DOI QR코드

DOI QR Code

인체 골격의 좌표형 임상용어체계 표준 개발 : SNOMED CT 기반의 융복합 연구

Development of Clinical Terminology System for Human Body : Convergence Research of SNOMED CT

  • 투고 : 2019.01.31
  • 심사 : 2019.04.20
  • 발행 : 2019.04.28

초록

본 연구는 인체 골격의 좌표형 임상용어체계 표준을 개발하기 위한 방법론적 연구이다. 문헌고찰과 자료 수집을 통해 연구 계획을 수립하여 예비 표준(안)을 만들고 전문가 세미나와 자문을 통해 수정 표준(안)을 만든 후 내용타당도 검증 후 최종(안)을 제시하는 4단계를 거쳐 표준을 개발하였다. 좌표형 임상용어체계 표준은 인체 이미지를 2D는 x, y축, 3D는 x,y,z축으로 좌표화하고, 좌표의 개념과 정의는 SNOMED CT의 FSN, Synonym, Preferred name으로 선조합하고 후조합은 개발 된 18개의 Relationship을 통해 정의되고, 개발된 Relationship 표준의 내용타당도 지수는 평균 4.01점이었다. 본 연구를 통해 인체 골격 이외의 뇌, 장기, 조직 등의 인체의 다른 부분에 대한 후속 표준 개발을 제언하고 임상에서 활용성을 높이기 위한 방법 연구를 제언한다.

This is a methodological study to develop standards for human body coordinate clinical terminology system. The Standard was developed through four stages: Stage 1 - research plan was developed through literature review and data collection. Stage 2 - preliminary standard was created. Stage 3 - the standard was revised in accordance with the consultation of experts through seminars. Stage 4 - Final version of the standard was presented after verification of the content level. 2D human body images are expressed as x, y axes, and 3D images are expressed as x, y, z axes. Concepts and definitions of coordinates were preassembled into FSN, synonyms and preferred names of SNOMED CT. The latter combination was defined through 18 relationships. The average index was 4.01 for the content validity of the developed relationship standard. This research suggests that subsequent standards should be developed for other parts of the human body such as the brain, organs, and tissues. Also, it suggests that methodological research should be continued to increase the utilization of the standard in clinical practice.

키워드

DJTJBT_2019_v17n4_177_f0001.png 이미지

Fig. 1. Method of Coordinate Human Body 3D Images

DJTJBT_2019_v17n4_177_f0002.png 이미지

Fig. 2. Clinical Terminology System for Human Body

DJTJBT_2019_v17n4_177_f0003.png 이미지

Fig. 3. Example of Coordinate Human Body 3D Images

DJTJBT_2019_v17n4_177_f0004.png 이미지

Fig. 4. Example of Clinical Terminology System of Human Body

Table 1. Course of Study

DJTJBT_2019_v17n4_177_t0001.png 이미지

Table 2. Content Validity for Standard of Clinical Terminology System for Human Body

DJTJBT_2019_v17n4_177_t0002.png 이미지

참고문헌

  1. Y. A. Ahn & H. J. Cho. (2017). Hospital System Model for Personalized Medical Service. Journal of the Korea Convergence Society, 8(12), 77-84. https://www.earticle.net/Article/A317613 https://doi.org/10.15207/JKCS.2017.8.1.077
  2. Y. S. Cho & S. C. Moon. (2015). A Study on Active Computerized Treatment Information Using Illness Pattern Analysis for Medical Recommender Service. Journal of Convergence for Information Technology, 2(1), 229-230.
  3. C. T. Kim. (2015). A Study on the Effect of Introduction of PACS and EMR System on Hospital Management Performance Effect. Journal of the Korean Data Analysis Society, 14(4), 2195-2210.
  4. S. J. Shin, C. K. Ahn & K. Y. Park. (2017). A case study on the application of new hand splint using 3D printing. Journal of the Korea Convergence Society, 7(2), 25-29. DOI:10.22156/CS4SMB.2017.7.2.025
  5. Institute of Electrical and Electronics Engineers(IEEE). (1990). Standard Computer Dictionary : A Compiliation of IEEE Standard Computer Glossaries. New york, NY.
  6. J. M. Seok, H. R. Jung, C. H. Iim, J. K. Kim & J. K. Park. (2008). Analysis about Planning Introduction PACS in Hospital Scale and Equipment Operation of Radiology Department. Journal of Digital Contents Society, 8(12), 322-333.
  7. Y. J. Song, H. S. Woo, H. S. Lee, M. Y. Lee. L. Y. Kwon & Y. J. Cha. (2016). A Study on Standard Terminology for Occupational Therapy Documentations Focusing on Korean-Type Medical Institutions. The Journal of Korean Society of Occupational Therapy. 24(2), 112-124. http://www.riss.kr/link?id=A101970140
  8. Y. S. Yoon, J. H. Yoon, W. G. Min, H. S. Lim, J. H. Song, S. R. Chae, C. G. Lee & J. A. Kwon. (2007). Standardization of Terminology in Laboratory Medicine I. Annals of Laboratory Medicine, 27(2), 151-155. https://doi.org/10.3343/kjlm.2007.27.2.151
  9. S. K. Lee. (2015). Development of u-Health standard terminology and guidelines for terminology standardization. Joural of the Korea Academia-Industrial cooperation Society, 16(6), 4056-4066. http://www.adbpia.co.kr/Article/NODE07214411 https://doi.org/10.5762/KAIS.2015.16.6.4056
  10. J. W. Baek & Y. K. Chung. (2006). A Study on the Development of a Classification Model for Terminological Relationships. Journal of the Korean Society for Information Management, 23(1), 63-81. http://www.riss.kr/link?id=A75802368 https://doi.org/10.3743/KOSIM.2006.23.1.063
  11. H. A. Park, H. Y. Kim & Y. H. Min. (2012). Use of clinical terminology for semantic interoperability of electronic health records. Journal of the Korean Medical Association, 55(8), 720-728. https://doi.org/10.5124/jkma.2012.55.8.720
  12. M. Q. Stearns, C. Price, K. A. Spackman & A. Y. Wang. (2013). SNOMED Clinical terms: overview of the development process and project status. Proc AMIA Symp, 662-666.
  13. J. M. Seo, M. C. Han, H. S. Lee, S. H. Lee & C. H Kim. (2017). Development of 4D CT Data Generation Program based on CAD Models through the Convergence of Biomedical Engineering Journal of the Korea Convergence Society, 8(4), 131-137. https://www.earticle.net/Article/A300694 https://doi.org/10.15207/JKCS.2017.8.4.131
  14. H. Ameddah & M. Assas. (2013). Three- Dimensional (3D) Bio-Cad Modeling of Human Knee. Advanced Science Letters, 19(3), 932-936. DOI:10.1166/asl.2013.4830
  15. SNOMED CT User Guide January 2013. (2013). International Release International Health Terminology Standards Development Organisation.
  16. M. R. Lynn. (1986). Determination and quantification of content validity. Nursing Research, 35(6), 382-385. http://dx.doi.org/10.1097/00006199-198611000-00017
  17. IHTSDO. SNOMED CT Technical Implementation Guide. (2018). [Internet] Available: https://confluence.ihtsdotools.org/display/DOCTIG/Tech nical+Implementation+Guide
  18. H. Y. Kim, I. S. Cho, J. H. Lee, J. H. Kim & Y. Kim. (2008). Concept representation of decision logic for hypertension management using SNOMED CT. Healthcare Informatics Research, 14(4), 395-403.