Maximizing efficiency through Lean led design
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The document discusses the consolidation of BJC Healthcare's diagnostic labs to eliminate inefficiencies through a lean design approach. It outlines the current state of scattered labs, the benefits of a centralized layout, and the steps taken for operational planning, including value stream mapping and simulations to optimize staffing and processes. Proposed changes include reducing walking distances, improving workflow, and utilizing data-driven decisions to enhance lab performance.
Maximizing efficiency through Lean led design
- 1. Consolidating BJC’s Diagnostic Labs Eliminating Inefficiency through Lean-Led Design
- 2. 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.
- 3. Agenda 1. The Problem with Labs 2. Layout Optimization 3. Operational Planning 4. Question and Answer
- 4. BJH Overview • Academic hospital • Campus includes BJH and SLCH • Trauma Level 1 Emergency Room • Staffed Inpatient Beds: 1,167 • Annual Admissions: 54,738
- 5. 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.
- 6. 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
- 7. 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
- 8. 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)
- 9. 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?
- 10. 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.
- 12. A Superior Design Queuing Time at Sort Queueing Time at Clerical Queueing Time at Manual Minutes 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.
- 13. Staffing Plan Next was to create a data-driven estimate for how many staff will be needed to launch on day 1.
- 14. 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 Minutes(AverageWaiting) 3 staff 4 staff 5 staff 6 staff 7 staff
- 15. Anticipated Lead Time 250 arrivals per hour 420 arrivals per hour 580 arrivals per hour Minutes 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.
- 16. LeanHDX Live
- 17. Benefits of Simulation with LeanHDX Data-driven decision making. Quick to build and test scenarios. Highly visual for stakeholder engagement. Complements existing Lean tools.