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. 2017 Fall;23(4):333-342.
doi: 10.1310/sci2304-333.

Validation of Algorithm to Identify Persons with Non-traumatic Spinal Cord Dysfunction in Canada Using Administrative Health Data

Chester Ho  1   2   3 , Sara J T Guilcher  4   5   6 , Nicole McKenzie  1 , Magda Mouneimne  3 , Anita Williams  3 , Jennifer Voth  7 , Yan Chen  8 , Shawna Cronin  7   9 , Vanessa K Noonan  10 , Susan B Jaglal  6   7   9   11
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Validation of Algorithm to Identify Persons with Non-traumatic Spinal Cord Dysfunction in Canada Using Administrative Health Data

Chester Ho et al. Top Spinal Cord Inj Rehabil. 2017 Fall.

Abstract

Background: Administrative health data, such as the hospital Discharge Abstract Database (DAD), can potentially be used to identify patients with non-traumatic spinal cord dysfunction (NTSCD). Algorithms utilizing administrative health data for this purpose should be validated before clinical use. Objective: To validate an algorithm designed to identify patients with NTSCD through DAD. Method: DAD between 2006 and 2016 for Southern Alberta in Canada were obtained through Alberta Health Services. Cases of NTSCD were identified using the algorithm designed by the research team. These were then validated by chart review using electronic medical records where possible and paper records where electronic records were unavailable. Measures of diagnostic accuracy including sensitivity, specificity, and positive and negative predictive values and 95% confidence intervals (CI) were computed. Results: Two hundred and eighty cases were identified to have both the administrative codes for neurological impairments and NTSCD etiology. Twenty-eight cases were excluded from analysis as 5 had inadequate medical record information, 17 had traumatic spinal cord injury, and 6 were considered "other" non-spinal cord conditions. Measures of diagnostic accuracy that were computed were sensitivity 97% (95% CI, 94%-98%), specificity 60% (95% CI, 47%-73%), positive predictive value (PPV) 92% (95% CI, 88%-95%), and negative predictive value (NPV) 80% (95% CI, 65%-90%). The most prevalent etiologies were degenerative (36.9%), infection (19.0%), oncology malignant (15.1%), and vascular (10.3%). Conclusion: Our algorithm has high sensitivity and PPV and satisfactory specificity and NPV for the identification of persons with NTSCD using DAD, though the limitations for using this method should be recognized.

Keywords: International Classification of Diseases; database; spinal cord diseases; validation studies.

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Figures

Figure 1.
Figure 1.
Non-traumatic spinal cord dysfunction (NTSCD) algorithm using International Statistical Classification of Diseases and Related Health Problems, 10th revision, Canada (ICD-10-CA) codes.
Figure 2.
Figure 2.
Calculation of measures of diagnostic accuracy. NPV = negative predictive value; PPV = positive predictive value.
See this image and copyright information in PMC

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