Volume 2 , Issue 2 , PP: 49-58, 2021 | Cite this article as | XML | Html | PDF | Full Length Article
Muhammad Edmerdash, Waleed khedr, Ehab Rushdy 1
Doi: https://doi.org/10.54216/IJWAC.020201
Cloud computing has brought a new paradigm shift to the technology industry and has become increasingly popular. Cloud communication is an emerging technology that can be combined with traditional healthcare management used to provide better healthcare services. Today, the adoption rate of cloud computing by small and medium enterprises (SMEs) is much higher than that of large companies. This triggered a debate about whether this cloud computing technology will penetrate the entire IT industry. Small and midsize enterprises are using cloud computing to deploy general IT infrastructure and software systems at low-cost, while large enterprises rely on their own infrastructure to ensure data security, privacy, and flexibility. One of the most demanded healthcare services that needs the cloud privileges is Drug-Drug Interaction – DDI. In this article, we have investigated different traditional systems compared to cloud-based systems, and as a privilege of providing system solutions to the public, what features the cloud brings to improve health management software.
Cloud computing , Cloud communication , healthcare management systems , Data Integrity , Potential Solutions
[1] FDA. URL: https://www.fda.gov/drugs/special-features/drug-interactions-understanding-risk (accessed on 01 JUN 2018).
[2] FDA. URL: https://www.fda.gov/consumers/consumer-updates/avoiding-drug-interactions (accessed on 03 JUN 2018).
[3] Wishart DS, Feunang YD, Guo AC, Lo EJ, Marcu A, Grant JR, Sajed T, Johnson D, Li C, Sayeeda Z, Assempour N, Iynkkaran I, Liu Y, Maciejewski A, Gale N, Wilson A, Chin L, Cummings R, Le D, Pon A, Knox C, Wilson M. DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res. 2017 Nov 8. doi: 10.1093/nar/gkx1037.
[4] Beaver, Clara. "Vincristine Minibag Administration: A quality improvement project to minimize medical errors." Clinical journal of oncology nursing 22.6 (2018).
[5] Blenkinsopp, Alison, and Colin Bradley. "Over the Counter Drugs: Patients, society, and the increase in self-medication." Bmj 312.7031 (1996): 629-632.
[6] Chressanthis, G. A., Dahan, N. G., & Fandl, K. J. (2015). The Effects of State Pharmacy Drug Product Selection Laws on Statin Patient Generic-To-Branded Drug Switch-Backs. The American Economist, 60(1), 26–51. doi:10.1177/056943451506000104.
[7] Min, H., A. Mitra, and S. Oswald, Competitive benchmarking of health care quality using the analytic hierarchy process: An example from Korean cancer clinics. Socio-economic planning sciences, 1997. 31(2): p. 147-159.
[8] Herédi-Szabó, K., Palm, J. E., Andersson, T. B., Pál, Á., Méhn, D., Fekete, Z., ... & Krajcsi, P. (2013). A P-gp vesicular transport inhibition assay–Optimization and validation for drug–drug interaction testing. European Journal of Pharmaceutical Sciences, 49(4), 773-781.
[9] Armbrust, Michael, et al.” A view of cloud computing.” Communications
of the ACM, 53(4), pp. 50-58, 2010.
[10] Sasikala, P. “Research challenges and potential green technological applications in cloud computing.” International Journal of Cloud Computing, 2(1), pp. 1-19, 2013.
[11] Fernando, Niroshinie, Seng W. Loke, and Wenny Rahayu. “Mobile cloud computing: A survey.” Future Generation Computer Systems, 29(1), pp. 84-106, 2013.
[12] Mell, P. and Grance, T. “The NIST Definition of Cloud Computing.” 2009.
[13] Puthal, D., Sahoo, B. P. S., Mishra, S., & Swain, S. (2015). Cloud Computing Features, Issues, and Challenges: A Big Picture. 2015 International Conference on Computational Intelligence and Networks. doi:10.1109/cine.2015.31.
[14] Zissis, Dimitrios, and Dimitrios Lekkas. “Addressing cloud computing security issues.” Future Generation Computer Systems, 28(3), pp. 583- 592, 2012.
[15] Choudhary, V. Software as a service: Implications for investment in software development. 40th Annual Hawaii International Conference on System Sciences, IEEE, 209a-209a, 2007.
[16] Seccombe A, et al. Security guidance for critical areas of focus in cloud computing. Cloud Security Alliance, 2(1), 2009.
[17] Subashini, S. and V. Kavitha (2011). “A survey on security issues in service delivery models of cloud computing.” Journal of Network and Computer Applications, 34(1), pp.1-11, 2011.
[18] Gajek, S., et al. Breaking and fixing the inline approach. ACM workshop on Secure web services, ACM, 2007.
[19] Descher, M., et al. Retaining data control to the client in infrastructure clouds. International Conference on Availability, Reliability and Security, IEEE, pp. 9-16, 2009.
[20] “U.s. department of health and human services, drug-druginteraction.” https://aidsinfo.nih.gov/understanding-hiv-aids/glossary/ 213/drug-drug-interaction. Accessed: 2018-09-01.
[21] R. A. Hamilton, L. L. Briceland, and M. H. Andritz, “Frequency of hospitalization after exposure to known drug-drug interactions in a medicaid population,” Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy, vol. 18, no. 5, pp. 1112–1120.
[22] C. Wang, Q. Wang, K. Ren, and W. Lou, Privacy-Preserving Public Auditing for Data Storage Security in Cloud Computing, Proc. IEEE INFOCOM, pp. 525-533, 2010.
[23] T. Sousa, A. Silva, and A. Neves, Particle swarm based data mining algorithms for classification tasks, Parallel Comput., 30(5), pp. 767783, 2004.
[24] S. Abrishami, M. Naghibzadeh, and D.H.J. Epema. ”Deadlineconstrained workflow scheduling algorithms for infrastructure as a service clouds.” Future Generation Computer Systems, 29(1), pp. 158-169, 2013.
[25] Schad, Jrg, Jens Dittrich, and Jorge-Arnulfo Quian-Ruiz. “Runtime measurements in the cloud: observing, analyzing, and reducing variance.” Proceedings of the VLDB Endowment, pp. 460-471, 2010.
[26] Iosup, Alexandru, Nezih Yigitbasi, and Dick Epema. “On the performance variability of production cloud services.” CCGrid, 2011 11th IEEE/ACM International Symposium on, pp. 104-113. IEEE, 2011.
[27] Di Niu; Zimu Liu; Baochun Li; Shuqiao Zhao; , ”Demand forecast and performance prediction in peer-assisted on-demand streaming systems,” INFOCOM, Proceedings IEEE , pp. 421-425, 2011.
[28] Al-Tamimi, A.-K.; Jain, R.; So-In, C.;, ”Dynamic resource allocation based on online traffic prediction for video streams,” Internet Multimedia Services Architecture and Application(IMSAA), 2010 IEEE 4th International Conference on, pp. 1-6, 2010.
[29] Caron, E.; Desprez, F.; Muresan, A.; , ”Forecasting for Grid and Cloud Computing On-Demand Resources Based on Pattern Matching,” Cloud Computing Technology and Science (CloudCom), IEEE 2nd International Conference on , pp. 456-463, 2010.
[30] Kalyvianaki, Evangelia, Themistoklis Charalambous, and Steven Hand. “Self-adaptive and self-configured CPU resource provisioning for virtualized servers using Kalman filters.” In Proceedings of the 6th international conference on Autonomic computing, ACM, pp. 117-126. 2009.
