A state of the art fuzzy based healthcare risk management for health information exchange

  • Authors

    • Amarendar Rao Thangeda Botho University
    • Alfred Coleman University of South Africa
    2019-11-10
    https://doi.org/10.14419/ijet.v8i4.29928
  • Health Information Exchange, Fuzzy Based Healthcare Risk Management (FHRM), Patients Monitoring.
  • The Today health-care organizations and physicians use several processes and instruments to exchange data about the private health of patients electronically. The main aims of the different methods of information (HIE) exchange on health are to reduce healthcare costs, to minimize medical errors and to better coordinate health services. Risks of information assets have a complex nature and different approaches address risk management of information security in medial field. The objective of this paper is to create the state-of - the-art information security risk management. In order to accomplish this, a Fuzzy based Healthcare Risk Management is suggested. This research aimed at exploring the core importance of the Fuzzy based Healthcare Risk Management (FHRM) from the views of health care consumers in the health sector. The result shows that the views of patients on multiple mechanisms for exchanging data about patient privacy, trust in competence and integrity and readiness to share data are significantly different.

     

     

     

  • References

    1. [1] Buntin, M. B., Burke, M. F., Hoaglin, M. C., & Blumenthal, D. (2011). The benefits of health information technology: a review of the recent literature shows predominantly positive results. Health affairs, 30(3), 464-471. https://doi.org/10.1377/hlthaff.2011.0178.

      [2] Kavaler, F., & Spiegel, A. D. (2003). Risk management in health care institutions: a strategic approach. Jones & Bartlett Learning.

      [3] Carroll, R. (Ed.). (2009). Risk management handbook for health care organizations (Vol. 30). John Wiley & Sons.

      [4] Sittig, D. F., & Singh, H. (2015). A new socio-technical model for studying health information technology in complex adaptive healthcare systems. In Cognitive informatics for biomedicine (pp. 59-80). Springer, Cham. https://doi.org/10.1007/978-3-319-17272-9_4.

      [5] Buntin, M. B., Burke, M. F., Hoaglin, M. C., & Blumenthal, D. (2011). The benefits of health information technology: a review of the recent literature shows predominantly positive results. Health affairs, 30(3), 464-471. https://doi.org/10.1377/hlthaff.2011.0178.

      [6] Jamal, A., McKenzie, K., & Clark, M. (2009). The impact of health information technology on the quality of medical and health care: a systematic review. Health Information Management Journal, 38(3), 26-37. https://doi.org/10.1177/183335830903800305.

      [7] Kierkegaard, P. (2011). Electronic health record: Wiring Europe’s healthcare. Computer law & security review, 27(5), 503-515. https://doi.org/10.1016/j.clsr.2011.07.013.

      [8] Amarasingham, R., Patzer, R. E., Huesch, M., Nguyen, N. Q., & Xie, B. (2014). Implementing electronic health care predictive analytics: considerations and challenges. Health Affairs, 33(7), 1148-1154. https://doi.org/10.1377/hlthaff.2014.0352.

      [9] Huang, C. D., Behara, R. S., & Goo, J. (2014). Optimal information security investment in a Healthcare Information Exchange: An economic analysis. Decision Support Systems, 61, 1-11. https://doi.org/10.1016/j.dss.2013.10.011.

      [10] Koh, H. C., & Tan, G. (2011). Data mining applications in healthcare. Journal of healthcare information management, 19(2), 65.

      [11] Smith, E., & Eloff, J. H. P. (2002). A prototype for assessing information technology risks in health care. Computers & Security, 21(3), 266-284. https://doi.org/10.1016/S0167-4048(02)00313-9.

      [12] Anderson, C. L., & Agarwal, R. (2011). The digitization of healthcare: boundary risks, emotion, and consumer willingness to disclose personal health information. Information Systems Research, 22(3), 469-490. https://doi.org/10.1287/isre.1100.0335.

      [13] Harland, C., Knight, L., Lamming, R., & Walker, H. (2005). Outsourcing: assessing the risks and benefits for organisations, sectors and nations. International Journal of Operations & Production Management, 25(9), 831-850. https://doi.org/10.1108/01443570510613929.

      [14] Tinetti, M. E., Gordon, C., Sogolow, E., Lapin, P., & Bradley, E. H. (2006). Fall-risk evaluation and management: challenges in adopting geriatric care practices. The Gerontologist, 46(6), 717-725. https://doi.org/10.1093/geront/46.6.717.

      [15] Bahli, B., & Rivard, S. (2003). The information technology outsourcing risk: a transaction cost and agency theoryâ€based perspective. Journal of Information Technology, 18(3), 211-221. https://doi.org/10.1080/0268396032000130214.

      [16] Haufe, K., Dzombeta, S., & Brandis, K. (2014). Proposal for a security management in cloud computing for health care. The Scientific World Journal, 2014. https://doi.org/10.1155/2014/146970.

      [17] Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: promise and potential. Health information science and systems, 2(1), 3. https://doi.org/10.1186/2047-2501-2-3.

      [18] Pronk, N. P., Peek, C. J., & Goldstein, M. G. (2004). Addressing multiple behavioral risk factors in primary care: a synthesis of current knowledge and stakeholder dialogue sessions. American journal of preventive medicine, 27(2), 4-17. https://doi.org/10.1016/j.amepre.2004.04.024.

      [19] Ventola, C. L. (2014). Social media and health care professionals: benefits, risks, and best practices. Pharmacy and Therapeutics, 39(7), 491.

      [20] Lobach, D., Sanders, G. D., Bright, T. J., Wong, A., Dhurjati, R., Bristow, E., & Williams, J. W. (2012). Enabling health care decision making through clinical decision support and knowledge management. Evid Rep Technol Assess (Full Rep), 203(203), 1-784.

  • Downloads

  • How to Cite

    Rao Thangeda, A., & Coleman, A. (2019). A state of the art fuzzy based healthcare risk management for health information exchange. International Journal of Engineering & Technology, 8(4), 552-558. https://doi.org/10.14419/ijet.v8i4.29928