Estimating the Prevalence of Treated Epilepsy Using Administrative Health Data and Its Validity: ESSENCE Study
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JCN Open Access ORIGINAL ARTICLE pISSN 1738-6586 / eISSN 2005-5013 / J Clin Neurol 2016;12(4):434-440 / http://dx.doi.org/10.3988/jcn.2016.12.4.434 Estimating the Prevalence of Treated Epilepsy Using Administrative Health Data and Its Validity: ESSENCE Study Seo-Young Leea, Soo-Eun Chungb c d zzFew of the epidemiologic studies of epilepsy have utilized well- Dong Wook Kim , So-Hee Eun Background and Purpose validated nationwide databases. We estimated the nationwide prevalence of treated epilepsy Hoon Chul Kange, Yong Won Chof based on a comprehensive medical payment database along with diagnostic validation. Sang Do Yig, Heung Dong Kime h MethodszzWe collected data on patients prescribed of antiepileptic drugs (AEDs) from the Ki-Young Jung Health Insurance Review and Assessment service, which covers the entire population of Ko- Hae-Kwan Cheongb rea. To assess the diagnostic validity, a medical records survey was conducted involving 6,774 on behalf of the Committee patients prescribed AEDs from 43 institutions based on regional clusters and referral levels on Epidemiology of Korean across the country. The prevalence of treated epilepsy was estimated by projecting the diag- Epilepsy Society nostic validity on the number of patients prescribed AEDs. aDepartment of Neurology, ResultszzThe mean positive predictive value (PPV) for epilepsy was 0.810 for those prescribed Kangwon National University AEDs with diagnostic codes that indicate epilepsy or seizure (Diagnosis-E), while it was 0.066 College of Medicine, Chuncheon, Korea b for those without Diagnosis-E. The PPV tended to decrease with age in both groups, with lower Department of Social and Preventive Medicine, Sungkyunkwan University values seen in females. The prevalence was 3.84 per 1,000, and it was higher among males, chil- School of Medicine, Suwon, Korea dren, and the elderly. cDepartment of Neurology, Konkuk University, ConclusionszzThe prevalence of epilepsy in Korea was comparable to that in other East Asian School of Medicine, Seoul, Korea dDepartment of Pediatrics, Korea University countries. The diagnostic validity of administrative health data varies depending on the College of Medicine, Ansan, Korea method of case ascertainment, age, and sex. The prescriptions of AEDs even without relevant eDepartment of Pediatrics, Yonsei University diagnostic codes should be considered as a tracer for epilepsy. College of Medicine, Seoul, Korea fDepartment of Neurology, Key Wordszz epilepsy, seizure, prevalence, health data, epidemiology, validation. Keimyung University School of Medicine, Daegu, Korea gYiSangDo Neurology Clinic, Daegu, Korea hDepartment of Neurology, Seoul National University College of Medicine, Seoul, Korea INTRODUCTION Epilepsy is a common neurologic disorder, with a reported prevalence ranging from 2.2 1 Received January 26, 2016 to 17.6 per 1,000. Until recently, epidemiologic reports on the prevalence of epilepsy in Revised February 27, 2016 Korea were lacking. Previously the authors reported the prevalence of treated epilepsy based Accepted February 29, 2016 on the diagnostic codes for claims and the antiepileptic drugs (AEDs) prescribed, using Correspondence the database from the National Health Insurance (NHI), public third party payment sys- Ki-Young Jung, MD tem.2 That study found that the overall prevalence was 2.41 per 1,000, which is very near Department of Neurology, Seoul National University Hospital, 101 Daehak-ro, to the bottom of the range of the rates found in other countries. However, because the di- Jongno-gu, Seoul 03080, Korea agnostic codes of the NHI database were generated for claims, it is crucial to validate the Tel +82-2-2072-4988 Fax +82-2-3672-7553 accuracy of these codes. Although the use of administrative health data for epidemiologic E-mail [email protected] studies has been increasing, few studies have estimated the prevalence adjusted by diagnos- Hae-Kwan Cheong, MD tic validity. The diagnostic validity may depend on demographic, institutional, or clinical Department of Social and Preventive Medicine, Sungkyunkwan University variables, and applying validity that is specific for subgroups will allow more accurate esti- School of Medicine, 2066 Seobu-ro, mation of prevalence. Jangan-gu, Suwon 16419, Korea Tel +82-31-299-6300 cc This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Com- Fax +82-31-299-6299 mercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial E-mail [email protected] use, distribution, and reproduction in any medium, provided the original work is properly cited. 