Maximizing efficiency through Lean led design

Post on 13-Apr-2017

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transcript

Consolidating BJC’s Diagnostic Labs Eliminating Inefficiency

through Lean-Led Design

Today’s Speakers

Rodney Mullins Performance Improvement Manager BJC Healthcare

Brittany Hagedorn U.S. Healthcare Lead SIMUL8

Special Thanks to Mike Lee for his help in making this project a success.

Agenda

1. The Problem with Labs

2. Layout Optimization

3. Operational Planning

4. Question and Answer

BJH Overview

• Academic hospital

• Campus includes BJH and SLCH

• Trauma Level 1 Emergency Room

• Staffed Inpatient Beds: 1,167

• Annual Admissions: 54,738

Labs: Critical to Care

Diagnostic tests are used in 70% of all medical

decision making.*

70%

*Forsman RW. Why is the laboratory an afterthought for managed care organizations? Clin Chem. 1996;42:813–816.

Current State of BJH’s Labs

6+ separate labs, each with various

capabilities, scattered across the campus.

This resulted in inefficiencies and waste:

• Complicated logistics

• Delays in processing

• Excess staffing at slow periods during the day

Benefits of Consolidation

• Centralized receiving to simplify logistics

• Elimination of excess handling (if split

specimens between multiple lab locations)

• Reduce turnaround time for results

• Improve service to patients

• Increased capacity to support additional testing

Lean Design Approach

1. Value Stream Mapping (VSM) for

each existing lab to determine

workload and identify inefficiencies.

2. 5-day Rapid Improvement Event

(RIE) to develop an initial layout.

3. Simulation to estimate staffing.

4. Challenged to further reduce the

number of touches.

5. 2-day “mini” RIE to identify additional

improvements.

6. Simulation to compare both layouts

and anticipate impact.

Plan (Design Requirements)

Design (Rapid Improvement

Event)

Check (Simulation)

Act (Implement &

Review)

Design Questions

• What is the best layout for work stations?

• How will the new lab design handle the ebb and flow of

volumes over the course of the day?

• To what extent will staff roles and responsibilities in the

lab need to change?

• Will there be enough space for the full complement of

lab staff that will need to work there?

• How many staff will need to be on each shift throughout

the day?

Proposed Changes

• Consolidated work spaces and proximity to each

other in order to reduce the number of hand-offs and

the time spent walking between stations.

• Relocated the runner home base to provide better

visibility and reduce distance traveled.

• Created multi-functional overflow work stations to

handle peak volumes.

• Created single-piece flow that is based on a pull

model, to guarantee a FIFO inventory system.

Potential Layouts

1

2

A Superior Design

Queuing Time at Sort Queueing Time at Clerical Queueing Time at Manual

Min

ute

s

Initial Layout Improved Layout

With an improved layout, the team was able to further reduce the amount of time that samples would spend waiting in various steps of the process.

Staffing Plan

Next was to create a data-driven estimate for how many staff will be

needed to launch on day 1.

Staffing Decisions

At each level of hourly demand (250 arrivals in the above), the simulation was used to compare delays and overall lab performance for a range of staffing levels.

Sort Register

Min

ute

s (A

vera

ge W

aiti

ng)

3 staff 4 staff 5 staff 6 staff 7 staff

Anticipated Lead Time

250 arrivals per hour 420 arrivals per hour 580 arrivals per hour

Min

ute

s

Average Queuing Time

As a new facility opens, it is important to set expectations about what level of delay is realistic to anticipate, varying throughout the day due to demand. The above

values are for the total lead time to automation, assuming 5 water-spiders.

LeanHDX Live

Benefits of Simulation with LeanHDX

Data-driven decision making.

Quick to build and test scenarios.

Highly visual for stakeholder

engagement.

Complements existing Lean tools.

Questions?

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