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Prueba de IA en el flujo de pacientes y la gestión de camas en hospitales

Compruebe su comprensión de la previsión de admisiones y altas, los centros de mando de los hospitales y por qué las predicciones sólo liberan camas cuando el personal actúa.

Rutas de guía relacionadasIA en el flujo de pacientes hospitalarios y la gestión de camas
Pregunta 1 de 8

In patient flow, what does 'boarding' mean?

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  1. In patient flow, what does 'boarding' mean?
    • Checking patients in at the front desk
    • Moving patients between hospitals by ambulance
    • Admitted patients waiting in the emergency department because no inpatient bed is available
    • Discharging patients to nursing homes
  2. Which prediction task estimates when each current inpatient is likely to leave?
    • Length-of-stay and discharge prediction
    • Demand forecasting
    • Sepsis risk scoring
    • Ambulance diversion planning
  3. Why can't capacity forecasts treat all beds as interchangeable?
    • All beds are identical in modern hospitals
    • Beds are counted only once a year
    • Only emergency department beds matter
    • Specialized beds such as ICU or telemetry serve different patient needs
  4. Which company partnered with Johns Hopkins Hospital on its 2016 capacity command center?
    • Qventus
    • GE Healthcare
    • LeanTaaS
    • Epic
  5. According to the guide, what is a key misconception about patient-flow AI?
    • That it can forecast admissions
    • That it uses historical data
    • That the model itself frees beds without anyone acting on its predictions
    • That it is used in command centers
  6. Why should simple baselines such as seasonal averages always be reported in hospital demand forecasting?
    • Strong weekly and seasonal patterns make them hard to beat
    • They are required by law
    • They always outperform machine learning
    • They eliminate the need for uncertainty estimates
  7. Why do managers need prediction intervals, not just a single forecast number?
    • Intervals make dashboards look more detailed
    • Intervals remove the need for staff
    • Point forecasts cannot be calculated for hospitals
    • They need to judge the range of likely demand when deciding whether to open a surge unit
  8. What is a feedback loop in patient-flow prediction?
    • Patients giving feedback on their stay
    • Acting on predictions changes the outcomes the model was trained to predict
    • A model automatically retraining every hour
    • Staff sending comments to the vendor