434 Copyright © 2016 Korean Neurological Association JCN Open Access Lee SY et al. JCN In this study we aimed to estimate the age- and sex-specific PPV derived from the medical records survey involving the prevalence of epilepsy with less bias, by using a nationwide number of initially presumed epilepsy patients from the HIRA database supplemented by extensive validation performed database after stratifying for covariates (Fig. 1). using a medical records survey of the representative sample. This study was approved by the Institutional Review Board (IRB) of the lead institutes (approval number: AN10221-001) METHODS and all participating institutes with an IRB. Study design Data sources We conducted two surveys in parallel: 1) a Health Insurance The national health system of Republic of Korea is based on Review and Assessment service (HIRA) database survey and the NHI system, registration in which is mandatory for the 2) a medical records survey. Data on potential epilepsy patients entire population and for all medical facilities, and Medicaid were extracted from the main HIRA database based on our (MA), which is provided through a social welfare fund for working criteria described below. We also performed a nation- registrants who are unable to pay the NHI premiums. The wide survey of medical records of patients sampled from rep- population coverage has been greater than 98% since 2005.3 resentative health institutes. Using the results of the medical This is basically a fee-for-service system, and all medical ex- records survey, we assessed positive predictive value (PPV), penditures including for medications, medical services, and the probability of the HIRA database patients having epilepsy, revenue are submitted to HIRA as separate claims. HIRA is according to diagnostic codes, age group, and sex. Finally, we a governmental third-party agency that has assessed all claims estimated the prevalence of treated epilepsy by projecting the based on diagnostic codes and medical records from NHI HIRA database survey Medical record survey (entire population, n=50,290,771) (stratified sample,n =6,774) Health resource utilization database Extraction of the data of the Cases prescribed of AEDs and Cases prescribed of AEDs and patients who received AEDs with diagnostic code without diagnostic code (n=7,282,236) (n=2,374) (n=4,400) Sort by person (n=1,119,360) Case ascertainment Case ascertainment Diagnostic validity Diagnostic validity Number of patients with AEDs Number of patients with AEDs (0.460–0.978) (0.021–0.324) and diagnostic code and without diagnostic code (n=155,307) (n=964,053) Number of epilepsy patients Number of epilepsy patients (n=126,595) (n=60,902) Estimated total number of epilepsy patients (n=187,497) Fig. 1. Study design. AEDs: antiepileptic drugs, HIRA: Health Insurance Review and Assessment service. www.thejcn.com 435 JCN Prevalence of Treated Epilepsy and MA since 2000, and from the Veterans Administration and undetermined.4 This survey method demonstrated a high since 2008. Costs for virtually all diagnostic and therapeutic validity in a preliminary study, with a sensitivity of 90% and a practices associated with epilepsy are covered by the system, specificity of 97%, and kappa statistics for interrater and test- and all related records are stored in the HIRA database. We retest reliabilities of 0.907 and 0.975, respectively.5 excluded patients under 1 year of age because we found that Multistage cluster sampling was performed in three geo- it is often difficult to determine from reviews of medical- re graphic regions (the capital, midland, and southeast areas) cords whether they have epilepsy or acute symptomatic sei- categorized based on approximately even distributions of zures at this age. institutes and population. Based on a pilot survey of three hos- pitals, the sample size was estimated at 2,000 for patients Potential patient dataset using the HIRA database prescribed AEDs with Diagnosis-E, and 4,000 for those pre- Our working criterion for extracting potential patients with scribed without Diagnosis-E. Finally, we surveyed 6,774 pa- epilepsy from the HIRA database was a prescription for at tients from 43 institutes distributed throughout the country, least one AED according to the list of claims in 2009. The comprising 4 tertiary referral hospitals, 29 general hospi- list of AEDs, based on those available in 2009 in Korea, in- tals, 8 hospitals, and 2 private clinics. cluded carbamazepine, clobazam, ethosuximide, gabapen- tin, lamotrigine, levetiracetam, oxcarbazepine, phenobarbi- Estimation of prevalence tal, phenytoin, pregabalin, primidone, topiramate, vigabatrin, The PPV for epilepsy was calculated as the number of patients valproate, and zonisamide. Clonazepam was excluded be- with true epilepsy divided by the total number of patients cause it is rarely used as a monotherapy for epilepsy and is prescribed AEDs, for age, sex, and diagnostic categories. used more frequently in other conditions. Other AEDs, in- The total number of the cases was estimated as cluding primidone, felbamate, esclicarbazepine, lacosamide, N=NDi×PDi+NMi×PMi, and tiagabine, were not available in 2009. EDi EMi where PDi= , PMi= , Potential epilepsy patients were classified into two cate- Di Mi gories: those prescribed AEDs with and without diagnostic NDi is the number of patients prescribed AEDs with Diagno- codes indicating epilepsy or seizure (Diagnosis-E), based on sis-E according to the HIRA claims data, NMi is the number of either the principal or additional diagnostic code for the claim.