Case Study: Mid-Atlantic Academic Medical Center

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CLIENT:

CASE STUDY

Mid-Atlantic Academic Medical Center

Constructing a simulation model and mapping unique departmental processes are ideal for pinpointing the best staffing scenarios. In hospitals with large, piecemeal campuses, inpatient transportation can be challenging. Coordinating staff size, scheduling, and departmental location are critical to developing the best solution. We employ a data-driven study process to help each client optimize their resources to reach a solution that works best for them.

CHALLENGE

EXECUTIVE SUMMARY

The client’s PES was unable to respond

The hospital staff lost confidence in the Patient Escort Services department

to every transportation request in a

because of delays. As a result, hospital units began creating their own

timely manner, resulting in inpatient

transportation teams, complicating staffing scenarios for the Patient Escort

hospital units losing confidence in

Services (PES) team. After investing in a manager for PES, furnishing the

the system and developing their own

department with a dedicated suite, and employing pilot programs to test

method of transport. Patient care

solutions for the problem, the hospital turned to Array Advisors.

staff also began performing transport

Array undertook a comprehensive study to explore the current transportation

themselves in certain instances.

operations, using data collection, current state mapping and simulation modeling to identify an optimal transportation staff size and structure. Current

SOLUTION Simulation Modeling

state gemba mapping allowed the Array team to create a snapshot of how the transportation process occurs prior to any changes. Data collection is integral to the accuracy of a simulation model, and in this instance, the team undertook a manual data collection process and used Electronic Medical Record (EMR)

A comprehensive study that employed

data. Using the data, Array Advisors created a simulation model with scaled floor

current state gemba mapping and

plans, and then generated a simulated transportation request from different

simulation modeling allowed Array to

groups at varying rates.

identify four scenarios that maximize staff utilization, minimize transport wait time, and greatly reduce the number of unit staff performing transport.

The study revealed that by putting all transportation into one resource pool, the department would be more efficient and better equipped to operate at optimal staff utilization. Based on the results of the simulation model, Array arrived upon four recommended scenarios that would ensure a staff size and schedule that enables transport in 10 minutes or less in 86% or more instances, with a staff utilization up to 97%, and allowing for unit staff transports in only 2.2% or fewer instances.

PROJECT HIGHLIGHTS

4 Staffing Options

At Least

Up to

86%

97%

of Transports Completed within 10 Minutes

Staff Utilization


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