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Lean in Healthcare
Applying Lean Tools to Healthcare Design
• Bachelor of Architecture
Philadelphia University
• Bachelor of Science, Interior Design
Philadelphia University
EDUCATION
CERTIFICATIONS
• AIA
• Lean Six Sigma Black Belt
• Lean Green Belt
JONATHAN Bykowski
Principal & Practice Leader, Continuous Improvement
• Master of Engineering, Healthcare Systems Engineering
Lehigh University
• Bachelor of Arts, Architecture
Lehigh University
EDUCATION
CERTIFICATES
• Lean Bronze Knowledge, SME
LAURA Silvoy
Healthcare Systems Engineer, Associate
We are problem solvers.
Not problem identifiers.
provides a way to do more with
less, create new work and deliver
value as defined by the customer.
LEAN
It’s not just for Toyotas, or
Hospitals, or everyone but
Architects.
Case Study: Laser Spine Institute
THE
PROBLEM
28,000 SF
Solution
• We can design
flexible spaces to
support future
growth
• We can save
money by building
8 flexible rooms
instead of 12
single-purpose
rooms
WOULD IT WORK?
Design Validation
LOGN(1.5, 0.736)
Case Study: Northeast Academic
Children’s Clinic
THE
PROBLEM
Combine three
separate clinics
1N Surgery 7N Genetics 7C GI
Requests
• Maximize number of exam
rooms
• Maximize waiting space
• Dedicated space for each
clinic
Design Analysis SPACE UTILIZATION
Scheduled
Appointment
Time
Scheduled
Appointment
Time
(50% Volume Increase)
+/- 10 Minute
Appointment
Time
+/- 10 Minute
Appointment
Time
(50% Volume
Increase)
Average patients
seen each day
31 59 31 59
Rooms in use at 9:36
AM on Day 1
3 10 3 5
Maximum number
of rooms used at
same time on Day 1
8 15 10 15
Average waiting
room utilization
44% 79% 50% 83%
Average maximum
registration queue
length
1.3 2.6 1 2.8
Average maximum
check out queue
length
1.6 5.1 1.1 2.6
Name
Total
Entries
Average Time Per Entry
(Min)
Maximum
Contents
Waiting Room 3446.6 18.5 29.2
Patient Exam 1 470.5 33.3 1
Patient Exam 10 341.6 37.2 1
Patient Exam 13 335.4 40.8 1
Patient Exam 11 334 37.6 1
Patient Exam 2 331.9 33.0 1
Patient Exam 12 297.7 46.5 1
Patient Exam 9 230.5 38.8 1
Name
Total
Entries
Average Time Per Entry
(Min)
Maximum
Contents
Waiting Room 3440 6.6 29.7
Patient Exam 1 496.4 47.1 1
Patient Exam 2 464.6 46.5 1
Patient Exam 3 417.1 47.0 1
Patient Exam 4 363.9 48.9 1
Patient Exam 5 320 48.5 1
Patient Exam 6 270.2 48.3 1
Patient Exam 7 228.3 47.6 1
Scheduled
Appointment
Duration for 31
Patients
Scheduled
Appointment
Duration for 59
Patients
Rooms Dedicated to Specific Clinic
Rooms Shared Among All Clinics
Solution
• 14 exam rooms
• Reduce waiting space
• Add staff lounge
Case Study: Mid-Atlantic Academic
Children’s Emergency Department
THE
PROBLEM
Minimize ED waiting time
Improve patient experience
Acuity Count Percentage
1 - Resuscitation 607 1.47%
2 - Emergent 3,986 9.64%
3 - Two+ Resources 12,547 30.35%
4 - One Resource 18,979 45.91%
5 - No Resources 5,221 12.63%
Total 41,340 100%
Data taken from 1/1/14 thru 6/30/14
Process Step Value Add (min)
Security N/A
Registration/Triage 3 minutes
Assessment 7 minutes
Time Arrivals per Hour
12 AM -- 7 AM 2
7 AM -- 11 AM 10
11 AM -- 2 PM 15
2 PM -- 4 PM 10
4 PM -- 8 PM 20
8 PM -- 10 PM 10
10 PM -- 12 AM 5
Average Process Step Duration
Estimated Arrival Rate
Patient Acuity Distribution
Data Provided by Hospital Lean Department
Data Conjectured by Array
Process Step Distribution (min)
Security
Triangular (1.5, 2, 3)
minutes
Registration/Triage/Assess
Triangular (8, 10, 15)
minutes
Estimated Process Step
Distributions
Data Analysis
Simulation
7 triage
rooms
2 security
desk
positions
Data-Driven Decisions
• Quick registration at security
• Vitals only during triage
• Assessment in room
Out of 42,000
Solution
• 5 triage rooms
• 3 security desk
positions
• 56 private treatment
rooms
• <.08% of Patients
wait longer than 5
minutes for triage
We don’t have to know the answer.

