The intercept parameter and its standard error are both very large for a logistic model and is still suggesting a problem. Was this done with the FIRTH option or not? If no, try using it. If yes, then you will need to simplify the model somehow to get a model that fits without evidence of problems - you should have no messages in the log about separation. Note that for a generalized model like a logistic model you cannot just run the model through PROC REG to get VIF values. See this note for assessing collinearity for generalized models. As noted in the NLMeans macro documentation, the Hessian warning will occur any time that the GLM parameterization (PARAM=GLM) is used in the model read into the macro.
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