Incorporating the Last Four Digits of Social Security Numbers Substantially Improves Linking XXXX Data from De-identified Hospital Claims Databases.

@entity1 @entity2286
OBJECTIVE: Assess algorithms for linking @entity1 across de-identified databases without compromising confidentiality. DATA SOURCES/STUDY SETTING: Hospital discharges from 11 Mayo Clinic hospitals during January 2008-September 2012 (assessment and validation data). Minnesota death certificates and hospital discharges from 2009 to 2012 for entire state (application data). STUDY DESIGN: Cross-sectional assessment of sensitivity and positive predictive value ( @entity2286 ) for four linking algorithms tested by identifying readmissions and posthospital mortality on the assessment data with application to statewide data. DATA COLLECTION/EXTRACTION METHODS: De-identified claims included @entity1 gender, birthdate, and zip code. Assessment records were matched with institutional sources containing unique identifiers and the last four digits of Social Security number (SSNL4). PRINCIPAL FINDINGS: Gender, birthdate, and five-digit zip code identified readmissions with a sensitivity of 98.0 percent and a @entity2286 of 97.7 percent and identified postdischarge mortality with 84.4 percent sensitivity and 98.9 percent @entity2286 . Inclusion of SSNL4 produced nearly perfect identification of readmissions and deaths. When applied statewide, regions bordering states with unavailable hospital discharge data had lower rates. CONCLUSION: Addition of SSNL4 to administrative data, accompanied by appropriate data use and data release policies, can enable trusted repositories to link data with nearly perfect accuracy without compromising @entity1 confidentiality. States maintaining centralized de-identified databases should add SSNL4 to data specifications.
