Simulation is not just a technology or technique, it is a strategy to accelerate the "time to market" for healthcare delivery transformation.

1. Medical Simulation 3.0: Improving Patient Safety
and Healthcare Delivery Transformation
Yue Dong, M.D.

2. Disclosures
• The views and opinions are expressed in
following presentations are presenters’ own,
not representative of Mayo Clinic, Society of
Simulation of Healthcare(SSH), Healthcare
Systems Modeling and Simulation Affinity
Group (HSMSAG)
• Faculty and organizing committee do not
endorse or recommend any specific products or
services mentioned on this presentation.
• Faculty and organizing committee do not have
any personal financial interest related to the
presentation.

3. ©2011 MFMER | 3123886-3

4. Mayo Clinic Core Value：
Quality (Outcome + Safety + Service)
Value =
Cost per over time
Smoldt RK, Cortese DA. Pay-for-performance or pay for value? Mayo Clinic Proceedings 2007;82:210-3
“The needs of the patient come first.”

5. Surgical never events and contribution human factors
Mayo Clinic
roughly 1 in every
22,000 procedures
National Practitioner
Data Bank
1 in every 12,000
procedure
Thiels CA, et al. Surgery 2015 May 29 http://www.ncbi.nlm.nih.gov/pubmed/26032826

6. Minnesota Adverse Events 2015
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7. Rates of All Harms, Preventable Harms, and High-Severity Harms per 1000 Patient-Days,
Identified by Internal and External Reviewers, According to Year
Landrigan CP et al. N Engl J Med 2010;363:2124-2134
Rates of All Harms, Preventable Harms, and High-Severity Harms per
1000 Patient-Days, Identified by Internal and External Reviewers,
According to Year
Landrigan CP et al. N Engl J Med 2010;363:2124-2134

8. Healthcare systems safety
• 400,000 Americans
die each year as a
result of medical
errors. (3rd after heart
disease and cancer)
• $765 billon (35%) US
healthcare cost is
wasted each year
• US annual healthcare
cost more than $ 3
trillion (16% GDP)
James JT. Journal of Patient Safety 2013;9:122-128; CDC.gov;
http://resources.iom.edu/widgets/vsrt/healthcare-waste.html

10. ICU as Systems of Systems
Adopted from: Network medicine--from obesity to the "disease". Barabási AL., N Engl J Med. 2007 Jul 26;357(4):404-7.
SHOCK
DIC AKI
ALI
Physician RT
Pharmacist
Nurse
Time 
Baseline
PatientOutcome,
ProviderSatisfactions

11. Learning Healthcare Systems
• Significant changes in the health
care delivery system, changes
largely concerned with organization
• quality improvement
• operational efficiency
• error reduction and patient safety
IOM. The Learning Healthcare System: Workshop Summary. Washington, DC: The National Academies Press; 2007.

12. “Blue Highways” on the NIH Roadmap
Practice-based
research
Phase 3 and 4 clinical
trials
Observational studies
Survey research
Basic science
research
Preclinical studies
Animal research
Human clinical
research
Controlled
observational studies
Phase 3 clinical trials
T1
Case series
Phase 1 and 2
clinical trials
Clinical practice
Delivery of recommended
care to right pt at right time
Identification of new clinical
questions and gaps in care
T2
Translation
to humans
T2
Guideline
development
Meta-analyses
Systematic
reviews
Translation
to patients
T3
Dissemination
research
Implementation
research
Translation
to practice
Westfall JM et al: JAMA 297:403, 2007
Bench Bedside Practice

13. The Science of Healthcare Delivery
• Understanding disease biology
• Finding effective therapies
•Therapies delivered effectively

14. 2011, Health IT and Patient Safety: Building Safer Systems for Better
Care, Committee on Patient Safety and Health Information Technology; Institute of
Medicine

15. What is simulation?
• Simulation is the imitation or
representation of one act or system by
another.
• Healthcare simulations have four main
purposes – education, assessment,
research, and health systems
integration to facilitate patient safety…

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Society for Simulation in Healthcare

17. SSH Membership Continuing Growth
17
180
539
1205
1520
1702
1850
2438
2925 2918
0
500
1000
1500
2000
2500
3000
3500
2005 2006 2007 2008 2009 2010 2011 2012 2013

18. History of medical simulation
1026
宋代针灸铜人
1969
SimOne
Dr. Abrahamson

19. Simulation 1.0
Education Assessment
Systems
Integration
Research
Simulation

20. Mayo Clinic Multidisciplinary Simulation Center

21. Ultrasound guided central line insertion

22. Precourse- literature review
Precourse exam (Online)
Cadaver lab (Procedural Skills Lab)
(1 hour)
Ultrasound hands-on station
(1 hour)
Gown/Gloving/Universal Precautions
(1 hour)
Certification Station
(following with feed back)
Briefing
Experience
Debriefing
Learninggoaldriven
Central Line Workshop
Courtesy of William Dunn, MD