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2015 Delaware Talk

  • 1. Lean in Healthcare Applying Lean Tools to Healthcare Design
  • 2. • Bachelor of Architecture Philadelphia University • Bachelor of Science, Interior Design Philadelphia University EDUCATION CERTIFICATIONS • AIA • Lean Six Sigma Black Belt • Lean Green Belt JONATHAN Bykowski Principal & Practice Leader, Continuous Improvement
  • 3. • Master of Engineering, Healthcare Systems Engineering Lehigh University • Bachelor of Arts, Architecture Lehigh University EDUCATION CERTIFICATES • Lean Bronze Knowledge, SME LAURA Silvoy Healthcare Systems Engineer, Associate
  • 4. We are problem solvers. Not problem identifiers.
  • 5. provides a way to do more with less, create new work and deliver value as defined by the customer. LEAN It’s not just for Toyotas, or Hospitals, or everyone but Architects.
  • 6. Case Study: Laser Spine Institute
  • 8. Solution • We can design flexible spaces to support future growth • We can save money by building 8 flexible rooms instead of 12 single-purpose rooms WOULD IT WORK?
  • 10. Case Study: Northeast Academic Children’s Clinic
  • 12. Requests • Maximize number of exam rooms • Maximize waiting space • Dedicated space for each clinic
  • 13. Design Analysis SPACE UTILIZATION Scheduled Appointment Time Scheduled Appointment Time (50% Volume Increase) +/- 10 Minute Appointment Time +/- 10 Minute Appointment Time (50% Volume Increase) Average patients seen each day 31 59 31 59 Rooms in use at 9:36 AM on Day 1 3 10 3 5 Maximum number of rooms used at same time on Day 1 8 15 10 15 Average waiting room utilization 44% 79% 50% 83% Average maximum registration queue length 1.3 2.6 1 2.8 Average maximum check out queue length 1.6 5.1 1.1 2.6 Name Total Entries Average Time Per Entry (Min) Maximum Contents Waiting Room 3446.6 18.5 29.2 Patient Exam 1 470.5 33.3 1 Patient Exam 10 341.6 37.2 1 Patient Exam 13 335.4 40.8 1 Patient Exam 11 334 37.6 1 Patient Exam 2 331.9 33.0 1 Patient Exam 12 297.7 46.5 1 Patient Exam 9 230.5 38.8 1 Name Total Entries Average Time Per Entry (Min) Maximum Contents Waiting Room 3440 6.6 29.7 Patient Exam 1 496.4 47.1 1 Patient Exam 2 464.6 46.5 1 Patient Exam 3 417.1 47.0 1 Patient Exam 4 363.9 48.9 1 Patient Exam 5 320 48.5 1 Patient Exam 6 270.2 48.3 1 Patient Exam 7 228.3 47.6 1 Scheduled Appointment Duration for 31 Patients Scheduled Appointment Duration for 59 Patients Rooms Dedicated to Specific Clinic Rooms Shared Among All Clinics
  • 14. Solution • 14 exam rooms • Reduce waiting space • Add staff lounge
  • 15. Case Study: Mid-Atlantic Academic Children’s Emergency Department
  • 16. THE PROBLEM Minimize ED waiting time Improve patient experience
  • 17. Acuity Count Percentage 1 - Resuscitation 607 1.47% 2 - Emergent 3,986 9.64% 3 - Two+ Resources 12,547 30.35% 4 - One Resource 18,979 45.91% 5 - No Resources 5,221 12.63% Total 41,340 100% Data taken from 1/1/14 thru 6/30/14 Process Step Value Add (min) Security N/A Registration/Triage 3 minutes Assessment 7 minutes Time Arrivals per Hour 12 AM -- 7 AM 2 7 AM -- 11 AM 10 11 AM -- 2 PM 15 2 PM -- 4 PM 10 4 PM -- 8 PM 20 8 PM -- 10 PM 10 10 PM -- 12 AM 5 Average Process Step Duration Estimated Arrival Rate Patient Acuity Distribution Data Provided by Hospital Lean Department Data Conjectured by Array Process Step Distribution (min) Security Triangular (1.5, 2, 3) minutes Registration/Triage/Assess Triangular (8, 10, 15) minutes Estimated Process Step Distributions Data Analysis
  • 19. Data-Driven Decisions • Quick registration at security • Vitals only during triage • Assessment in room Out of 42,000
  • 20. Solution • 5 triage rooms • 3 security desk positions • 56 private treatment rooms • <.08% of Patients wait longer than 5 minutes for triage
  • 21. We don’t have to know the answer.

Editor's Notes

  1. Jonathan I am a healthcare architect. I have degrees in architecture and interior designer. I have green and black belt certifications in Lean and Six Sigma. I clearly have a thirst for knowledge, and a serious control issue. I am the practice leader for continuous improvement at Array Architects and have been for about two years. But that’s not where this story begins.
