Practical advice on how to optimize your MRI practice (or radiology practice in general) by applying the principles of Kaizen events (or Lean and Six Sigma). Lessons learned from executing more than 60 rapid workflow improvement events in Radiology practices worldwide .

1. Optimizing your MRI practice
with Kaizen events
André van Est
Founding Partner
Care IQ Group
September 2015

2. Outline
2
• Introduction
• Data treasure
• Benchmark lessons
• Kaizen approach
• Examples
• Conclusion

3. Care IQ Group 150 years of experience
in healthcare planning & engineering
3

4. Career theme:
Healthcare
innovation
4
• 1983 – MRI development
(Philips Gyroscan)
• 1988 - WS development
(Gyroview)
• 1992 – Healthcare IT Apps
(EasyVision)
• 1999 - MR Applications
(Intera, Achieva, Ingenia)
• 2004 - Professional Services
o 2004 - NetForum Community
o 2006 - Utilization Services
o 2008 - Consulting Services
• 2013 - Founding Partner Care IQ Courtesy)to)Philips)Healthcare)
www.philips.com/ne7orum)))))
NetForum)Community)

5. OHSU
Portland OR
NIC
Las Vegas, NE
The Netherlands (Rijnstate Arnhem,
2x Catharina Eindhoven, Antonius
Nieuwegein, Viecuri Venlo, Elkerliek
Helmond, 9x UMC Utrecht)
Japan
(Yaesu
Clinics)
Austria
(Neusiedl,
Klagenfurt,
Kapfenberg)
Denmark
(2x Herlev Hosp.
Kopenhagen,
Herning Hosp.)
Turkey
(Yeditepe
University )
Saudi Arabia
(NGH Riyadh, Bakhsh
Hospital Jeddah)
UA Emirates
(Al Zahra Hosp
Sharjah)
Southern Open MRI
FL
DMI
Palm Springs CA
2x St Barnabas
Livingston NJ
China
(Renji
Hospital)
Sweden
(2x Lund Uni Hospital,
2x Unilabs Göteborg)
France (La Porte
Verte Versailles,
La Pitié Paris) UK
(North Staffs
Univ Hosp.
Germany
(2x BrüderKH Trier,
2x Asklepios Barmbek
Hamburg, MRT Schwerin)
Norway (AHUS Oslo,
Molde Hospital,
Ålesund Hospital,
2x Unilabs Oslo)
60+ Kaizen Events,
300+ Quick Scans
Spain
(2x La Fé
Valencia)
5
Switzerland
(2x Unilabs
Geneva)

6. 6
• Introduction
• Data treasure
• Benchmark lessons
• Kaizen approach
• Examples
• Conclusion

7. “You can have data without information,
but…
you cannot have information without data.”
Daniel Keys Moran
7

8. From “what goes wrong”
to “what goes on!” and
turning this into opportunities

9. Tracing the waste!
9
Examina1on)Times)
• )many)or)long)scans)
• )contrast)prep)in)room))
• )repeat)or)add:on)scans)
• )non:coopera;ve)pat’s)
Changeover)Times)
• )pa;ent)late/no:shows)
• )inefficient)changeover)
• )inefficient)pat.)transport))
• )unplanned)slots)
Most)1me)waste)occurs)when)the)scanner)is)not)running!)

10. Recognizing trends and patterns
10Keep)measuring)to)know)that)improvement)is)durable!)

11. DATA PROVIDE A GOOD
START FOR A MORE
OBJECTIVE DISCUSSION
Lesson learned
11

12. 12
• Introduction
• Data treasure
• Benchmark lessons
• Kaizen approach
• Examples
• Conclusion

13. Significant)performance)varia;on)despite)similar)technology)
Top)performers)more)effec;ve)in)managing)org.)complexity)
Global benchmark Philips 1.5T
13
)Philips)1.5T)Systems) )) )) )) )) )) )) )) )) ))
)2013) BEL) CAN) CHI) DEN) FRA) GER) ITA) JAP) NL) SWI) SPA) SWE) UK) USA)
)Procedure)1me) 26) 40) 25) 43) 26) 32) 36) 39) 34) 47) 39) 46) 35) 58)
)Scan)1me) 17) 23) 13) 21) 16) 19) 21) 18) 18) 24) 22) 22) 20) 25)
)Scans)per)exam) 7.8) 8.7) 7.6) 8.1) 8.2) 8.5) 9.1) 8.9) 8.0) 8.6) 9.0) 8.5) 9.9)
Source:(Philips(U0liza0on(Services))
1.5T)Germany)by)
prac1ce)type)
Procedure)1me)
Mean) Best)
Private) 31) 16)
Hospital)<500)beds) 43) 21)
Hospital)>500)beds) 52) 20)
Academic) 64) 20)

