In the Parameter Estimates table output from Proc MIANALYZE, the last column is the p-value for testing that the estimate=0 (in your case it is very small, i.e. less than .0001). If you want the actual value then you would either need to format the output by modifying the template (cumbersome) or saving the table to a SAS dataset and then applying a FORMAT.
proc mianalyze data=est_ds; by label; modeleffects LBetaEstimate; stderr stderr;
ods output ParameterEstimates=parms;
run;
proc print data=parms;
format Probt 10.8;
run;
The combined standard error will almost always be larger than any of the standard errors for the single estimates by design. Part of what makes multiple imputation appealing and a good tool to reduce bias is the fact that it introduces variability across the imputations and not just within the imputations. In other words, the variance for the estimates includes two factors--the within imputation variance and the between imputation variance. The formulas in the documentation are informative in that regard.
SAS Help Center: Combining Inferences from Imputed Data Sets
run;
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