An administrative data algorithm to identify traumatic spinal cord injured patients: a validation study

• Published in: Spinal cord Vol. 52; no. 1; pp. 34 - 38
• Main Authors: Welk, B, Loh, E, Shariff, S Z, Liu, K, Siddiqi, F
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.01.2014; Nature Publishing Group
• Subjects: 692/699/375/1824; 692/700/228/491; Adult; Algorithms; Anatomy; Biomedical and Life Sciences; Biomedicine; Clinical Coding - methods; Clinical Coding - standards; Female; Human Physiology; Humans; International Classification of Diseases; Male; Middle Aged; Neurochemistry; Neuropsychology; Neurosciences; Ontario; original-article; Spinal Cord Injuries - classification; Ontario; International Classification of Diseases; epidemiology; validation studies; spinal cord injuries; sensitivity and specificity
• ISSN: 1362-4393; 1476-5624; 1476-5624
• DOI: 10.1038/sc.2013.134

Objective: To assess the validity of different administrative data sources available for the identification of traumatic spinal cord injured (TSCI) patients. Study design: Retrospective validation study. Setting: Ontario, Canada. Participants: Adult patients seen in tertiary outpatient spinal cord rehabilitation clinics after 1 April 2002. Outcome measures: Sensitivity, specificity, positive and negative predicative values of diagnostic ICD10 codes from Canadian Institutes of Health Discharge Abstracts (CIHI-DAD), Rehabilitation Coding Groups (RCG) from that National Rehabilitation System (NRS), and spinal cord injury fee codes from the Ontario Healthcare Insurance Plan (OHIP). Secondary outcome was the agreement between actual lesion level and RCG/ICD10 coded lesion level. Results: The RCG codes in the NRS have high sensitivity (92%, 95% confidence interval (CI): 87–95%) and specificity (97%, 95% CI: 94–99%) for the identification of true TSCI patients, whereas CIHI-DAD ICD10 codes are highly specific (99%, 95% CI: 95–100) and moderately sensitive (76%, 95% CI: 79–87%). OHIP fee codes had poor sensitivity (64%, 95% CI: 57–71%). Agreement between true lesion level and the NRS and CIHI-DAD coding is good (Kappa of 0.65–0.88 and 0.56–0.70, respectively). Conclusion: This study demonstrated that the NRS is able to accurately discriminate between patients with and without a TSCI. A large population of incident and prevalent TSCI patients are identifiable using administrative data. Sponsorship: This study was funded by a grant from the Division of Urology, Western University.