Validity of the coding for intensive care admission, mechanical ventilation, and acute dialysis in the Danish National Patient Registry: a short report

Linea Blichert-Hansen, Malene S Nielsson, Rikke B Nielsen, Christian F Christiansen, Mette Nørgaard

Department of Clinical Epidemiology, Aarhus University Hospital, Denmark

Background: Large health care databases provide a cost-effective data source for observational research in the intensive care unit (ICU) if the coding is valid. The aim of this study was to investigate the accuracy of the recorded coding of ICU admission, mechanical ventilation, and acute dialysis in the population-based Danish National Patient Registry (DNPR).
Methods: We conducted the study in the North Denmark Region, including seven ICUs. From the DNPR we selected a total of 150 patients with an ICU admission by the following criteria: (1) 50 patients randomly selected among all patients registered with an ICU admission code, (2) 50 patients with an ICU admission code and a concomitant code for mechanical ventilation, and (3) 50 patients with an ICU admission code and a concomitant code for acute dialysis. Using the medical records as gold standard we estimated the positive predictive value (PPV) for each of the three procedure codes.
Results: We located 147 (98%) of the 150 medical records. Of these 147 patients, 141 (95.9%; 95% confidence interval [CI]: 91.8–98.3) had a confirmed ICU admission according to their medical records. Among patients, who were selected only on the coding for ICU admission, the PPV for ICU admission was 87.2% (95% CI: 75.6–94.5). For the mechanical ventilation code, the PPV was 100% (95% CI: 95.1–100). Forty-nine of 50 patients with the coding for acute dialysis received this treatment, corresponding to a PPV of 98.0% (95% CI: 91.0–99.8).
Conclusion: We found a high PPV for the coding of ICU admission and even higher PPVs for mechanical ventilation, and acute dialysis in the DNPR. The DNPR is a valuable data source for observational studies of ICU patients.

Keywords: critical care, epidemiology, intensive care unit, positive predictive values, validity