Medical Trend Analysis Methods
Medical Trend Analysis Methods
dc.contributor.advisor | Wu, Qiang | en_US |
dc.contributor.author | Yin, Le | en_US |
dc.contributor.committeemember | Hong, Don | en_US |
dc.contributor.committeemember | Sinkala, Zachariah | en_US |
dc.contributor.department | Basic & Applied Sciences | en_US |
dc.date.accessioned | 2014-06-02T19:01:54Z | |
dc.date.available | 2014-06-02T19:01:54Z | |
dc.date.issued | 2014-12-31 | en_US |
dc.description.abstract | Medical trend is the most important component used to indicate and file rates. Insurance companies use trend to forecast future costs and premiums. Governments use medical trend in the rate review process. This thesis reviews four methods used to find a trend factor: average ratio, linear regression, exponential regression and time series analysis method with rolling average technology. A software package is developed to calculate medical trend based on annual data or monthly data. An efficient method to detect the outliers is also presented. | en_US |
dc.description.degree | M.S. | en_US |
dc.identifier.uri | http://jewlscholar.mtsu.edu/handle/mtsu/3638 | |
dc.publisher | Middle Tennessee State University | en_US |
dc.subject | Average ratio method | en_US |
dc.subject | Medical trend | en_US |
dc.subject | Outlier detection | en_US |
dc.subject | Regression method | en_US |
dc.subject | Rolling average | en_US |
dc.subject | Time series analysis | en_US |
dc.subject.umi | Mathematics | en_US |
dc.thesis.degreegrantor | Middle Tennessee State University | en_US |
dc.thesis.degreelevel | Masters | en_US |
dc.title | Medical Trend Analysis Methods | en_US |
dc.type | Thesis | en_US |
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