Reliability of in-hospital mortality as a quality indicator in clinical quality registries. A case study in an intensive care quality register

Methods Inf Med. 2013;52(5):432-40. doi: 10.3414/ME12-02-0070. Epub 2013 Jun 28.


Objectives: Errors in the registration or extraction of patient outcome data, such as in-hospital mortality, may lower the reliability of the quality indicator that uses this (partly) incorrect data. Our aim was to measure the reliability of in-hospital mortality registration in the Dutch National Intensive Care Evaluation (NICE) registry.

Methods: We linked data of the NICE registry with an insurance claims database, resulting in a list of discrepancies in in-hospital mortality. Eleven Intensive Care Units (ICUs) were visited where local data sources were investigated to find the true in-hospital mortality status of the discrepancies and to identify the causes of the data errors in the NICE registry. Original and corrected Standardized Mortality Ratios (SMRs) were calculated to determine if conclusions about quality of care changed compared to the national benchmark.

Results: In eleven ICUs, 23,855 records with 460 discrepancies were identified of which 255 discrepancies (1.1% of all linked records) were due to incorrect in-hospital mortality registration in the NICE registry. Two programming errors in computer software of six ICUs caused 78% of errors, the remainder was caused by manual transcription errors and failure to record patient outcomes. For one ICU the performance became concordant with the national benchmark after correction, instead of being better.

Conclusions: The reliability of in-hospital mortality registration in the NICE registry was good. This was reflected by the low number of data errors and by the fact that conclusions about the quality of care were only affected for one ICU due to systematic data errors. We recommend that registries frequently verify the software used in the registration process, and compare mortality data with an external source to assure consistent quality of data.

Keywords: Quality assurance; hospital mortality; registries; risk adjustment; root cause analysis.

MeSH terms

  • Data Mining
  • Databases, Factual
  • Hospital Mortality*
  • Humans
  • Intensive Care Units*
  • Netherlands
  • Organizational Case Studies
  • Quality Indicators, Health Care*
  • Registries*
  • Reproducibility of Results