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©2011 MFMER | slide-1
Medical Simulation 2.0
Improving value-based healthcare
delivery
Yue Dong, M.D.
Mayo Clinic Multidis...
Disclosures
• No financial COI
©2011 MFMER | slide-3
Mayo Clinic Multidisciplinary Simulation Center
Fellows
Anesthesiologist
Medical
Pulmonologist
Intensivist
Simulation
Medicine
Statistician
Administration
Informatics
ER ...
Multidisciplinary Collaboration
Dr. Hutian Lu
Dr. Susan Lu, Sura K Ak Qudah
Dr. Ashish Gupta
Dr. Mark Van Oyen, Pooyan Kaz...
Objectives
• Challenges facing healthcare professionals
to improve the healthcare delivery: Systems
Thinking and Patient S...
©2011 MFMER | slide-7
© 2010 Mayo Foundation for Medical
Education and Research
Vis-à-vis International Sepsis
Campaign
Institution Compliance, % Mortality, %
Spain
•Pre-intervention 5.3 44
•Post-
inter...
Time, June 22, 2010
Health System Safety
• 33.6 million
admissions to U.S.
hospitals in 1997
• 44,000- 98,000
Americans die each
year as a res...
*Rate of growth declining in recent years, McKinsey 2011
U.S. spends most, but lower life
expectancy relative to developed peers
Source: OECD Health Data, 2008
~$3 Trillion (~1/5 ...
Green LW. Making research relevant: if it is an evidence-based practice, where's the practice-
based evidence? Family Prac...
“Blue Highways” on the NIH Roadmap
Practice-based
research
Phase 3 and 4 clinical
trials
Observational studies
Survey rese...
The fundamental problem with the quality of
American medicine is that we’ve failed to view
delivery of health care as a sc...
Temporal Trends in Rates of Patient Harm
Resulting from Medical Care
Temporal Trends in Rates of Patient Harm Resulting fr...
Complexity in ICU
Critical Care at Mayo
Courtesy of Dr. Vitaly Herasevich
Health care as a complex
adaptive system
W. B. Rouse. Health care as a complex adaptive system: Implications for design an...
Complex adaptive systems
• nonlinear and dynamic, system behaviors may appear to be
random or chaotic.
• composed of indep...
William Worrall Mayo, MD
“Left open for further thought
and research”
The world is a complex system of systems
Communication
$ 3.96 Tn
Transportation
$ 6.95 Tn
Leisure / Recreation /
Clothing
...
©2011 MFMER | slide-27
System integration
Human beings make mistakes because
the systems, tasks and processes they
work in are poorly designed.
Dr. Lucian Leape
Eve...
Transforming healthcare:
a safety imperative
L Leape, D Berwick, C Clancy, et al. Qual Saf Health Care 2009; 18:424-428
Swiss Cheeses Model
©2011 MFMER | slide-30
Outcome + Safety + Service
Value =
Cost over time
Leveraging for Highest Value
Smoldt RK, Cortese DA. Pay-for-performance ...
Systems Approach
to Improve Patient Safety
Martinez, et al. Anesth Analg 2010 110: 307-311
“ Simply educating and training more physicians will not be enough to address these
shortages. Complex changes such as imp...
2011, Health IT and Patient Safety: Building Safer Systems for Better
Care, Committee on Patient Safety and Health Informa...
Adjust structure and process to eliminate or
minimize risks of health care-associated
injury, before they have an adverse ...
System Interventions
Systems Engineering Initiative for Patient Safety (SEIPS) Work system design for patient safety: the ...
WHO Global Priorities for Patient Safety Research
Bates DW, et al. Global priorities for patient safety research. BMJ 2009...
Structure, process or outcome: which
contributes most to patients' overall
assessment of healthcare quality?
• Experiences...
“We can’t solve
problems by
using the same
kind of thinking
we used when
we created
them”
Delivery System
Order (2 lanes !)
Pay
Pickup
System Design Thinking
Service centered = Customer centered
Escape Fire, Berwick, 2006
Mistake Proofing/Force Functioning
• designing the system to prevent
errors
• designing procedures to make errors
visible when they do occur so that
they may...
Common patient safety
improvement efforts
• Culture
• Crew resource
management
• Event reporting:
close-claim; near-
miss
...
Terminology
• Model vs. Simulation (noun)
Model can be used WRT conceptual,
specification, or computational levels
Simulat...