23. Clinical competence
Metricassessment
Time
Traditional training
Safety standard
Simulation-based training
Simulation-based objective assessment Discern Clinical Proficiency in Central Line Placement, Dong, et. al,
CHEST 2010

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25. ©2011 MFMER | slide-25
WHO Global Priorities for Patient Safety Research
Bates DW, et al. Global priorities for patient safety research. BMJ 2009;338:b1775

26. ED Trauma Team Training
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27. Learning Objective
Faculty Development
Curriculum
Facility and
Technology
Assessment
Debriefing
Simulation based education
Learners

28. Key questions for SBT?
• Does the simulation-based education work
• How does simulation compare with other
instructional approaches?
• Why are some simulation interventions better
than others (and how can we improve them
all)?
• Is simulation-based education worth its costs?
David Cook, The literature on healthcare simulation education: What does It show ?
http://webmm.ahrq.gov/perspective.aspx?perspectiveID=138#ref8

30. ROI of Simulation based training
• Approximately 9.95 CRBSIs were
prevented among MICU patients with
CVCs／year
• Cost of CRBSI were $82,000 in 2008
dollars and 14 additional hospital days
(including 12 MICU days).
• Cost of the simulation-based education
$112,000.
• 7 to 1 rate of ROI

31. Shannon DW. How a Captive Insurer Uses Data and Incentives to Advance Patient Safety. PSQH. Nov/ Dec 2009.

32. Simulation 1.0
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Education Assessment
Systems
Integration
Research
Simulation

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Five steps to develop checklists for evaluating clinical performance: An integrative approach。 Schmutz J, Eppich WJ,
Hoffmann F, Heimberg E, Manser T. Academic Medicine. 2014 Jan;89(7):996-1005

34. Central Line Procedure Checklist
Simulation-based objective assessment Discern Clinical Proficiency in Central Line Placement, Dong, et. al, CHEST 2010

35. ©2011 MFMER | slide-35
Simulation-based objective assessment Discern Clinical Proficiency in Central Line Placement, Dong, et. al, CHEST 2010

36. Short-term and Long-term Impact of the Central Line Workshop on Resident Clinical Performance During Simulated
Central Line Placement。 Laack, Dong, et al. Simulation in Healthcare 9 (4), 228-233

38. “Medicine used to be simple, ineffective and relatively
safe. Now it is complex, effective and potentially
dangerous” Sir Cyril Chantler

39. Information overload
2012, IOM, Discussion Paper1: The Clinical Trials Enterprise in the United States: A Call for Disruptive Innovation

40. The Complexities of Physician Supply and Demand: Projections Through 2025. 2008 AAMC http://www.aamc.org/workforce
“ Simply educating and
training more physicians
will not be enough to
address these
shortages. Complex
changes such as
improving efficiency,
reconfiguring the way
some services are
delivered and making
better use of our
physicians will also be
needed.”

41. Simulation 2.0
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Education Assessment
Systems
Integration
Research
Simulation

42. Human Factor Research
• Using simulation as a tool to study human
performance variation under different “stress
conditions” (fatigue, cognition, workload,
etc.)
• conduct usability testing of devices
instrument and processes

43. The effect of drug concentration expression on
epinephrine dosing errors: a randomized trial
Wheeler DW, Carter JJ, Murray LJ, Degnan BA, Dunling CP, Salvador R, et al.. Ann Intern Med 2008;148:11-4.
(1 mg in 1 mL) (1 mL of a 1:1000 solution)

44. Arriaga AF, Bader AM, Wong JM, et al. Simulation-based trial of surgical-crisis checklists. N Engl J Med 2013;368:246-253

45. Ahmed, et al. Critical Care Medicine, 39(7) 1626-1634
The effect of two different electronic health record user interfaces on
intensive care provider task load, errors of cognition, and performance

46. Simulation 3.0
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Education Assessment
Systems
Integration
Research
Simulation

47. Dr. Lucian Leape Dr. Donald M. Berwick
Transforming healthcare: a safety imperative
L Leape, D Berwick, C Clancy, et al. Qual Saf Health Care 2009; 18:424-428

49. A technical systems grow in
complexity and
connectedness, inevitably
will lead to accidents with
catastrophic potential
• the degree of system
complexity
• tight coupling of processes,
• and the inability of a single
individual or small group of
individuals to manage all
the potential interactions
• Stochastic escalation
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Perrow, C. Living with high-risk technologies. Princeton University Press:
John Wiley and Sons Ltd; New Jersey: 1999.

50. What is system integration？

51. Caffezo, et al rom discovery to design, Human factor in healthcare, 2012

53. Modeling Complexity (Rouse, 2007)
“ Starting with this model of the enterprise, the overarching strategy should focus on increasing complexity where
it can be managed best and decreasing complexity for end users.”

