초록

○ 국내외 의료기관이 벤치마킹할 수 있는 상시위기대응체계 모델 개발
○ 입원 중 발생하는 신경학적 응급상황 고위험군 선별(스크리닝 점수 개발), 선제 대응(이상 징후 감지 인공지능 개발), 응급 대응(검사와 치료 소요 시간 단축 프로세스 마련), 후속 조치(급성기 추적 진료 및 퇴원 후 재발 평가), 유효성 검증(스크리닝 점수 체계와 인공지능 예측력)을 포괄하는 프로세스 마련

(출처 : 요약서 3p)

Abstract ▼

□ Purpose&Contents
To establish neurological rapid response system for in-hospital neurological emergencies
○ Development of a screening tool to detect patients with high risks for in-hospital neurological emergencies
- To analyze risk factor using In-hospital electronic medical record and

□ Purpose&Contents
To establish neurological rapid response system for in-hospital neurological emergencies
○ Development of a screening tool to detect patients with high risks for in-hospital neurological emergencies
- To analyze risk factor using In-hospital electronic medical record and NAT registry
○ Development of a screening tool using artificial intelligence for early detection of in-hospital neurological emergencies
- To develop an AI tool using big data from electronic medical records
○ Improvement of work-flows to diagnose and manage patients with neurological emergencies
- Prevention and education of patients with high risk for emergencies
- AI-based real-time monitoring and preemptive measures for early detection patients
- In-hospital neurological patient emergency care
○ To present clinical outcomes and a follow-up model for after acute care for neurological emergencies
- To prevent early neurological deterioration during hospitalization
- To prevent late neurological deterioration after hospital discharge

□ Results
○ We developed a model of a neurological rapid response system that can be a benchmarking model by other domestic and oversea institutions.
○ We developed a screening tool of a neurological high-risk group for in-hospital neurological emergencies (neurological alert team - neurological early warning score, NAT-NEWS), preemptive management (neurological alert team - artificial intelligence, NAT-AI), emergency management, follow-up, and validation protocol.

□ Expected Contribution
○ Application Plan
- Validation from other institutions and conducting a multi-center study
- Technology transfer and commercialization for on-site application of neurological early detection program
- Development of medical quality indicators
- Promotion of various follow-up research using registry, big data, and artificial intelligence
○ Expected Effect
- Improvement of medical standards by enhancing patient safety
- Completion of unmet needs regarding lack of human resources in the real world
- Benchmarking by domestic and oversea institutions
- Pioneering a new area in the fields of neurology and critical care

(출처 : SUMMARY 5p)

목차 Contents

• 표지 ... 1
• 제출문 ... 2
• 보고서 요약서 ... 3
• 국문 요약문 ... 4
• SUMMARY ... 5
• 목차 ... 6
• 1. 연구개발과제의 개요 ... 7
• 1-1. 연구개발 목적 ... 7
• 1-2. 연구개발의 필요성 ... 7
• 1-3. 연구개발 범위 ... 19
• 2. 국내외 기술개발 현황 ... 20
• 3. 연구수행 내용 및 결과 ... 21
• 4. 목표달성도 및 관련분야 기여도 ... 33
• 4-1. 목표달성도 ... 33
• 4-2. 관련분야 기여도 ... 33
• 5. 연구결과의 활용계획 ... 34
• 6. 연구과정에서 수집한 해외과학기술정보 ... 37
• 7. 연구개발성과의 보안등급 ... 37
• 8. 국가과학기술종합정보시스템에 등록한 연구시설·장비 현황 ... 37
• 9. 연구개발과제 수행에 따른 연구실 등의 안전조치 이행실적 ... 37
• 10. 연구개발과제의 대표적 연구실적 ... 38
• 11. 기타사항 ... 38
• 12. 참고문헌 ... 39
• 별첨4. 실적 증빙자료 ... 40
• 끝페이지 ... 107