Clinical Epidemiology (Oct 2016)
The Danish Intensive Care Database
Abstract
Christian Fynbo Christiansen,1 Morten Hylander Møller,2 Henrik Nielsen,1 Steffen Christensen3 1Department of Clinical Epidemiology, Institute of Clinical Medicine, Aarhus University Hospital, Aarhus, 2Department of Intensive Care 4131, Copenhagen University Hospital Rigshospitalet, Copenhagen, 3Department of Intensive Care, Aarhus University Hospital, Aarhus, Denmark Aim of database: The aim of this database is to improve the quality of care in Danish intensive care units (ICUs) by monitoring key domains of intensive care and to compare these with predefined standards. Study population: The Danish Intensive Care Database (DID) was established in 2007 and includes virtually all ICU admissions in Denmark since 2005. The DID obtains data from the Danish National Registry of Patients, with complete follow-up through the Danish Civil Registration System. Main variables: For each ICU admission, the DID includes data on the date and time of ICU admission, type of admission, organ supportive treatments, date and time of discharge, status at discharge, and mortality up to 90 days after admission. Descriptive variables include age, sex, Charlson comorbidity index score, and, since 2010, the Simplified Acute Physiology Score (SAPS) II. The variables are recorded with 90%–100% completeness in the recent years, except for SAPS II score, which is 73%–76% complete. The DID currently includes five quality indicators. Process indicators include out-of-hour discharge and transfer to other ICUs for capacity reasons. Outcome indicators include ICU readmission within 48 hours and standardized mortality ratios for death within 30 days after admission using case-mix adjustment (initially using age, sex, and comorbidity level, and, since 2013, using SAPS II) for all patients and for patients with septic shock. Descriptive data: The DID currently includes 335,564 ICU admissions during 2005–2015 (average 31,958 ICU admissions per year). Conclusion: The DID provides a valuable data source for quality monitoring and improvement, as well as for research. Keywords: critical care, databases, health care quality, intensive care
