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Applications of business analytics in healthcare

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  • Ward, Michael J.
  • Marsolo, Keith A.
  • Froehle, Craig M.

Abstract

The American healthcare system is at a crossroads, and analytics, as an organizational skill, figures to play a pivotal role in its future. As more healthcare systems capture information electronically and begin to collect more novel forms of data, such as human DNA, how will we leverage these resources and use them to improve human health at a manageable cost? In this article, we argue that analytics will play a fundamental role in the transformation of the American healthcare system. However, there are numerous challenges to the application and use of analytics: the lack of data standards, barriers to the collection of high-quality data, and a shortage of qualified personnel to conduct such analyses. There are also multiple managerial issues, such as how to get end users of electronic data to employ it consistently to improve healthcare delivery and how to manage the public reporting and sharing of data. In this article, we explore applications of analytics in healthcare, barriers and facilitators to its widespread adoption, and ways in which analytics can help us achieve the goals of the modern healthcare system: high-quality, responsive, affordable, and efficient care.

Suggested Citation

  • Ward, Michael J. & Marsolo, Keith A. & Froehle, Craig M., 2014. "Applications of business analytics in healthcare," Business Horizons, Elsevier, vol. 57(5), pages 571-582.
  • Handle: RePEc:eee:bushor:v:57:y:2014:i:5:p:571-582
    DOI: 10.1016/j.bushor.2014.06.003
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    1. Catherine M. DesRoches & Dustin Charles & Michael F. Furukawa & Maulik S. Joshi & Peter Kralovec & Farzad Mostashari & Chantal Worzala Ashish K. Jha, "undated". "Adoption of Electronic Health Records Grows Rapidly, But Fewer Than Half of US Hospitals had at Least a Basic System in 2012," Mathematica Policy Research Reports 0d8d890b940d4e0f835fa1ade, Mathematica Policy Research.
    2. Suresh Chand & Herbert Moskowitz & John Norris & Steve Shade & Deanna Willis, 2009. "Improving patient flow at an outpatient clinic: study of sources of variability and improvement factors," Health Care Management Science, Springer, vol. 12(3), pages 325-340, September.
    3. Diwas S. Kc & Christian Terwiesch, 2009. "Impact of Workload on Service Time and Patient Safety: An Econometric Analysis of Hospital Operations," Management Science, INFORMS, vol. 55(9), pages 1486-1498, September.
    4. repec:mpr:mprres:7826 is not listed on IDEAS
    5. Craig M. Froehle & Michael J. Magazine, 2013. "Improving Scheduling and Flow in Complex Outpatient Clinics," International Series in Operations Research & Management Science, in: Brian T. Denton (ed.), Handbook of Healthcare Operations Management, edition 127, chapter 0, pages 229-250, Springer.
    6. Diwas Singh KC & Christian Terwiesch, 2012. "An Econometric Analysis of Patient Flows in the Cardiac Intensive Care Unit," Manufacturing & Service Operations Management, INFORMS, vol. 14(1), pages 50-65, January.
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