Development and validation of an algorithm of diagnostic and procedural codes for the identification of children hospitalized with a tracheostomy in Ontario, Canada. Issue 6 (6th April 2020)

• Record Type: Journal Article
• Authors: McKelvie, Brianna; Pianosi, Kiersten; Chan, Jason; Tsampalieros, Anne; Benchimol, Eric I.; Macdonald, Kristian I.; Strychowshy, Julie; Vaccani, Jean‐Philippe; McNally, James D.
• Is Part Of: Pediatric pulmonology. Volume 55:Issue 6(2020)
• Page Start: 1503
• Page End: 1511
• Publication Date: 2020-04-06
• Subjects: chart review -- health administrative data -- pediatrics -- ventilation; Pediatric respiratory diseases -- Periodicals; Pediatrics -- Periodicals; 618.922
• DOI: 10.1002/ppul.24757
• Languages: English
• ISSNs: 8755-6863

Abstract

Abstract: Background: The requirement for a tracheostomy in children is associated with significant morbidity, mortality, and healthcare utilization. Easy identification of children with tracheostomies would facilitate important research on this population and provide quality improvement initiatives. Aim: The purpose of this study is to determine whether an algorithm of diagnostic and procedural codes can accurately identify children hospitalized with a tracheostomy using routinely collected health data. Methods: Chart reviews were performed at the Children's Hospital of Eastern Ontario (CHEO) and the London Health Sciences Center (LHSC) to establish a true positive cohort of pediatric patients with tracheostomies admitted between 2008 and 2016. A multidisciplinary team developed algorithms of diagnostic and procedural codes contained within the Canadian Institute for Health Information Discharge Abstract Database. Algorithms were tested and refined against the true‐positive and true‐negative cohort. The accuracy of the diagnostic codes related to tracheostomy complications was also evaluated. Results: A chart review identified 158 unique children with tracheostomies (77 at CHEO, 81 at LHSC) with 901 individual admissions (401 at CHEO, 507 at LHSC). The best algorithms for identifying children with a tracheostomy had a sensitivity and specificity of more than 99%, a positive predictive value (PPV) of 94.0% and negative predictive value (NPV) of 100%. The algorithm for the identification of tracheostomy‐related complications had a sensitivity of 76.7%, a specificity of 65%, PPV of 52.3%, and an NPV of 84.7%. Conclusions: This study provides an algorithm for the accurate identification of children hospitalized in Canada with a tracheostomy, facilitating population‐level epidemiological research and quality improvement initiatives.