An administrative data algorithm to identify traumatic spinal cord injured patients: a validation study.
OBJECTIVE
To assess the validity of different administrative data sources available for the identification of traumatic spinal cord injured (TSCI) patients.


METHODS
Retrospective validation study.


METHODS
Ontario, Canada.


METHODS
Adult patients seen in tertiary outpatient spinal cord rehabilitation clinics after 1 April 2002.


METHODS
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).


CONCLUSIONS
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.


BACKGROUND
This study was funded by a grant from the Division of Urology, Western University.
1] Department of Surgery, Western University, London, Ontario, Canada [2] Institute for Clinical Evaluative Sciences-Western (ICES Western), London, Ontario, Canada.
B
B
Welk
Department of Physical Medicine and Rehabilitation, Western University, London, Ontario, Canada.
E
E
Loh
Institute for Clinical Evaluative Sciences-Western (ICES Western), London, Ontario, Canada.
S Z
SZ
Shariff
Institute for Clinical Evaluative Sciences-Western (ICES Western), London, Ontario, Canada.
K
K
Liu
Department of Clinical Neurologic Sciences, Western University, London, Ontario, Canada.
F
F
Siddiqi
D000328:Adult; D000465:Algorithms; D059019:Clinical Coding / Q000379:methods / Q000592:standards*; D005260:Female; D006801:Humans; D038801:International Classification of Diseases; D008297:Male; D008875:Middle Aged; D009864:Ontario; D013119:Spinal Cord Injuries / Q000145:classification*