1. Predicting Falls in People Aged 65 Years and Older from Insurance Claims 
Mark L. Homer, PhD, MMSc, Nathan P. Palmer, PhD, Kathe P. Fox, PhD, Joanne Armstrong, MD, MPH, Kenneth D. Mandl, MD, MPH 
The American Journal of Medicine 
Volume 130, Issue 6, Pages 744.e e23 (June 2017)
DOI: /j.amjmed
Copyright © 2017 Elsevier Inc. Terms and Conditions

2. Figure 1
Predictive model's risk stratification performance on held-out test data. The predictive model risk stratifies the population and yields estimates of the average fall risk (circle) within each stratum. The estimates are compared to the actual risk in each stratum (triangle).
The American Journal of Medicine  , 744.e e23DOI: ( /j.amjmed )
Copyright © 2017 Elsevier Inc. Terms and Conditions

3. Figure 2
Comparison of predictive model variations by AUC. Models differ by the types of predictive variables included. AUC = area under the receiver operating characteristic curve.
The American Journal of Medicine  , 744.e e23DOI: ( /j.amjmed )
Copyright © 2017 Elsevier Inc. Terms and Conditions

4. Figure 3
Comparison of predictive model variations by number of members identified as high-risk during validation (>20%). The number of people who actually fell within each model's estimated high-risk group are provided (in blue) and the number within each bar denotes the fraction of the high-risk members who fell, ie, positive predictive value.
The American Journal of Medicine  , 744.e e23DOI: ( /j.amjmed )
Copyright © 2017 Elsevier Inc. Terms and Conditions