Clinical Micro-system
Clinical
Delivery System
Patient Providers Processes
Complexity/SOP
Bottleneck/ Waste/
no value adde...
• Simulation is the imitation or representation of
one act or system by another.
• Healthcare simulations can be said to h...
Simulation based medical education
The 11 dimensions of simulation applications.
Gaba D M Qual Saf Health Care 2004;13:i2-i10
©2004 by BMJ Publishing Group L...
Medical Education
• Study the effectiveness of
simulation based medical education
(SBME)
• Developing valid outcome
assess...
©2011 MFMER | slide-51
Simulation-based objective assessment Discern Clinical Proficiency in Central Line Placement, Dong,...
©2011 MFMER | slide-52
Patient Outcomes
Mastery
n=26
Control
n=24
Adjusted Analysis
OR (95%CI) p-value
# Patients/Repairs ...
Skill Acquisition Curve
Impact of Zero-Risk Training
CP1345275-1
Clinical competence
Metricassessment
(e.g.,compositescore...
The First Research Consensus Summit of the
Society for Simulation in Healthcare
• Simulation for Learning and Teaching Pro...
ALL MODELS ARE WRONG
BUT SOME ARE USEFUL
George Box
Simulation in Healthcare
Simulation 1.0
• Simulation as subject
• At simulation center
• Education
Training effectiveness
...
Military Simulation Spectrum
J G Taylor, Modeling and Simulation of Land Combat, ed L G Callahan, Georgia Institute of Tec...
Human factor and Usability research
• Using simulation as a tool to study human
performance variation under different “str...
The effect of drug concentration expression on
epinephrine dosing errors: a randomized trial
Wheeler DW, Carter JJ, Murray...
Ahmed, et al. Critical Care Medicine, 39(7) 1626-1634
The effect of two different electronic health record user interfaces...
Complexity of Sepsis Resuscitation in ICU
Adopted from: Network medicine--from obesity to the "disease". Barabási AL., N E...
Trial and error
©2011 MFMER | slide-63
http://www.economist.com/node/174411 http://www.wired.com/magazine/2011/12/ff_causa...
How about the population at risk
Modeling &
Simulation
Computer Simulation
R. P. Science, New Series, Vol. 256, No. 5053 (Apr. 3, 1992)
Simulation in manufacturing and business: A review
M. Jahangirian, T. Eldabi, A. Naseer, L.K. Stergioulas and T. Young, Si...
Simulation-based Engineering and Science
©2011 MFMER | slide-69
Simulation and Healthcare
Delivery
System Engineering Tools for Healthcare Delivery
Proctor P. Reid, W. Dale Compton, Jerome H. Grossman, and Gary Fanjiang, ...
©2011 MFMER | slide-73
Systems Engineering: Modeling
and Simulation
• Using system engineering/operation
research approach...
©2011 MFMER | slide-74
Project 1: Sepsis Workflow Redesign
Sepsis Care Optimization by Discrete Event Simulation
(S-CODES)
Place Central
Line
Central
Line
Approval
Etc, etc,
etc
Don...
Project 2: Scheduling for Critical Care Fellows using Modeling and
Simulation: The Trade Off Between Duty Hours and Hand-o...
Comparison of Provider Scheduling
©2011 MFMER | slide-77
Provider
Transfers (H/L)
per month
Patient
Handoffs
(avg./mo)
ICU...
Project 3: Time-motion observational study of
multidisciplinary ICU rounding in a teaching hospital
• To describe the curr...
©2011 MFMER | slide-79
Project 4: Education Game:
The Friday Night at ER ™
Professional Society
Challenges and opportunities
• Fragmentation of
care delivery
• Access
information from
various sources
• Clinical
impleme...
• 1920’: BME, Biophysics, Medical Physics
• 1943: German Biophysical Society
• 1948: Annual Conference of Engineering in
M...
Road map for
better healthcare delivery
Road map for
better healthcare delivery
Dong Y, et al. ICU Operational Modeling and Analysis. In: Kolker A, Story P, eds. ...
Key Messages
• The complexity of healthcare delivery
systems contributes to preventable
medical error and insufficient qua...
