Development and validation of a case definition for epilepsy for use with administrative health data
Introduction
The global burden of epilepsy is high, with 50 million cases worldwide and a prevalence of 4–8 per 1000 (Forsgren et al., 2005, World Health Organization, 2006). While epilepsy is the second most commonly reported neurological condition worldwide (Murray et al., 1994), there are currently no ongoing surveillance activities for epilepsy regionally, provincially, or nationally in Canada. International Classification of Disease (ICD) codes are used worldwide and are routinely collected and maintained in administrative databases. These data are a valuable source of information including both inpatient and outpatient healthcare encounters. As such, administrative data consisting of ICD-9-CM or ICD-10 codes can be used for studies and surveillance and have already been used successfully in Canada and the US for surveillance of acute and chronic conditions including diabetes and traumatic brain injury (Asghari et al., 2009, Centers for Disease Control and Prevention, 2011, Chen et al., 2010, Hux et al., 2002).
Epilepsy ICD-9-CM and ICD-10 coding has previously been validated in emergency room (ER) and hospital discharge data in a large Canadian region (Calgary, Alberta, Canada) (Jette et al., 2010), as well as in other countries (Christensen et al., 2007, Parko and Thurman, 2009, Pugh et al., 2008). However, in order to develop a comprehensive national population-based epilepsy registry, it is also critical to validate outpatient databases. Physician claims data capture both outpatient and inpatients visits; and are a valuable source for surveillance for epilepsy. However, physician claims data have not yet been validated for epilepsy coding in Canada. The aims of our study were to: (1) validate epilepsy coding in physician claims data; (2) develop validated coding algorithms for epilepsy using inpatient and physician claims data (capturing both inpatient and outpatient visits); and (3) assess whether adding an ER database to the inpatient and physician claims databases enhances the epilepsy case validity.
Section snippets
Patient population
We randomly selected 720/2049 visits (35% of all visits) from the fiscal year April 1, 2002–March 31, 2004 and 1533/3252 visits (47% of all visits) from the fiscal year April 1, 2005–March 31, 2007 from 13 neurologists’ practices in Calgary, Alberta, Canada for chart review as the “gold standard” for diagnosis. All adults ages 18 and older were eligible for inclusion.
Chart samples for validation
Two trained physicians with epilepsy management expertise reviewed each chart to determine if the patient had epilepsy,
Results
Of 2253 charts reviewed, 52% and 48% of charts were from epilepsy and neurology clinics respectively. Age groups were represented as follows: age 18–44 years 53.3%, age 45–65 years 35.3%, age 66–99 years 11.4%. Epilepsy cases represented 44% of charts reviewed, while 1% were associated with patients who had convulsions (but not epilepsy), and 55% were other diagnoses. The most common epilepsy diagnoses based on chart review (reviewer assigned code using ICD-9 or 10) were 345.4
Discussion
Utilizing chart data as the “gold standard” for diagnosis, this study assessed the accuracy and validity of ICD-9-CM and ICD-10 coding for epilepsy patients followed by neurologists. We found that a majority of epilepsy cases can be accurately identified in administrative data using the following case definition: 2 physician claims or 1 hospitalization in 2 years coded with the epilepsy ICD-9 code 345 or ICD-10 codes G40 or G41. This case definition balances the need for both sensitivity and
Acknowledgments
This study was funded by a grant from the Public Health Agency of Canada to N. Jette. N. Jette holds a salary award from Alberta Innovates Health Solutions (AI-HS) and a Canada Research Chair Tier 2 in Neurological Population Health and Health Services Research. H. Quan holds an AI-HS Population Health Investigator Award. S. Wiebe holds the Hopewell Professorship of Clinical Neurosciences Research at the University of Calgary.
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