PROC SEVERITY supports OUTSCORELIB statement that enables you to create what are called "scoring functions" that you can evaluate on any data set with a fitted distribution. Please read the SAS/ETS User's Guide to know more about the OUTSCORELIB statement and post back if you have any questions.
In the context of PROC SEVERITY, 'scoring' means you can compute quantities such as CDF, PDF, etc of the the fitted distribution for a given response variable value, or mean of the distribution if it is defined and if <dist>_MEAN function appears in the libraries specified in the CMPLIB path (SASHELP.SVRTDIST contains mean functions for all predefined distributions). In the "extensibility" spirit of PROC SEVERITY, you can also define your own scoring functions.
Starting with SAS/ETS 14.2 release, which ships later this year, you will also be able to use the OUTPUT statement to "score" observations in the input (DATA=) data set. The OUTPUT statement allows you to overcome one limitation of scoring functions, which is that the scoring functions cannot be generated when your severity model contains complex scale regression effects such as CLASS variables and interactions.