디지털융복합연구 (Journal of Digital Convergence)

  • 제16권12호
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  • Pages.533-540
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  • 2018
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  • 2713-6434(pISSN)
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  • 2713-6442(eISSN)
한국디지털정책학회 (The Society of Digital Policy and Management)
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우리나라 의료기관의 질병 코딩 불일치성 분석 : 외래환자 건강보험 청구 자료를 중심으로

An Analysis of the Disagreement in Disease Coding in South Korean Medical Institutions: Focusing on the Health Insurance Claim Data of Outpatients

  • 전윤희 (충청대학교 보건의료정보과) ;
  • 강길원 (충북대학교 의학과 의료정보학 및 관리학 교실)
  • Jeon, Yun-Hee (Department of Medical Information, Chungcheong University) ;
  • Kang, Gil-Won (Department of Health Information and Management College of Medicine, Chungbuk National University)
  • 투고 : 2018.11.16
  • 심사 : 2018.12.20
  • 발행 : 2018.12.28
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초록

이 연구는 건강보험 심사평가원 자료를 이용하여 동일 환자의 동일 질환에 대하여 서로 다른 의료기관이 부여하는 질병 코딩의 불일치성을 분석하여 국가 보건 통계 질 향상을 위한 기초 자료로 활용하고자 시행하였다. 건강보험심사평가원 2014년 전체 환자 데이터셋(HIRA-NPS)에서 9,976,826건의 진료비 명세서를 연구 대상으로 하였다. 연구결과 의료기관의 이동 경로에 따라서 질병 코딩 불일치의 차이가 존재 하였고 불일치율은 보건기관 이외의 타 의료기관에서 보건기관으로 이동하였을 때 높아지는 경향이 발견되었고, 상급종합병원 간 이동하였을 때는 불일치율이 현저하게 낮았다. 본 연구의 의료기관 간 질병 코딩 불일치 현황 분석은 국내 의료기관에서 일관성 있는 질병 코딩이 이루어지기 위한 제도적 보완의 필요성을 시사하고 있다.

The purpose of this study was to use the data from the Health Insurance Review and Assessment Service to analyze the disagreement in disease coding given by different medical institutions on the same disease of the same patient and provide basic data that could help improve the quality of national public health statistics. 9,976,826 patients' data records from the Health Insurance Review and Assessment Service-National Patient Sample (HIRA-NPS) of 2014 were analyzed. The disagreement in disease coding differed by movement paths for medical institutions; the disagreement rate tended to increase when moving from a medical institution other than public health centers to a public health center and decrease remarkably when moving from a specialized general hospital to another. Therefore, this analysis of disagreement in disease coding among medical institutions suggests the need to supplement the system so that domestic medical institutions can realize consistent disease coding.

키워드

DJTJBT_2018_v16n12_533_f0001.png 이미지

Fig. 1. Analysis model (Determination of analysis unit)

