간호 퀴즈의 AI

퀴즈를 풀면 정답과 설명이 나타납니다.

1. In the 2026 NARRATE study, which outcomes were compared between conventional and AI-supported supervisor reports?
   • WHO-aligned incident-report completeness and adapted PDQI narrative-quality scores
   • Time to complete nursing documentation and bedside visit counts
   • Automatic transcription accuracy against retained audio recordings
   • Nurse adoption rates across all hospitals
2. In a 2025 study of sepsis patients, what outcome was the Epic Deterioration Index evaluated against?
   • Medication cost per patient
   • First-episode rapid-response-team activation
   • Patient satisfaction with nursing staff
   • Length of a physician note
3. 간호 AI 맥락에서 '알람 피로'란 무엇입니까?
   • 걷다 지쳐가는 간호사들
   • 너무 작아서 듣기 힘든 알람
   • 잘못된 경고를 포함하여 너무 많은 경고로 인한 둔감화
   • 일정 관리 소프트웨어 버그
4. 패혈증 및 악화 모델은 주로 어떤 종류의 데이터에 의존합니까?
   • 병원 로비 사진
   • 환자 소셜 미디어 게시물
   • 일기 예보
   • EHR의 시계열 활력 징후 및 실험실 값
5. Why is local validation important before deploying a nursing deterioration model?
   • Patient populations, data quality, and workflows can differ by hospital
   • All hospitals use identical patient data
   • A high score guarantees clinical deterioration
   • Validation is unnecessary after training
6. 간호 임상 판단과 관련하여 AI의 의도된 역할은 무엇입니까?
   • 간호사의 결정을 무시하려면
   • 임상 판단을 대체하는 것이 아니라 강화하고 지원하기 위해
   • 간호사의 필요성을 없애기 위해
   • 모든 결정을 독립적으로 내리기 위해
7. How can a hospital reduce the risk that an early-warning score creates excessive low-value alerts?
   • Send every possible alert to every nurse
   • Remove human review from the workflow
   • Calibrate alert thresholds against local data and review alert burden with clinical staff
   • Assume more alerts always improve safety
8. What should teams monitor after deploying a nursing deterioration model?
   • Only the model’s training loss
   • Only the number of installed workstations
   • Whether every nurse clicks every alert
   • Clinical performance, false-alert workload, and subgroup behavior in the local workflow