Prediction of Patient Placement (POPP) is an advanced, real-time forecasting tool that can predict likelihood of admission from the ED within 10 to 20 minutes following triage.

Project Overview

POPP will utilize the Accelerator Grant to transform a static predictive model into a real-time capacity prediction dashboard at Boston Children’s Hospital. The POPP dashboard will bring advanced predictive research into actual operational settings and generate early data on this predictive approach to capacity management.

POPP gives operations staff visibility into incoming admissions from the Emergency Department by predicting likely admissions before the clinical staff have completed their evaluation.

  • An accurate model, predicting need to admit patients to ED, supports admissions coordinators
  • Only seen by operations and administrative staff, predictions not shown to clinicians

Healthcare Context

Overcrowding in the Emergency Department is a familiar sight for ED clinicians. In fact, 50% of all EDs operate at or above their space capacity – an alarming statistic for clinicians and patients alike. The impact of this operational inefficiency has serious adverse effects. Operating at or above space capacity increases costs and limits the capacity of the hospital for disaster response. Further, operating at or above space capacity leads to higher morbidity and mortality, and compromises quality of patient care and satisfaction.

Patients admitted to the Emergency Department are spending more and more time in the hospital. Emergency Departments are forced to divert incoming patients to other Emergency Departments. Proactively, and intelligently, managing the flow of patients into the Emergency Department provides hospitals with shorter wait times and improved outcomes.

Interested in learning more about POPP?

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Dr. Yuval Barak-Corren

Predictive Medicine Group

Dr. Andrew Fine 

Division of Emergency Medicine

Dr. Ben Reis 

Predictive Medicine Group

Nitin Gujral

Innovation and Digital Health Accelerator