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. 2021 Mar 8;9(3):e25121. doi: 10.2196/25121

Table 2.

Subscriber characteristics and prevalence of the dependent variable in the training and test sets for the Germany predictive model compared with the previously published results of the US predictive model in the test set. P values are reported for differences between German test and training sets, and between US and German test sets.

Characteristics Germany predictive model (this study) US predictive model (from [9])
Training set Test set P value (test vs training Germany) Test set P value (US vs Germany test)
General
Prediction dates Jan 1, 2012, to Jan 1, 2018 Jan 1, 2012, to Jan 1, 2018 Feb 1, 2014
# of unique PERSa users, n (%) 4644 (80) 116 (20) 109,966 (20)
# of prediction windows, n (%) 96,273 (79.5) 24,847 (20.5) 109,966 (20)
Age in years, mean (SD) 84.0 (8.2) 83.6 (8.3) .001 81.1 (11.4) <.001
Female gender, n (%) 2997 (64.5) 743 (64.0) .37 88,433 (80.4) <.001
Years on PERS service, n (%)
0-2 2598 (55.9) 630 (54.3) .32 48,922 (44.4) <.001
2-4 1079 (23.2) 264 (22.7) .75 26,193 (23.8) .41
4 or more 967 (20.8) 267 (23.0) .11 34,851 (31.7) <.001
Number of PERS self-reported medical conditions, n (%)
None 265 (5.7) 73 (6.3) .49 24,910 (22.6) <.001
1-2 1325 (28.5) 329 (28.3) .93 26,515 (24.1) <.001
3-4 1397 (30.1) 370 (31.9) .25 28,561 (26.0) <.001
5 or more 1657 (35.7) 389 (33.5) .18 29,980 (27.3) <.001
30-day emergency hospital transport (% of prediction windows) 1506 (1.6) 350 (1.4) .08 2455 (2.2) <.001

aPERS: personal emergency response system.