • [16] HIMMS (2019), Healthcare Information and Management System Society, HIMMS EMRAN STAGE 6 & 7 COMMUNITY, https://www.himss.eu/communities/himss-emram-stage-6-7-community , 2019.
  • [17] Digiral, (2019), Ministry of Health Digital Hospital website, https://dijitalhastane.saglik.gov.tr/TR,4858/emram-hakkinda.html, 2019
  • [18] TUIK, Turkish Statistical Institute, Number of Physicians, Number of Persons per Physicians and Number of Patient Hospital Visits per Physician, www.turkstat.gov.t , 2017.

CAPABILITY MODEL AND COMPETENCE MEASURING FOR SMART HOSPITAL SYSTEM: AN ANALYSIS FOR TURKEY

Year 2020, , 41 - 50, 25.04.2020
https://doi.org/10.33457/ijhsrp.670597

Abstract

Today, rapidly developing technological innovations affect and change all sectors. Health sectors are inevitably involved in a digital transformation. In this transformation, IoT technology plays an important role, which enables many devices to connect and work together. IoT basically converts systems into intelligent systems that work together using sensors, connection methods, internet protocols, databases, cloud computing and analytics as infrastructure. In this respect, it is necessary to establish the necessary technical infrastructure and establish a suitable environment for the establishment of intelligent hospitals. Finally, a capability model has been developed in order to measure digital performance of Turkey. For Turkey health sector, technology assessment report is presented based on survey results and HIMMS EMRAM data.

References

  • [1] I. Foster, C. Kesselmann, “The Grid: Blueprint for a New Computing Infrastructure”, Morgan Kaufmann Publishers, USA, 1999. [16].M.L. Bote-Lorenzo,
  • [2] Hashemi, S. M., & Bardsiri, A. K. (2012). Cloud computing vs. grid computing. ARPN journal of systems and software, 2(5), 188-194.
  • [3] Lee, I., & Lee, K. (2015). The Internet of Things (IoT): Applications, investments, and challenges for enterprises. Business Horizons, 58(4), 431-440.
  • [4] Stojmenovic, I., & Wen, S. (2014, September). The fog computing paradigm: Scenarios and security issues. In Computer Science and Information Systems (FedCSIS), 2014 Federated Conference on (pp. 1-8). IEEE
  • [5] Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M. (2015). Internet of things: A survey on enabling technologies, protocols, and applications. IEEE Communications Surveys & Tutorials, 17(4), 2347-2376.
  • [6] Sterritt, R., & Hinchey, M. (2005, April). Why computer-based systems should be autonomic. In 12th IEEE International Conference and Workshops on the Engineering of Computer-Based Systems (ECBS'05) (pp. 406-412). IEEE.
  • [7] Wan, J., Zou, C., Zhou, K., Lu, R., & Li, D. (2014). IoT sensing framework with inter-cloud computing capability in vehicular networking. Electronic Commerce Research, 14(3), 389-416.
  • [8] Aloi, G., Caliciuri, G., Fortino, G., Gravina, R., Pace, P., Russo, W., & Savaglio, C. (2017). Enabling IoT interoperability through opportunistic smartphone-based mobile gateways. Journal of Network and Computer Applications, 81, 74-84.
  • [9] Bello, O., & Zeadally, S. (2013). Communication issues in the Internet of Things (IoT). In Next-Generation Wireless Technologies (pp. 189-219). Springer, London.
  • [10] Madakam, S., Ramaswamy, R., & Tripathi, S. (2015). Internet of Things (IoT): A literature review. Journal of Computer and Communications, 3(05), 164.
  • [11] Naik, N. (2017, October). Choice of effective messaging protocols for IoT systems: MQTT, CoAP, AMQP and HTTP. In 2017 IEEE international systems engineering symposium (ISSE)(pp. 1-7). IEEE.
  • [12] Tsang, L., Kracov, D. A., Mulryne, J., Strom, L., Perkins, N., Dickinson, R., et al. (2017). The impact of artificial intelligence on medical innovation in the european union and united states. Intellectual Property & Technology Law Journal, 29(8), 3-11.
  • [13] Keleş, A., Keleş, A., & Yavuz, U. (2011). Expert system based on neuro-fuzzy rules for diagnosis breast cancer. Expert Systems with Applications, 38(5), 5719-5726.
  • [14] Paydar, S., Pourahmad, S., Azad, M., Bolandparvaz, S., Taheri, R., Ghahramani, Z., ... & Abbasi, H. R. (2015). The Evolution of a Malignancy Risk Prediction Model for Thyroid Nodules Using the Artificial Neural Network. Middle East Journal of Cancer, 7(1), 47-52.
  • [15] Krupitzer, C., Roth, F. M., VanSyckel, S., Schiele, G., & Becker, C. (2015). A survey on engineering approaches for self-adaptive systems. Pervasive and Mobile Computing, 17, 184-206.
  • [16] HIMMS (2019), Healthcare Information and Management System Society, HIMMS EMRAN STAGE 6 & 7 COMMUNITY, https://www.himss.eu/communities/himss-emram-stage-6-7-community , 2019.
  • [17] Digiral, (2019), Ministry of Health Digital Hospital website, https://dijitalhastane.saglik.gov.tr/TR,4858/emram-hakkinda.html, 2019
  • [18] TUIK, Turkish Statistical Institute, Number of Physicians, Number of Persons per Physicians and Number of Patient Hospital Visits per Physician, www.turkstat.gov.t , 2017.
There are 18 citations in total.

Details

Primary Language English
Subjects Health Care Administration
Journal Section Article
Authors

Banu Çalış 0000-0001-8214-825X

Publication Date April 25, 2020
Submission Date January 5, 2020
Acceptance Date March 16, 2020
Published in Issue Year 2020

Cite

IEEE B. Çalış, “CAPABILITY MODEL AND COMPETENCE MEASURING FOR SMART HOSPITAL SYSTEM: AN ANALYSIS FOR TURKEY”, IJHSRP, vol. 5, no. 1, pp. 41–50, 2020, doi: 10.33457/ijhsrp.670597.

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