14. PRACTICE OPTIMIZATION REQUIRES A
SOUND MIX OF PEOPLE, PROCESS AND
TECHNOLOGY, PLUS CAREFULLY
FACILITATED CHANGE
Lesson learned
14
change

15. 15
• Introduction
• Data treasure
• Benchmark lessons
• Kaizen approach
• Examples
• Conclusion

16. Data is not information,
Information is not knowledge,
Knowledge is not understanding,
Understanding is not wisdom.
Clifford Stoll
16

17. How to get started?
Question the status quo!
• Measure – Voice of the data
• Interview – Voice of the people
• Observe – Voice of the process
© Care IQ Group BV 17

18. How to get results that stick?
• Involve the team to inspire commitment
• Do it swiftly and focused ! Kaizen
18
: Iden;fy)issues))
: Analyze)root)causes)
: Iden;fy)solu;ons)
: Priori;ze)solu;ons)
: Implement)solu;ons)

19. 5 day Kaizen event
19
• Team work
• Fact based
• Solution driven
• DMAIC
)Deliver)
)Report)
)Interpret)
)Exam)
)Perform)
)Exam)
)Prepare)
)Exam)
)Receive)
)Pa1ent)
)Confirm)
)Exam)
)Schedule)
)Exam)
Receive)
Order)
Quality))
of)care)
Cost)
effec;veness)
Pa;ent)&)Staff)
experience)
KAIZEN)EVENT)

20. THINK BIG, ACT SMALL
KAIZEN & TEAMWORK
Lesson learned
20

21. 21
• Introduction
• Data treasure
• Benchmark lessons
• Kaizen approach
• Examples
• Conclusion

22. Keep the schedule simple!
22
Before:)li[le)flexibility)due)to)
many)‘reserva;ons’)
A^er:)more)flexibility)and)capacity,))
more)autonomy)for)scheduling)staff)

23. Clear space, clear mind!
Issues
• Clutter in the scanner room, e.g. coil
and accessory storage, sterile goods,
contrast materials, blankets, etc.
• Excessive amounts
• Unnecessary materials
• Dirty laundry and waste
Solution
23
Before)
A^er)

24. Timely contrast prep outside room
saves 3-5 min per exam!
24
Common issues
• Patient prep starts too late
• Patient being anxious
• Contrast prep inside room
Opportunities to add value
• Tech-aide to help maximize
technologist time
• Personal contact to educate
patient about exam or handle
anxiety
• Scan execution reports shows
impact of in-room prep
5 min inter-scan delay

25. Tech aide - avoid being
penny wise pound foolish
Issue:
• High volume (30 ex/day)
• Single operator, stress!
• Invest in staff?
Solution:
• Introduce tech aide to
assist with patient prep
(shared with CT suite)
Results:
• Productivity +10%
• Quick ROI
• Staff satisfaction "
25

26. Preparation – two birds one stone
or tackling no-shows effectively
Issue:
• High no-show rate (9%) due to
patient ‘shopping’ behavior
Solution:
• Introduce ‘reminder’ calls & script
• Overcoming ‘no time’ syndrome
Results:
• No-show rate from 9% to 3%
• Effective use of shift overlap
26
Pa;ent)present)
Pa;ent)no:show)

27. Scanning - start optimizing most used
not the most complex exams!
27

28. Utilize the technological advances
28
Before) A^er)
Issue
• Knee ExamCard not updated after major system upgrade
• Untapped technological advances
Solution
• New method technology applied (asymmetric-TSE)
• 30% time gain, average scan time reduced by 5 min
50%)
peak)
25%)
peak)

29. Leverage the combined team skills
29
Before)
Issue
• 2D strategy often leads to add-on scans (i.e. extra spine levels)
• Lack of ownership and team play
Solution
• 3D strategy automatically covers larger field of view
• More robust and predictable ExamCard execution
20%)
peak)
80%)
peak)
A^er)

30. 30
• Introduction
• Data treasure
• Benchmark lessons
• Kaizen approach
• Examples
• Conclusion

31. Conclusion
Data)
Informa;on)
Knowledge)
Understanding)
31
Wisdom)
Ac;on)
experience)
applica;on)
Data is not information,
Information is not knowledge,
Knowledge is not understanding,
Understanding is not wisdom.)
Clifford)Stoll)

32. Thank)you)for)your)a[en;on)
)
more)info:)
andre.van.est@care:iq.com))
www.care:iq.com))