Master human subject ID generator and matcher based on PHI keys: lastFirstNames, dob, gender, mrn
u0028003$ java -jar -Xmx2G ~/Code/SubjectMatchMaker/target/SubjectMatchMaker_0.2.jar
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** Subject Match Maker : Sept 2022 **
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SMM attempts to match subject's PHI keys (FirstLastName, DoB, Gender, MRN) against a
registry of the same and fetch their unique subject coreIds. SMM uses a sum of
the key's LevenshteinEditDistance/Length as the distance metric with penalties for
missing keys. Both a json and spreadsheet report are generated. If indicated,
queries not matched will be added to the registry with a new coreId. Use this tool to
assign unique ids to new subjects and find them using missing, partial, or typo
altered PHI keys. JUnit tested.
Required:
-r Directory containing one file with the prefix 'currentRegistry_' that contains a
registry of subjects, tab delimited file(.gz/.zip OK), one subject per line:
lastName firstName dobMonth(1-12) dobDay(1-31) dobYear(1900-2050) gender(M|F)
mrn coreId otherIds. The last two columns are optional. Semicolon delimit
otherIds. Use '.' for missing info. CoreIds will be created as needed.
Example: Biden Joseph 11 20 1942 M 19485763 . 7474732,847362
-q File containing queries to match to the registry, ditto. Alternatively, provide
a single column of coreIds to use in fetching subject info from the registry.
-o Directory to write out the match result reports.
Optional:
-a Add query subjects that failed to match to the registry and assign them a coreId.
-s Max edit score for match, defaults to 0.12, smaller scores are more stringent.
-p Score penalty for a single missing key, defaults to 0.12
-k Score penatly for additional missing keys, defaults to 1
-t Number of threads to use, defaults to all.
-m Number of top matches to return per query, defaults to 3
-c Case-insensitive name matching, defaults to case sensitive.
Example: java -jar pathTo/SubjectIdMatchMaker_xxx.jar -r ~/PHI/SMMRegistry
-q ~/Tempus/newPatients_PHI.txt -o ~/Tempus/SMMRes/ -a -c
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