Validation process of a high-resolution database in a paediatric intensive care unit-Describing the perpetual patient's validation

J Eval Clin Pract. 2021 Apr;27(2):316-324. doi: 10.1111/jep.13411. Epub 2020 May 5.

Abstract

Rationale: High data quality is essential to ensure the validity of clinical and research inferences based on it. However, these data quality assessments are often missing even though these data are used in daily practice and research.

Aims and objectives: Our objective was to evaluate the data quality of our high-resolution electronic database (HRDB) implemented in our paediatric intensive care unit (PICU).

Methods: We conducted a prospective validation study of a HRDB in a 32-bed paediatric medical, surgical, and cardiac PICU in a tertiary care freestanding maternal-child health centre in Canada. All patients admitted to the PICU with at least one vital sign monitored using a cardiorespiratory monitor connected to the central monitoring station.

Results: Between June 2017 and August 2018, data from 295 patient days were recorded from medical devices and 4645 data points were video recorded and compared to the corresponding data collected in the HRDB. Statistical analysis showed an excellent overall correlation (R2 = 1), accuracy (100%), agreement (bias = 0, limits of agreement = 0), completeness (2% missing data), and reliability (ICC = 1) between recorded and collected data within clinically significant pre-defined limits of agreement. Divergent points could all be explained.

Conclusions: This prospective validation of a representative sample showed an excellent overall data quality.

Keywords: big data; critical care; database; electronic health record; paediatrics.

MeSH terms

  • Canada
  • Child
  • Databases, Factual
  • Humans
  • Intensive Care Units, Pediatric*
  • Prospective Studies
  • Reproducibility of Results