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The Ottawa SAH search algorithms: protocol for a multi- centre validation study of primary subarachnoid hemorrhage prediction models using health administrative data (the SAHepi prediction study protocol)

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dc.contributor.author English, S. W
dc.contributor.author McIntyre, L.
dc.contributor.author Saigle, V.
dc.contributor.author Chassé, M.
dc.contributor.author Fergusson, D. A
dc.contributor.author Turgeon, A. F
dc.contributor.author Lauzier, F.
dc.contributor.author Griesdale, D.
dc.contributor.author Garland, A.
dc.contributor.author Zarychanski, R.
dc.contributor.author Algird, A.
dc.contributor.author van Walraven, C.
dc.date.accessioned 2018-10-01T03:22:38Z
dc.date.issued 2018-09-15
dc.identifier.citation BMC Medical Research Methodology. 2018 Sep 15;18(1):94
dc.identifier.uri https://doi.org/10.1186/s12874-018-0553-3
dc.identifier.uri http://hdl.handle.net/1993/33480
dc.description.abstract Abstract Background Conducting prospective epidemiological studies of hospitalized patients with rare diseases like primary subarachnoid hemorrhage (pSAH) are difficult due to time and budgetary constraints. Routinely collected administrative data could remove these barriers. We derived and validated 3 algorithms to identify hospitalized patients with a high probability of pSAH using administrative data. We aim to externally validate their performance in four hospitals across Canada. Methods Eligible patients include those ≥18 years of age admitted to these centres from January 1, 2012 to December 31, 2013. We will include patients whose discharge abstracts contain predictive variables identified in the models (ICD-10-CA diagnostic codes I60** (subarachnoid hemorrhage), I61** (intracranial hemorrhage), 162** (other nontrauma intracranial hemorrhage), I67** (other cerebrovascular disease), S06** (intracranial injury), G97 (other postprocedural nervous system disorder) and CCI procedural codes 1JW51 (occlusion of intracranial vessels), 1JE51 (carotid artery inclusion), 3JW10 (intracranial vessel imaging), 3FY20 (CT scan (soft tissue of neck)), and 3OT20 (CT scan (abdominal cavity)). The algorithms will be applied to each patient and the diagnosis confirmed via chart review. We will assess each model’s sensitivity, specificity, negative and positive predictive value across the sites. Discussion Validating the Ottawa SAH Prediction Algorithms will provide a way to accurately identify large SAH cohorts, thereby furthering research and altering care.
dc.rights info:eu-repo/semantics/openAccess
dc.title The Ottawa SAH search algorithms: protocol for a multi- centre validation study of primary subarachnoid hemorrhage prediction models using health administrative data (the SAHepi prediction study protocol)
dc.type Journal Article
dc.type info:eu-repo/semantics/article
dc.language.rfc3066 en
dc.rights.holder The Author(s).
dc.date.updated 2018-10-01T03:22:38Z


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