FuzzyMatching | Matching intellectually disabled patients to non

FuzzyMatching is a Python library. FuzzyMatching has no bugs, it has no vulnerabilities and it has low support. However FuzzyMatching build file is not available. You can download it from GitHub.

Open a CSV with patient data containing intellectually disabled (ID) and non intellectually disabled patients (non ID). Attempt to match non ID patients to ID patients on key criteria: gender, ethnic group (caucasian, non caucasian or unknown), substance abuse, legal status, diagnosis group and then to fuzzily match age to within 10% (although this may be tweaked after usage on real data) of the ID patients' age. Then sort the potential matches by amount of match opportunities and randomly assign a matched non ID patient to an ID patient. Remove the non ID patient's record from all of the other matches if necessary and then continue.