2022 Spring DHC5031 – BMI Lab@SAIHST

2022 Spring DHC5031 Introduction to Medical Informatics

- Introductory class of biomedical informatics
- In-depth explanation on sub-areas of biomedical informatics
- This class will explain the topics of medical informatics based on healthcare data life cycle

Instructor

- Prof. Soo-Yong Shin (sy.shin (at) skku.edu)

Date & Room

- Tuesday 09:00 ~ 11:50
- Room: 슈바이처홀, 9F, Building B, Ilwon Campus
- On/Off hybrid class (real-time streaming at the offline classroom).
  - SAIHST students should attend the offline classroom.
  - Other students (including part-time students) could attend the class via webex.
  - Online link: https://skku-ict.webex.com/meet/sy.shin
  - After class, the recorded lecture will be uploaded in iCampus. Part-time students can watch this recorded lecture.

Reference (optional)

- 최윤섭, 디지털 헬스케어, 클라우드나인, 2020
  - Highly recommended
- 보건의료정보학(대한의료정보학회 저, 현문사, 2014)

Evaluation

- Attendance: 10%
  - If only onle, attendance could be pass/fail.
- Assignment: 30%
  - Assignments will be given irregularly based on the topic of each class
  - In total, there will be three assignments.
- Final term: 60%
  - It could be changed into report based on the COVID-19 status.
- Final GRADE

Assignment

- All assignments should be submitted to Instructor via email.
  - File naming convention: 의료정보학_Assignment(No)_학번_이름 ex) 의료정보학_Assignment1_20201234_홍길동.doc
- The assignement should be submitted before the next class

Final Term

- Finalterm

Course Schedule

(Course schedule can be changed.)

1. 02/22: What is medical informatics
  - Supplementary Video Lecture (Optional)
    - What is Biomedical and Health Informatics? (by William Hersh, Oregon Health & Science University)
      - You have to watch following three lectures (use Chrome browser)
        What is Biomedical and Health Informatics (1)?
        What is Biomedical and Health Informatics (2)?
        A Short History of Biomedical and Health Informatics
2. 03/01: Data acquisition (1) – Healthcare Big Data (3/1절. 동영상 수업으로 대체)
  - Reading materials
    - (Mandatory) Shilo, S., Rossman, H. & Segal, E. Axes of a revolution: challenges and promises of big data in healthcare. Nat Med 26, 29–38 (2020).
    - (Mandatory) NIH 데이터 관리 및 공유 정책 최종안 (2020) 요약
    - (Optional) NIH Strategic Plan for Data Science (2020)
3. 03/08: Data acquisition (2) – Hospital information system
  - Reading materials
    - (Optional) The Learning Healthcare System and Cardiovascular Care: A Scientific Statement From the American Heart Association
4. 03/15: Data acquisition (3) – Patient-generated health data
  - Reading materials
    - (Mandatory) IQVIA, Digital Health Trends 2021
    - (Optional) US AHRQ, Integrating Patient-Generated Digital Health Data into Electronic Health Records in Ambulatory Care Settings
5. 03/22: Data acquisition (4) – Social determinant of health
  - Reading materials
    - (Mandatory) WHO social determinants of health
    - (Optional) CODE, Leveraging data on the Social Determinants of Health
6. 03/29: Data acquisition (5) – Genome data
  - Reading materials
    - (Optional) Claussnitzer, M., Cho, J.H., Collins, R. et al. A brief history of human disease genetics. Nature 577, 179–189 (2020).
  - (Assignment #1) – (점수)
7. 04/05: Standards for healthcare data
  - Reading materials
    - (Mandatory) Digital Medicine Standards 101
    - (Optional) FHIR Trends
    - (Optional) FHIR-based HIE (in Korean)
    - (Optional) LOINC
8. 04/12: Ethics & regulation
  - Reading materials
    - (Optional) Dangers of artificial intelligence in medicine
    - (Mandatory) Process of Medical Device Approval in Korea (in Korean)
    - (Mandatory) STEP 정일영 박사님, 주요국의 의료데이터 정책 및 활용사례
    - (Optional) WHO, Ethics and governance of artificial intelligence for health
9. 04/19: P&S: De-identification of healthcare data
  - Reading materials
    - (Mandatory) 비식별 처리시 안전성 요구사항 및 수준별 보증방안 (한라대 김순석 교수님 발표자료)
    - (Optional) UN, Data Privacy, Ethics and Protection: Guidance Note on Big Data for Achievement of the 2030 Agenda
    - (Optional) KDnuggets – Data Anonymization – History and Key Ideas
  - (Assignment #2) – (점수)
10. 04/26: Data analysis (1): Clinical Research Informatics
11. 05/03: Data analysis (2): Artificial Intelligence
  - Reading materials
    - (Optional) Deep Learning Tutorial
12. 05/10: Clinical validation
  - Reading materials:
    - (Mandatory) 박성호, 최재순, 변정식, 인공지능 임상검증, 의료기기 허가, 의료보험 적용과 관련된 핵심 원리, J Korean Med Assoc 2020, 63(11): 696-708.
    - (Mandatory) Gordon, W.J., Landman, A., Zhang, H. et al. Beyond validation: getting health apps into clinical practice. npj Digit. Med. 3, 14 (2020).
  - (Assignment #3) – (점수)
13. 05/17: Business model of digital health
  - Reading materials:
    - - (Optional) 김치원, 디지털 헬스케어는 어떻게 비즈니스가 되는가, 클라우드나인, 2020
      - (Optional) 김충현, 의료기기 산업의 미래에 투자하라, 클라우드나인, 2020
14. 05/24: Recent Topics
  - Reading materials:
    - (Mandatory) 보건산업진흥원, 디지털 헬스 산업 분석 및 전망 연구 (2020.12)
    - (Mandatory) 보건산업진흥원, 디지털 헬스 서비스의 활용 효과 연구 (2021.12)
15. 05/31: Finalterm – (점수)