Using health administrative databases to identify mechanical ventilation in transported pediatric critically ill patients. Issue 6 (2nd November 2021)

• Record Type: Journal Article
• Authors: Tijssen, J. A.; Richard, L.; Shariff, S. Z.; To, T.; Parshuram, C.
• Is Part Of: Canadian journal of respiratory, critical care, and sleep medicine =. Volume 5:Issue 6(2021)
• Page Start: 380
• Page End: 385
• Publication Date: 2021-11-02
• Subjects: Mechanical ventilation -- critical care -- pediatrics -- population-health; Lungs -- Diseases -- Periodicals; Critical care medicine -- Periodicals; Sleep apnea syndromes -- Periodicals; 616.2005
• DOI: 10.1080/24745332.2020.1802627
• Languages: English
• ISSNs: 2474-5332

Abstract

Abstract: RATIONALE: Accurate identification of children who received mechanical ventilation (MV) is important for operational decisions related to resource allocation and to provide valid population-level evaluations of critically ill children. OBJECTIVES: The object of this study was to validate health administrative database codes for the identification of MV in children. METHODS: Algorithms composed of hospital-based Canadian Classification of Health Interventions (CCI) and physician billing codes were validated against a reference dataset composed of critically ill pediatric patients transported to the pediatric critical care unit at the Hospital for Sick Children in Toronto, Canada between 2004 and 2012. MEASUREMENTS: Descriptive statistics, sensitivity, specificity and positive and negative predictive values (PPV and NPV, respectively) were obtained. MAIN RESULTS: Of 611 patients, 75% received MV, and of these, 94% received invasive MV only. For all types of MV (invasive and noninvasive), CCI and billing codes had a sensitivity of 85.6% and 87.8% and a specificity of 67.8% and 41.4%, respectively. The combination of CCI and billing codes yielded a sensitivity of 98% and a specificity of 37.5% for MV. Invasive MV CCI codes had a sensitivity of 86.3% and specificity of 71.5%. When only noninvasive MV CCI codes were tested, the sensitivity was 40.2% and the specificity was 97.1%. The PPV was highest using the CCI codes alone for any MV (89%) and for invasive MV (88%). CONCLUSIONS: The combination of CCI and billing codes yielded an excellent sensitivity for MV; however, there is a risk of overestimating MV as specificity was low for all algorithms.