Somers’ $D$ is an index that you want to be closer to 1 and farther from $-1$. First, you use your model to generate the predicted scores for your dependent variable, $\hat{y}_i$. Then you think about every possible pairing of data points. A pair of predicted scores are “in agreement” if the rank order of the predicted scores match the rank order of the observed scores. That is, if $y_1 < y_2$ and $\hat{y}_1 < \hat{y}_2$, then the pair of points is considered to agree with the prediction. (To make life easy for this explanation, we will assume that ties are not possible.) If $\hat{y}_1 > \hat{y}_2$, then the predicted values are not in agreement with the observed values. After considering all possible pairs of points in your data set, $n_c$ is the number of agreements and $n_d$ is the number of disagreements (I'm using the same mathematical notation as the SAS PROC page, but using slightly different vocabulary.)
Let $p=\frac{n(n-1)}{2}$, the total number of possible pairs for a data set with sample size $n$. The formula for Somers” $D$ is
$$D = \frac{n_c-n_d}{p}$$
Hope this explanation is clear.