title: [Deterministic record linkage with indirect identifiers: data of the Berlin Myocardial Infarction Registry and the AOK Nordost for patients with myocardial infarction].
abstract: OBJECTIVE
  How can 2 pseudonymised data sets be linked? Using the example of data from the Berlin Myocardial Infarction Registry and from a German sickness fund (AOK Nordost) we will demonstrate how record linkage can be achieved without personal identifiers.
  
  
  METHODS
  In different steps the method of deterministic record linkage with indirect identifiers: age, sex, hospital admission date and time, will be explained.
  
  
  RESULTS
  We were able to show that 80.6% of the expected maximum number of patients were matched with our approach. As a result we had no duplicate matches in the linkage process, where one AOK patient was linked to 2 or more BMIR patients or vice versa. The matching variables produced enough uniqueness to be used as indirect patient identifiers.
  
  
  CONCLUSIONS
  Deterministic record linkage with the following indirect indicators: age, sex, hospital admission date and time was possible in our study of patients with myocardial infarction in a circumscribed geographical region, which limited the number of cases and avoided mismatches.
authors.affiliation: Berliner Herzinfarktregister am Fachgebiet Management im Gesundheitswesen an TU Berlin.
authors.forename: B
authors.initials: B
authors.lastname: Maier
authors.affiliation: Berliner Herzinfarktregister am Fachgebiet Management im Gesundheitswesen an TU Berlin.
authors.forename: K
authors.initials: K
authors.lastname: Wagner
authors.affiliation: Kardiologie, Vivantes Humboldt-Klinikum, Berlin.
authors.forename: S
authors.initials: S
authors.lastname: Behrens
authors.affiliation: Kardiologie, Unfallkrankenhaus Berlin, Berlin.
authors.forename: L
authors.initials: L
authors.lastname: Bruch
authors.affiliation: Management im Gesundheitswesen, TU Berlin, Berlin.
authors.forename: R
authors.initials: R
authors.lastname: Busse
authors.affiliation: Krankenhausplanung, AOK Nordost, Berlin.
authors.forename: D
authors.initials: D
authors.lastname: Schmidt
authors.affiliation: Kardiologie, Vivantes Auguste-Viktoria-Klinikum, Berlin.
authors.forename: H
authors.initials: H
authors.lastname: Schühlen
authors.affiliation: Kardiologie, Jüdisches Krankenhaus Berlin, Berlin.
authors.forename: R
authors.initials: R
authors.lastname: Thieme
authors.affiliation: Kardiologie, Humboldtmühle Medical Park, Berlin.
authors.forename: H
authors.initials: H
authors.lastname: Theres
mesh_terms: D000328:Adult; D000068598:Data Accuracy; D000068240:Data Anonymization; D005260:Female; D005858:Germany / Q000453:epidemiology; D006751:Hospital Information Systems / Q000706:statistics & numerical data*; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods / Q000706:statistics & numerical data; D008297:Male; D062527:Meaningful Use / Q000706:statistics & numerical data; D008498:Medical Record Linkage / Q000379:methods*; D008875:Middle Aged; D009203:Myocardial Infarction / Q000175:diagnosis / Q000453:epidemiology* / Q000628:therapy; D009313:National Health Programs / Q000706:statistics & numerical data*; D012042:Registries / Q000706:statistics & numerical data*