Validation of Algorithm to Identify Persons with Non-traumatic Spinal Cord Dysfunction in Canada Using Administrative Health Data.
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. O...
| Published in: | Topics in Spinal Cord Injury Rehabilitation Vol. 23; no. 4; pp. 333 - 343 |
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| Main Authors: | , , , , , , , , , |
| Format: | algorithm research tables/charts Journal Article |
| Published: |
KnowledgeWorks Global, Ltd
Fall2017
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=126147356&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 126147356 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10820744 0OF jtl: Topics in Spinal Cord Injury Rehabilitation issn: 10820744 maglogo: N pubinfo: dt: Fall2017 vid: 23 iid: 4 pid: 81084 pub: KnowledgeWorks Global, Ltd place: Richmond, Virginia artinfo: ui: 126147356 126147356 126147356 10.1310/sci2304-333 126147356 ppf: 333 ppct: 10 formats: fmt: @attributes: type: P tig: atl: Validation of Algorithm to Identify Persons with Non-traumatic Spinal Cord Dysfunction in Canada Using Administrative Health Data. aug: au: Ho, Chester Guilcher, Sara J. T. McKenzie, Nicole Mouneimne, Magda Williams, Anita Voth, Jennifer Yan Chen Cronin, Shawna Noonan, Vanessa K. Jaglal, Susan B. affil: Division of Physical Medicine & Rehabilitation, Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta sug: subj: Spinal Cord Diseases Diagnosis Algorithms Evaluation Resource Databases, Health Alberta International Classification of Diseases Retrospective Design Validation Studies Record Review Sensitivity and Specificity Predictive Value of Tests Confidence Intervals Human Funding Source ab: 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. pubtype: Academic Journal doctype: algorithm research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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