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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2018.1
- 수록면
- 1 - 8 (8page)
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Background: Linkage of public healthcare data is useful in stroke research because patients may visit different sectors of the health system before, during, and after stroke. Therefore, we aimed to establish high-quality big data on stroke in Korea by linking acute stroke registry and national health claim databases. Methods: Acute stroke patients (n = 65,311) with claim data suitable for linkage were included in the Clinical Research Center for Stroke (CRCS) registry during 2006–2014. We linked the CRCS registry with national health claim databases in the Health Insurance Review and Assessment Service (HIRA). Linkage was performed using 6 common variables: birth date, gender, provider identification, receiving year and number, and statement serial number in the benefit claim statement. For matched records, linkage accuracy was evaluated using differences between hospital visiting date in the CRCS registry and the commencement date for health insurance care in HIRA. Results: Of 65,311 CRCS cases, 64,634 were matched to HIRA cases (match rate, 99.0%). The proportion of true matches was 94.4% (n = 61,017) in the matched data. Among true matches (mean age 66.4 years; men 58.4%), the median National Institutes of Health Stroke Scale score was 3 (interquartile range 1–7). When comparing baseline characteristics between true matches and false matches, no substantial difference was observed for any variable. Conclusion: We could establish big data on stroke by linking CRCS registry and HIRA records, using claims data without personal identifiers. We plan to conduct national stroke research and improve stroke care using the linked big database.
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참고문헌 (22)
참고문헌 신청
Silveira DP / 2009 / Accuracy of probabilistic record linkage applied to health databases: systematic review / Rev Saude Publica 43(5):875~882
Bohensky MA / 2010 / Data linkage: a powerful research tool with potential problems / BMC Health Serv Res 10(1):346
Harron KL / 2017 / A guide to evaluating linkage quality for the analysis of linked data / Int J Epidemiol 46(5):1699~1710
Jutte DP / 2011 / Administrative record linkage as a tool for public health research / Annu Rev Public Health 32(1):91~108
Ido MS / 2015 / Administrative data linkage to evaluate a quality improvement program in acute stroke care, Georgia, 2006–2009 / Prev Chronic Dis 12:E05
Bohensky MA / 2010 / Data linkage: a powerful research tool with potential problems / BMC Health Serv Res 10(1):346
Harron KL / 2017 / A guide to evaluating linkage quality for the analysis of linked data / Int J Epidemiol 46(5):1699~1710
Jutte DP / 2011 / Administrative record linkage as a tool for public health research / Annu Rev Public Health 32(1):91~108
Ido MS / 2015 / Administrative data linkage to evaluate a quality improvement program in acute stroke care, Georgia, 2006–2009 / Prev Chronic Dis 12:E05
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