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Inpatient Throughput Improvements

Case Study

The Challenge

A large 27 unit, 918 bed Community Hospital was challenged with admission holds in the Emergency Department and discharge delays in the inpatient units.

With an over 30% admission rate and a high acuity ED, the Emergency Department was at capacity and unable to handle day to day volume. Furthermore, two Critical Care Units and a high-volume Medical-Surgical floor were also at capacity, contributing to the delays in the ED. Discussions with hospital staff and on-site observations revealed concerns with the hospitalist practice workflow for admissions and discharges, along with concerns with the overall hospital responsiveness to the admission holds in the department. The discussions uncovered operational issues within the following processes:

  • Patient flow from the ED to Inpatient Unit
  • Transfers within the Hospital (Unit to Unit transfers)
  • Discharges from the Unit

The Solution

Using Discrete Event Simulation and data analysis, US Acute Care Solutions worked with the highest volume Med-Surg, Medical and Cardiac ICU floors to help determine the causes of the delays in the patient processes. During the initial assessment, patient processing times were inefficient and contributing to delays in the Emergency Department.

There were several factors contributing to the long throughput times of the patients. Some of the key findings are outlined here:

  • Report process was not streamlined to allow rapid patient movement to beds
  • Supply of open beds did not meet peak demand period
  • Off line beds (beds unavailable due to isolation, gender or maintenance) averaged around 10 on the Med-Surg Unit, pressuring an already high capacity demand
  • Lengthy admission and discharge cycles
  • Diagnostic Services issues delayed ability to discharge patients
  • Slow and unpredictable discharges
  • Delays in notification of housekeeping to clean beds
  • Discharges were being extended to the end of the shift in order to avoid additional admissions

Figure 2: Bed Demand Graph - Initial State

Figure 2: Bed Demand Graph - Initial State

The Results


Through the use of Discrete Event Simulation; scenarios were run to demonstrate the changes needed to improve both Inpatient and ED throughput. The combination of these strategies helped to alleviate the stress the floors and ED were facing and also improved bed demand timing throughout the hospital. (see Table 2: Simulation Outcomes and Figure 3: Bed Demand Graph– Improved State)

Strategies modeled included:

  • Moving the peak discharge order hours earlier in the day– allowing for patients to be discharged earlier
  • Streamlining the report process between the ED and Inpatient units and also between floors
  • Creating processes to improve the coordination of discharges early in the admission stay
  • Push to Bed strategy to allow for improved floor visibility of ED capacity challenges

Table 2: Patient Processing Times from Data Analysis and Simulation - Improved State

Table 2: Patient Processing Times from Data Analysis and Simulation - Improved State