Healthcare Administration

What is “k-means clustering,” and how might it help healthcare administration leaders in their health services organization?

One of the more common methods of clustering is the use of k-means, where “k” is the number of clusters that are meant to describe the population of interest. For example, what if you were interested in segmenting patients based on satisfaction levels? K-means clustering could be used in the same way to help describe this given population.

This technique might assist healthcare administration leaders in determining what characteristics need to be considered to execute effective healthcare delivery. In striving to uphold patient satisfaction, maintaining a high quality of health services, and minimizing costs of healthcare delivery, k-means clustering is an effective tool for the healthcare administration leader.

For this Assignment, review the resources for this week, and examine the k-means clustering approach. Reflect on how you might apply this approach to an issue or challenge in a health services organization. Then, complete the problems for the Assignment.

The Assignment: (3–5 pages)

• Complete Problem 21 on page 984 of your course text.
  • Chapter 17.4, “Classification Methods” (pp. 964–980)
  • Chapter 17.5, “Clustering” (pp. 980–982)

Note: You will need to complete a logistic regression, as well as a k-means cluster analysis, using SPSS.

Albright, S. C., & Winston, W. L. (2015). Business analytics: Data analysis and decision making (5th ed.).