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Incorporating the Last Four Digits of Social Security Numbers Substantially Improves Linking Patient Data from De‐identified Hospital Claims Databases
Author(s) -
Naessens James M.,
Visscher Sue L.,
Peterson Stephanie M.,
Swanson Kristi M.,
Johnson Matthew G.,
Rahman Parvez A.,
Schindler Joe,
Sonneborn Mark,
Fry Donald E.,
Pine Michael
Publication year - 2015
Publication title -
health services research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.706
H-Index - 121
eISSN - 1475-6773
pISSN - 0017-9124
DOI - 10.1111/1475-6773.12323
Subject(s) - confidentiality , medicine , zip code , identifier , diagnosis code , identification (biology) , database , data security , patient data , medical emergency , unique identifier , computer security , computer science , environmental health , population , encryption , botany , biology , programming language
Objective Assess algorithms for linking patients 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 ( PPV ) 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 patient gender, birthdate, and zip code. Assessment records were matched with institutional sources containing unique identifiers and the last four digits of Social Security number ( SSNL 4). Principal Findings Gender, birthdate, and five‐digit zip code identified readmissions with a sensitivity of 98.0 percent and a PPV of 97.7 percent and identified postdischarge mortality with 84.4 percent sensitivity and 98.9 percent PPV . Inclusion of SSNL 4 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 SSNL 4 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 patient confidentiality. States maintaining centralized de‐identified databases should add SSNL 4 to data specifications.