1) HIRA database
The public medical insurance system in South Korea covers almost all patients through the National Health Insurance (NHI) and National Medical Aid (NMA) programs. The HIRA service is a government-operated organization that builds accurate review and quality assessment systems for NHI and NMA claims. Healthcare service providers submit claims data to the HIRA for reimbursement for services provided to patients. Access to HIRA data is regulated by the Rules for Data Exploration and Utilization of the HIRA. The present study used data after receiving approval from the HIRA data access committee. All data were delivered anonymously and none of the researchers had access to any potentially identifying personal information, including the patient names, addresses, and dates of birth. This study was approved by the Institutional Review Board of Seoul National University Hospital (IRB No. E-1707-059-868).
Data on patients treated for AAA between 2012 and 2016 were extracted from the HIRA database by complete enumeration. The patients were classified according to year, regions of medical centers at which they received treatment, age, sex, and risk factors or comorbidities. All patients had one or more disease codes of AAA (I71.3, I71.4, I71.5, I71.6, I71.8, and I71.9) according to the Korean standard classification of diseases (KCD, 7th). Age was classified as underage (less than 20 years), young (20 to 39 years), middle-age (40 to 59 years), or old (60 years or more). The risk factors or comorbidities included hypertension (I10–13, I15), dyslipidemia (E78), diabetes mellitus (E10–14), coronary artery disease (I20–25, Z95.1, Z95.5), cerebral vascular accident (I60–69), chronic renal disease (N17–19, I12, I13), vasculitis (M05.2, M31.4, M32, M35.2, I77.6, I79.1), congestive heart failure (I50), and chronic obstructive pulmonary disease (J44). Smoking (F17) and obesity (E66), also well-known risk factors, were excluded due to the lack of data. The AAA type was categorized as ruptured (I71.3, I71.5, I71.8) or unruptured (I71.4, I71.6, I71.9). Additionally, surgical treatment for AAA was divided into endovascular aneurysmal repair (EVAR) or open surgical aneurysmal repair (OSAR).
Rehospitalization and patient death occurring within 30 days after AAA treatment were considered AAA-related rehospitalization and death.
① Classification of medical institutions
The medical institutions were classified according to the regions and referral grade as primary, secondary, or tertiary hospitals. A primary hospital was defined as a hospital with fewer than 100 beds. A secondary hospital was defined as a hospital with more than 100 to 300 beds and with 7 to 9 or more medical departments. A tertiary hospital was defined as a specialized center for severe diseases with 20 or more medical departments assigned at least one specialist, which was designated by the Ministry of Health and Welfare every three years. Korea contains 42 tertiary hospitals; 13 in Seoul, five in Gyeonggi, four each in Busan and Daegu, three in Incheon, two each in Chungnam, Jeonbuk, Gwangju, and Gyeongnam, and one each in Daejeon, Gangwon, Chungbuk, Jeonnam, and Gyeongbuk.
② Regional classification
South Korea was divided into seven metropolitan cities and nine provinces and the data were provided by the HIRA according to regions. Metropolitan cities, defined as a city with populations exceeding one million, included Seoul, Busan, Incheon, Daegu, Daejeon, Gwangju, and Ulsan. The regional populations as of 2016, published by the National Statistical Office, were as follows: Gyeonggi (12,671,956), Seoul (9,805,506), Busan (3,440,484), Gyeongnam (3,339,633), Incheon (2,913,024), Gyeongbuk (2,682,169), Daegu (2,461,002), Chungnam (2,132,566), Jeonbuk (1,833,168), Jeonnam (1,796,017), Chungbuk (1,603,404), Daejeon (1,535,445), Gangwon (1,521,751), Gwangju (1,501,557), Ulsan (1,166,033), and Jeju (623,332) (Statistics Korea, http://kostat.go.kr).
The statistical analyses were conducted using SAS Enterprise Guide 6.1 and SAS Enterprise Miner 13.2 (SAS Institute Inc., Cary, NC, USA). The data were analyzed in the remote analysis system provided by the HIRA. The data used in the statistical analyses were expressed as means±standard deviation and P-values <0.05 were considered statistically significant. Chi-square tests were used to evaluate the correlations between each risk factor and mortality. Statistical maps were provided by Bing Maps (Microsoft, Redmond, WA, USA).