54. Adjust structure and process to eliminate or minimize
risks of health care-associated injury, before they have
an adverse event-impact on the outcomes of care
Donabedian. Evaluating of Medical Care. The Milbank Memorial Fund Quarterly, Vol. 44, No. 3, Pt. 2, 1966 (pp. 166–203)

55. Systems Engineering Initiative for Patient Safety (SEIPS) Work system design for patient safety: the SEIPS model.Carayon P, et al . Qual Saf Health Care. 2006 Dec;15 Suppl
1:i50-8. Review.

56. Simulation, modeling and Analysis, Law and Kelton, 2000

57. Robert Pool, Science, Vol. 256, No. 5053 (Apr. 3, 1992)
“ Computation has become a ‘third branch’ of
science, alongside theory and experiment”

59. McDonnell , G. (July, 2007).Workshop on Multiscale Modeling using AnyLogic 6 with Health Examples at International System Dynamics
Society Conference. Boston, MA
Simulation Application in Healthcare

60. Operation Research using DES
(Discrete Event Simulation)
1. Formulate the research question
2. Define the operational process (workflow)
3. Collect date to fit distribution
4. Construct and validate the model
5. Run experiment
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62. Crit Care Med 2007 Vol. 35, No. 11
Critical Importance of Timing

63. Spain Study
Ferrer R, et al. Improvement in process of care and outcome after a multicenter severe sepsis educational program in Spain. JAMA.
2008;299(19):2294-2303.

64. Research Methodology
Baseline Process
Identify Causes of
Delay
Process Modeling
Suggestions for
Improvement
Measure ImpactSensitivity Analysis
Statistical Analysis
Root Cause Analysis &
FMEA
Discrete-Event
Simulation
ANOVA
Design of Experiment
User Requirement
and Scope

65. Workflow analysis by providers

66. Data Collection
• Time frame
• Dec 2007 to June 2009
• Sample size:
• 600 sepsis patients
• Source of data
• Sepsis QI Project (Courtesy of Dr. Afessa)
• EMR: ICU Datamart
• Direct observations: CVC, fluid infusion, etc.
• Expert opinions: MD, RN, RT, Pharmacist, et al
• Administration database
• Obstacles with data
• Uncompleted dataset
• Care process variation

67. Fellow ResidentConsultant PharmacistBedside RN
Sepsis
Recongnition
Antibiotics/
Source Control
Fluid
Resuscitation
Central Venous
Catheterization
Vesopressor
Administration
Inotrope
Administration
Transfusion
Patient
SepsisResuscitationGoalReached
Simulation Modeling of Healthcare Delivery During Sepsis Resuscitation
Dong Y, et al. Optimization of healthcare delivery during sepsis resuscitation by simulation and modeling. Simulation in Healthcare 2010;5:423.

68. Accelerated
T&X
CVC Efficiency
ScVO2
Monitors
No CXR DelayEarly Recognition
ResuscitationRecognition
Sepsis Care Optimization by Discrete Event Simulation (S-CODES)

69. Model Validation
Empirical
Data
Model
Data
%
Variance
Duration (months) 18 18 0%
Total Sepsis
Patients
597 600 0.5%
Average number
of patients/day
2.4 2.7 -1.3 %
Average Cycle
Time (min)
382 418 9.4 %

70. Sepsis Resuscitation Time Reduction by Different Options
Clinical
Data
Sepsis Resusiation Time Reducation by Different Options
29.16
26.81
7.81
137.92
16.11
55.94
0.00
30.00
60.00
90.00
120.00
150.00
Opt 1 - Early Recog Opt 2 - Quick CVC Opt 3 - No X-Ray Opt 4 - Pre
Type/Cross
Opt 5 - ScVO2
Monitors
Opt 6 - All
Time(min)

71. DES study in clinical practices
• Analyze & Visualize patient
flow (Batarseh 2014)
• Optimize unit bed capacity
(Zhu 2012)
• Forecast near-future
operation status (Hoot
2009)
• Study interaction between
providers (Lim 2013)
• Evaluate ED/EMS
interaction (Stahl 2003)
• Decrease inpatient
boarding (Levin 2008)
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73. Recent Major Reports
• Executive Office of the President President’s Council of Advisors on Science and Technology: Report To The President Better Health Care And Lower Costs: Accelerating
Improvement Through Systems Engineering (May 2014)
• National Science Foundation: Operations Research - A Catalyst for Engineering Grand Challenges (May 2014)
• The ASQ Healthcare Division Marshall Plan: "Put Me In The Game, Coach! ” (The Quality Management Forum, Winter 2014)

75. Simulation to improve quality and safety
Constructive
Virtual
Live
Training
Assessment
Research and
Integration
Patient
Healthcare Providers
Healthcare Systems

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78. Learning from others

79. Summary
• Quality and patient safety are the
driver for value based healthcare
delivery
• Use more simulation to
• Improve provider and team skills
• Improve systems performance

80. From Mayo Clinic Center for Innovation

81. Healthcare Systems Modeling & Simulation Affinity
Group
goo.gl/PRIkog
goo.gl/0r5mOs
http://www.ssih.org/Interest-
Groups/Healthcare-Systems-Modeling-
Simulation
goo.gl/7QuuQd