  2. Jonathan
  3. Jonathan
  4. Jonathan Lean is a conceptual approach to thinking about systems, identifying problems, and improving them. It is a philosophy about people and process, not simply a manufacturing tool or applicable only to repetitive micro processes.
  5. Jonathan About a year and a half ago, our client approached us with a challenge. As a result of some extreme success in their business, they were poised for a large national expansion, but wanted to completely reconsider the way they were doing business. While they are a for-profit healthcare provider, which comes with all the bottom-line driven decisions one might expect, they were seeking to be much more patient-centric providing the utmost comfort for their patients and their families --- objectives not typical of for-profit institutions. So much so, they were seeking to be the first “Planetree designated” for profit health provider in the country.
  6. Jonathan The client’s current state of operations was not in alignment with their goals. Their existing facilities had grown organically over time – leading to inferior work environments and inefficiencies. We needed to address both increased efficiency and increased patient amenities. And we needed to do it fast: their plans for expansion included opening 3 new sites per year. They themselves are a very data-driven organization: they actually track the origin of all calls from across the country, map them, and then target their next expansion project for the regions with the greatest concentration of calls.
  7. Laura Designed a solution and wanted to validate it. Needed to validate because we were going against guidelines (8 flexible rooms instead of 12 recommended rooms)
  8. Laura Did observation and documented the current state process Nurses were already collecting data through the EMR and some analysis was done in the past They passed the data onto us and we were able to distill it down and analyze the major process steps Main goal was to minimize waiting time between OR and Recovery Designed and built a simulation model to represent the actual system. Tested and validated it. Changed it to match proposed plan Planned space works! Best option is to have 8 flexible rooms with 3 ORs and 2 surgeons Simulation helped validate the building design. One way to use it. Let’s explore it’s use during the design process.
  9. Jonathan A leading academic institution with several physician clinics spread across different sites on campus wanted to bring together those with opportunities for care coordination synergies
  10. Jonathan Three separate clinics operating in three separate parts of the hospital Each had different problems – not enough waiting space, not enough rooms, not enough space for residents Client thought they needed as much space as they could possibly get out of this renovation
  11. Laura Resulted in an initial design with 14 exam rooms and waiting space for 52 patients and 4 strollers or wheel chairs Not enough! Still wanted more waiting! Also thought that there should be more rooms because the rooms were to be dedicated to each clinic
  12. Laura Collected data using paper forms at each clinic. Some clinics were better than others at collecting the data. Also used appointment data from the EMR Model was developed so that rooms would be shared among all three clinics, but remember, our client wanted to assign exam rooms to each clinic. When exam rooms are assigned to a clinic, waiting time triples from 6 minutes to 18 minutes Waiting room volumes never exceeded 30 people (patients and caregivers combined) Variation in arrival times compared to appointment times help keep the registration queue shorter When volume is increased 50%, room utilization, as expected, is much higher
  13. Laura Still want to keep 14 exam rooms to stay flexible Able to reduce waiting space and provide a staff lounge Simulation proved that there was enough space for everyone to wait and there could be a space for staff to relax
  14. Jonathan With more than 100,000 visits per year, this pediatric ED was overwhelmed with ALOS of more than 5 hours. Believing their bottleneck came at the front end with a spit flow for triage and assessment the wanted to renovate the ED to increase the number of triage rooms and combine assessment.
  15. Jonathan They thought there were too many steps on the front end Wanted to combine steps to make things quicker. The idea that fewer patient steps would be faster seemed to make sense. Before designing a ____ SF renovation we wanted to be sure the basic planning driver held water
  16. Laura Received data from the hospital’s lean department Developed basic simulation model based on current process and data. Added some variability to the data to the model and confirmed with the nurses and physicians that it was reflecting their current operations.
  17. Laura After confirming the model’s accuracy, we changed the model so it would reflect the desired future state. Results are in: ED must staff 2 security staff and 6 triage rooms at peak volumes to keep waiting time under 5 minutes
  18. Laura Managers decided that they cannot commit to staffing 6 triage rooms at peak volumes. What’s a better way to do this? Do a quick registration at security and try moving assessment to the treatment room and only doing traditional triage upon arrival With these changes, registration takes a little longer, triage is a little quicker Now we need 3 security staff and 5 triage rooms at peak volumes –Staff managers are ok with this
  19. Jonathan Decreasing the number of triage spaces allowed for more space dedicated to treatment rooms in the ED
  20. Jonathan We don’t have to know the answer before the meeting begins (as we are so used to being expected in our role as our client’s problem solvers). We assemble a team of experts. The people who actually do the work, and then follow the steps to understand the problem, what’s happening currently, what we want to happen, and why that isn’t what we do. Its almost magical to watch. Consensus and discovery run rampant in the first work session and the team often rapidly focuses in on a path to improvement. I could come up with a proposed solution for every problem that comes across my desk, but they would be half as sustainable and viable as the solutions the cross functional teams develop.