Journal of the Health Care and Life Science (보건의료생명과학 논문지)

The Korean Society of Medical Informatics Education (한국의료정보교육협회)
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A Study on SQL Practice Model for Data Analysis Using Chat GPT in Insurance Claims Databas

보험 청구 데이터베이스에서 Chat GPT를 이용한 데이터 분석을 위한 SQL 실습 모델 연구

  • Joon-Young Choi (Dept. of Medical Administration, Wonkwang Health Science University)
  • 최준영 (원광보건대학교 의무행정과)
  • Received : 2023.06.09
  • Accepted : 2023.07.07
  • Published : 2023.07.31
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Abstract

In this study, a practice model that can improve healthcare information management ability using Chat GPT and SQL was studied. For SQL utilization, learners were asked to use Chat GPT to easily access the database and write SQL for data extraction. For the contents analyzed in the claims database, the sum of insurance claim amount, insurance claim amount by treatment item, claim details corresponding to a specific amount, other diagnosis names of specific prescription patients, examination details of specific diagnosis names, and total amount by item were calculated. As a result of executing SQL statements written for each subject in Chat GPT, it was confirmed that the analysis contents were the same. It is believed that the use of ChatGPT as progressed in this study will contribute to improving the ability of healthcare data management to increase accuracy and efficiency in database management and analysis work, rather than simply simplifying or automating tasks.

본 연구에서는 Chat GPT와 SQL을 활용하여 보건의료정보 관리 능력을 향상시킬 수 있는 실습모델을 연구하였다. SQL 활용을 위해서 학습자가 Chat GPT를 사용하여 데이터베이스에 쉽게 접근하고 데이터 추출을 위한 SQL 작성을 요청하였다. 청구 데이터베이스에서 분석한 내용은 보험청구금액의 합계, 진료항목별 보험 청구금액, 특정 금액에 해당하는 청구내역, 특정 처방환자의 기타 진단명, 특정 진단명의 검사내역, 항목별 합계금액을 산출하였다. Chat GPT에서 각 주제별로 작성된 SQL 문장으로 실행한 결과분석내용이 동일한 것을 확인하였다. 본 연구에서 진행한 바와 같이 ChatGPT를 사용하는 것은 단순히 업무를 단순화하거나 자동화하는 것이 아니라, 데이터베이스 관리 및 분석 작업에서의 정확성과 효율성을 높이는 보건의료데이터 관리의 역량을 향상시키는데 기여할 수 있을것이라고 사료된다.

Keywords

Acknowledgement

본 논문은 2023년도 원광보건대학교 교내연구비 지원에 의해서 수행되었음.

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