Table 1. Disagreement rate by patient characteristics

DJTJBT_2018_v16n12_533_t0001.png 이미지

Table 2. Disagreement rate by medical institutions characteristics

DJTJBT_2018_v16n12_533_t0002.png 이미지

Table 3. Disagreement rate due to movement of medical institutions

DJTJBT_2018_v16n12_533_t0003.png 이미지

Table 4. Disagreement rate when moved to the same department

DJTJBT_2018_v16n12_533_t0004.png 이미지

Table 5. Disagreement rate when moved to another department

DJTJBT_2018_v16n12_533_t0005.png 이미지

참고문헌

  1. M. Farzandipour, A. Sheikhtaheri & F. Sadoug hi. (2010). Effective factors on accuracy of principal diagnosis coding based on international classification of diseases, the 10th revision (ICD-10). International Journal of Information Management, 30(1), 78-84. DOI : 10.1016 /j.ijinfomgt. 2009. 07. 002 https://doi.org/10.1016/j.ijinfomgt.2009.07.002
  2. WHO. (2016). International Classification of Diseases(ICD)-10.
  3. J. H. Lee & M. S. Sim. (2009). The accuracy of the ICD-10 code for trauma patients visiting on emergency department and the error in the ICISS. Journal of the Korean Association of Traumatology, 22(1), 108-115. UCI : G704 -SER000001561. 2009.22.1.009
  4. Y. H. Kim & K. H. Kim. (2015). Study about the relationship between Chief complaint of pure death patients using medical record information. Journal of Digital Convergence, 13(1), 407-414. DOI : 10.14400 / JDC. 2015. 13. 1. 407 https://doi.org/10.14400/JDC.2015.13.1.407
  5. Y. R. Song, M. S. Lee, D. R. Kim & K. H. Kim. (2017). A Convergence Study on the Characteristics of Length of Hospital Stays of Injured and Traumatic Death Patients - Based on the Korea National Hospital Discharge Injury Survey Data. Journal of the Korea Convergence Society, 8(5), 87-96. DOI : 10.15207/JKCS.2017.8.5.087
  6. D. Lorence. (2003). Regional variation in m edical classification agreement: benchmar king the coding gap. Journal of Medical System, 27(5), 435-443 . DOI : https://doi.org/10.1023/A:1025607805588
  7. K. H. Kim, Y. H. Kim, J. W. Park, S. Y. W On, H. Kang, H. Choi & S. T. Han. (2008). A study on the concordance rate between principal diagnosis on the Written request and final diagnosis of obstetrics and gynecologic patients. Journal of the Korean Data Analysis Society, 10(4B), 1923-1931. DOI : 10.15207/JKCS.2017.8.5.087
  8. G. S. Lee. (1995). Diagnosis coding agre ement between medical records and medical claim billing data [dissertation]. Seoul National University; Korea.
  9. J. Stausberg, N. Lehmann, D. Kaczmarek. & M. Stein. (2008). Reliability of diagnoses coding with ICD-10. International Journal of Medical Informatics, 77(2008), 50-57. DOI: 10.1016/j.ijmedinf.2006.11.005
  10. Y. J. Kim, D. R. Kim & K. H. Kim. (2018). A Study on Clinical Characteristics of Patients with Mild Cognitive Impairment at Convalescent Hospitals. Journal of the Korea Convergence Society, 9(8), 77-85. DOI : 10.15207/JKCS.2018.9.8.077
  11. http://www.koiha.kr/
  12. O. R. Moon, C. Y. Kim & M. K. Kim. (1992). Individual variations in the code of the international classification of disease for similar outpatient conditions among general practitioners. Health Policy and Management, 2(1), 66-79.
  13. Y. S. Seo, K. S. Lee, J. H. Park & S. H. Kang. (2010). A study on regional medical utilization variation of hospital inpatients in Korea, Journal of the Korea Academia-Industrial cooperation Society, 11(4), 1511-1519. UCI : G704 - 001653. 2010.11.4.037 https://doi.org/10.5762/KAIS.2010.11.4.1511
  14. S. O. Bae & G. W. Kang. (2015). A compar ative study of the disease codes between korean national health insurance claims and korean national hospital discharge in-depth injury survey. Journal of Health Policy and Management, 24(4), 322-329. DOI : 10.4332/KJHPA.2014.24.4.322
  15. S. O. Bae, G. W. Kang, Y. Boo, Y. Lee, H. S. Choi & H. Y. Choi. (2015). A Study on the Difference in Disease Coding of Doctors, Medical Insurance Review Nurses and Medical Record Administrators based on Coding Simulation. Journal of Health Informatics and Statistics, 40(3), 161-174. UCI : G704-SER000008861.2015.40.3.015
  16. Y. H. Jeon. (2018). Variation in disease coding by physician in Korea : based on outpatient claim data. Doctoral dissertation. Chungbuk National University, Cheongju Chungbuk.