Case definitions
The case definitions used in HAIBA combine data from the Danish Microbiology Database (MiBa), the National Patient Register (LPR) and the Danish Central Person Register (CPR) to identify different types of infections.
The following types of infections are described in case definitions:
- Bacteraemia
- Clostridioides difficile infection
- Hip arthroplasty infection
- Knee arthroplasty infection
- Urinary tract infection
Data from MiBa
Data are transferred automatically from MiBa to HAIBA. Data from MiBa contain CPR numbers, sample date, sample time (if available), cultured or detected microorganisms, and information about the department of clinical microbiology that completed the diagnostics. Data from MiBa are linked to LPR through the CPR numbers.
More information about The Danish Microbiology Database – MiBa
Data from the National Patient Register (LPR)
Information on inpatients and outpatients from public and private hospitals is automatically transferred from the LPR to HAIBA every night. A new version of LPR (LPR3) was launched in February 2019. HAIBA now contains data from the previous LPR version (LPR2), data from previous private hospital registers (MiniPas), and data from LP3, including public and private hospital data.
The LPR data contain CPR numbers, date and time for healthcare contact, the responsible departments, hospitals, places of stay, diagnosis-, procedure-, and surgery codes. Since the LPR registers every contact as a new record, HAIBA uses an algorithm to merge any linked contacts to form a single record. The previous contact tracing algorithm, applied to LPR data until 2019, is described in the publication “The development and use of a new methodology to reconstruct courses of admission and ambulatory care based on the Danish National Patient Registry”. The algorithm was adapted for use with LPR3.
More information about the LPR (in Danish).
Data from the CPR
Information from the CPR concerns vital state and departure date. This information is important for the incidence calculations of the denominators used in the bacteraemia, urinary tract infections, and Clostridioides difficile infections, where dead or emigrated patients should not be included. This information can also be used for additional mortality analysis.