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Related Concept Videos

Hospitals-II00:59

Hospitals-II

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Hospitals provide inpatient and outpatient services. Inpatient services provide care to patients that stay in the hospital for an extended period, ranging from days to months. Examples of inpatient services include intensive care units, hospital wards, or surgeries. Outpatient services provide care to patients who come to a hospital for a diagnostic or treatment but do not stay overnight —for example, diagnostic tests, surgical procedures, or health education.
Nurses that work in...
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Hospitals-I01:28

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Hospitals offer medical and surgical care to the sick and injured, along with accommodation while they recover. At the same time, they also provide outpatient, emergency, psychiatric, and rehabilitation services to meet various community needs. In addition to providing medical care, hospitals also act as hubs for medical research and training. Hospitals use clinical procedures and evidence-based practice standards to deliver patient care. To deliver safe and efficient care, a nurse must stay up...
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Related Experiment Video

Updated: Aug 15, 2025

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Design and Performance of a COVID-19 Hospital Recovery Model.

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  • 1Health Systems Engineering, Massachusetts General Hospital, Boston, MA.

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Summary
This summary is machine-generated.

A predictive model accurately forecasted hospital occupancy during COVID-19 recovery, ensuring capacity for emergency and scheduled care. This tool aids hospitals in planning for patient surges and resource allocation.

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Area of Science:

  • Healthcare Management
  • Epidemiology
  • Predictive Modeling

Background:

  • Hospitals face challenges balancing COVID-19 and non-COVID patient needs during recovery.
  • Effective planning is crucial to maintain emergency department (ED) access and scheduled procedures.
  • A predictive model was developed to forecast inpatient occupancy for pandemic recovery.

Purpose of the Study:

  • To evaluate the accuracy of a predictive model for inpatient occupancy.
  • To assess the model's utility in aiding hospital recovery planning post-COVID-19 surge.
  • To determine the model's performance in predicting occupancy for COVID and non-COVID patient groups.

Main Methods:

  • A predictive model was implemented at a New England quaternary care hospital.
  • Data included COVID, non-COVID nonscheduled (NCNS), and non-COVID scheduled operating room (OR) hospitalizations from March 10 to July 12, 2020.
  • Daily occupancy predictions were compared to actuals using mean absolute percentage error (MAPE) and mean absolute error (MAE) during the recovery period (May 25 to July 12).

Main Results:

  • The model demonstrated high accuracy in predicting total hospital occupancy (MAPE 2.8%, MAE 22.3).
  • Accuracy was also strong for general care (MAPE 2.6%, MAE 17.8) and intensive care unit (ICU) occupancy (MAPE 9.7%, MAE 11.0).
  • The recovery period included 444 COVID, 5637 NCNS, and 1218 non-COVID OR hospitalizations.

Conclusions:

  • The predictive model accurately forecasted hospital occupancy during the COVID-19 recovery period.
  • Such models can support hospital recovery planning by ensuring adequate capacity.
  • The findings suggest models can help maintain ED access while facilitating the return of scheduled procedures.