Advertisement

Application of Seasonal Analytics in HealthCare Sector

  • Shrikant H. KoppadEmail author
  • S. Anupama Kumar
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 26)

Abstract

Healthcare organization generate huge amount of structured and unstructured data by its different stakeholders. It is challenging to design and integrate data from heterogeneous sources in a meaningful form, manipulate the data according to the business requirement, flush out unwanted data from the warehouse and generate reports from data. Analytical tools provide solution for most of forecasting problems at finger tips by using different types of analytical methods such as predictive, descriptive, diagnostic and perspective which can be used to increase the functionality of the organization. This research work provides the simulation model which provides insight for healthcare organizations to increase revenue with available resource by implementing seasonal analytics and take administrative decisions to help the stakeholders. The analytics also support to find the efficient doctor and most vital patient so that special care can be taken in treatment.

Keywords

Healthcare Seasonal analytics Big data analytics Gross revenue Patient care 

References

  1. 1.
    Khedr, A., Kholeif, S., Saad, F.: An integrated business intelligence framework for healthcare analytics. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 7, 263–270 (2017)CrossRefGoogle Scholar
  2. 2.
    Kankanhalli, A., Hahn, J., Tan, S., Gao, G.: Big data and analytics in healthcare: introduction to the special section. Inf. Syst. Front. 18(2), 233–235 (2016)CrossRefGoogle Scholar
  3. 3.
    Raghupathi, W., Raghupathi, V.: An overview of health analytics. J. Health Med. Inf. 4(132), 2 (2013)Google Scholar
  4. 4.
    Priyanka, K., Kulennavar, N.: A survey on big data analytics in health care. Int. J. Comput. Sci. Inf. Technol. 5(4), 5865–5868 (2014)Google Scholar
  5. 5.
    Daemmrich, A.A.: Us Healthcare Reform and the Pharmaceutical Industry. 12-015. Harvard Business School, Boston, 14 September 2011Google Scholar
  6. 6.
    National Survey: The Landscape of Data & Analytics in Healthcare (2014)Google Scholar
  7. 7.
    Cognizant Reports: Analytics-Driven Healthcare: Improving Care. Compliance and Cost. Cognizant Reports (February), pp. 1–10 (2013)Google Scholar
  8. 8.
    Koppad, S.H., Kumar, A.: Application of big data analytics in healthcare system to predict COPD. In: Proceedings of IEEE International Conference on Circuit, Power and Computing Technologies, ICCPCT (2016)Google Scholar
  9. 9.
    Groves, P., Kayyali, B., Knott, D., Van Kuiken, S.: The big data revolution in healthcare. McKinsey Q. 2, 3 (2013)Google Scholar
  10. 10.
    Raghupathi, W., Raghupathi, V.: Big data analytics in healthcare: promise and potential. Health Inf. Sci. Syst. 2(1), 3 (2014)CrossRefGoogle Scholar
  11. 11.
    Hersh, W., Jacko, J.A., Greenes, R., Tan, J., Janies, D., Embi, P.J., Payne, P.R.: Health-care hit or miss? Nature 470(7334), 327 (2011)Google Scholar
  12. 12.
    National Survey: The Landscape of Data & Analytics in Healthcare, eHealth Initiative 818 Connecticut Ave NW, Suite 500 Washington, DC 20006 (2014). www.ehidc.org
  13. 13.
    Patel, P., Pawar, T., Saini, S.S., Khade, A.: Predictive Analysis in Healthcare. Int. J. Comput. Eng. Appl. XII(IV), April 18. www.ijcea.com ISSN 2321-3469
  14. 14.
    Sonnati, R.: Improving healthcare using big data analytics. Int. J. Sci. Technol. Res. 4(8), 142–146 (2015)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of MCARashtreeya Vidyalaya College of EngineeringBengaluruIndia

Personalised recommendations