Level of Agreement and Factors Associated With Discrepancies Between Nationwide Medical History Questionnaires and Hospital Claims Data

김연용; 박종헌; 강희진; 이은주; 하성준; 신순애

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자료유형: 학술저널

저자정보: 김연용 박종헌 강희진 이은주 하성준 신순애

저널정보: 대한예방의학회 예방의학회지 예방의학회지 제50권 제5호

발행연도: 2017.1

수록면: 294 - 302 (9page)

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Objectives: The objectives of this study were to investigate the agreement between medical history questionnaire data and claims data and to identify the factors that were associated with discrepancies between these data types. Methods: Data from self-reported questionnaires that assessed an individual’s history of hypertension, diabetes mellitus, dyslipidemia, stroke, heart disease, and pulmonary tuberculosis were collected from a general health screening database for 2014. Data for these diseases were collected from a healthcare utilization claims database between 2009 and 2014. Overall agreement, sensitivity, specificity, and kappa values were calculated. Multiple logistic regression analysis was performed to identify factors associated with discrepancies and was adjusted for age, gender, insurance type, insurance contribution, residential area, and comorbidities. Results: Agreement was highest between questionnaire data and claims data based on primary codes up to 1 year before the completion of self-reported questionnaires and was lowest for claims data based on primary and secondary codes up to 5 years before the completion of self-reported questionnaires. When comparing data based on primary codes up to 1 year before the completion of self-reported questionnaires, the overall agreement, sensitivity, specificity, and kappa values ranged from 93.2 to 98.8%, 26.2 to 84.3%, 95.7 to 99.6%, and 0.09 to 0.78, respectively. Agreement was excellent for hypertension and diabetes, fair to good for stroke and heart disease, and poor for pulmonary tuberculosis and dyslipidemia. Women, younger individuals, and employed individuals were most likely to under-report disease. Conclusions: Detailed patient characteristics that had an impact on information bias were identified through the differing levels of agreement.

#Information bias #Memory decay #Data accuracy #Self-report #Sensitivity and specificity #Kappa statistics

참고문헌 (24)

참고문헌 신청

Bergmann MM / 2004 / Agreement of self-reported medical history: comparison of an in-person interview with a self-administered questionnaire / Eur J Epidemiol 19 (5) : 411 ~

Brewer NT / 2002 / Cholesterol control, medication adherence and illness cognition / Br J Health Psychol 7 (Part 4) : 433 ~ 447

Cheol Seong S / 2016 / Data resource profile: the national health information database of the National Health Insurance Service in South Korea / Int J Epidemiol pii : dyw253

Coughlin SS / 1990 / Recall bias in epidemiologic studies / J Clin Epidemiol 43 (1) : 87 ~ 91

Egan BM / 2010 / US trends in prevalence, awareness, treatment, and control of hypertension, 1988-2008 / JAMA 303 (20) : 2043 ~ 2050

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