This paper describes improvements of and extensions to the Mayo Clinic 2006 smoking status classification system. The new system aims at addressing some of the limitations of the previous one. The performance improvements were mainly achieved through remodeling the negation detection for non-smoker, temporal resolution to distinguish a past and current smoker, and improved detection of the smoking status category of unknown. In addition, we introduced a rule-based component for patient-level smoking status assignments in which the individual smoking statuses of all clinical documents for a given patient are aggregated and analyzed to produce the final patient smoking status. The enhanced system builds upon components from Mayo's clinical Text Analysis and Knowledge Extraction System developed within IBM's Unstructured Information Management Architecture framework. This reusability minimized the development effort. The extended system is in use to identify smoking status risk factors for a peripheral artery disease NHGRI study.