©2011 MFMER | slide-89
Medicine: Human interactions
• email: dong.yue@mayo.edu
• Blog: simdoc.wordpress.com
• Twitter: dongyue
• LinkedIn:
• CiteUlike: simdoc
Medical Simulation 2.0:  Improving value-based healthcare delivery
Medical Simulation 2.0:  Improving value-based healthcare delivery
Medical Simulation 2.0:  Improving value-based healthcare delivery
Medical Simulation 2.0:  Improving value-based healthcare delivery
Medical Simulation 2.0:  Improving value-based healthcare delivery
Medical Simulation 2.0:  Improving value-based healthcare delivery
Medical Simulation 2.0:  Improving value-based healthcare delivery
Medical Simulation 2.0:  Improving value-based healthcare delivery
Medical Simulation 2.0:  Improving value-based healthcare delivery
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Medical Simulation 2.0: Improving value-based healthcare delivery

  1. 1. ©2011 MFMER | slide-1 Medical Simulation 2.0 Improving value-based healthcare delivery Yue Dong, M.D. Mayo Clinic Multidisciplinary Simulation Center METRIC (Multidisciplinary Epidemiology and Translational Research in Intensive Care) Mayo Clinic Center for Science of Healthcare Delivery
  2. 2. Disclosures • No financial COI
  3. 3. ©2011 MFMER | slide-3 Mayo Clinic Multidisciplinary Simulation Center
  4. 4. Fellows Anesthesiologist Medical Pulmonologist Intensivist Simulation Medicine Statistician Administration Informatics ER medicine Research Coordinator Collaborators Pediatrician METRIC (Multidisciplinary Epidemiology and Translational Research in Intensive Care)
  5. 5. Multidisciplinary Collaboration Dr. Hutian Lu Dr. Susan Lu, Sura K Ak Qudah Dr. Ashish Gupta Dr. Mark Van Oyen, Pooyan Kazemian Bjorn, Berg
  6. 6. Objectives • Challenges facing healthcare professionals to improve the healthcare delivery: Systems Thinking and Patient Safety • Summarize simulation and modeling tools for systematic analysis and optimization complex system processes and interventions • Describe common computer simulation applications for quality improvement and patient safety in ICU.
  7. 7. ©2011 MFMER | slide-7 © 2010 Mayo Foundation for Medical Education and Research
  8. 8. Vis-à-vis International Sepsis Campaign Institution Compliance, % Mortality, % Spain •Pre-intervention 5.3 44 •Post- intervention 10.0 39.7 International •Pre-intervention 10.9 37 •Post- intervention 41.3 30 Mayo •Baseline 10.5 31.5 •Sepsis QI 58.4 22.0
  9. 9. Time, June 22, 2010
  10. 10. Health System Safety • 33.6 million admissions to U.S. hospitals in 1997 • 44,000- 98,000 Americans die each year as a result of medical errors. • Total cost $17- $29 billion
  11. 11. *Rate of growth declining in recent years, McKinsey 2011
  12. 12. U.S. spends most, but lower life expectancy relative to developed peers Source: OECD Health Data, 2008 ~$3 Trillion (~1/5 GDP) ~ 30% may be waste USA
  13. 13. Green LW. Making research relevant: if it is an evidence-based practice, where's the practice- based evidence? Family Practice 2008; 25: i20–i24
  14. 14. “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
  15. 15. The fundamental problem with the quality of American medicine is that we’ve failed to view delivery of health care as a science. • understanding disease biology • finding effective therapies • insuring those therapies are delivered effectively Peter Pronovost http://www.letstalkhealthcare.org/health-care-costs/how-a-checklist-can-improve-health-care/
  16. 16. Temporal Trends in Rates of Patient Harm Resulting from Medical Care Temporal Trends in Rates of Patient Harm Resulting from Medical Care. Landrigan, et al, N Engl J Med 2010 ; 363 : 2124 - 2134
  17. 17. Complexity in ICU
  18. 18. Critical Care at Mayo Courtesy of Dr. Vitaly Herasevich
  19. 19. Health care as a complex adaptive system W. B. Rouse. Health care as a complex adaptive system: Implications for design and management. The Bridge, 38(1), Spring 2008.
  20. 20. Complex adaptive systems • nonlinear and dynamic, system behaviors may appear to be random or chaotic. • composed of independent agents whose behavior is based on physical, psychological, or social rules rather than the demands of system dynamics. • agents’ needs or desires, their goals and behaviors are likely to conflict. In response to these conflicts or competitions, agents tend to adapt to each other’s behaviors. • agents are intelligent. As they experiment and gain experience. • adaptation and learning tend to result in self-organization. Behavior patterns emerge rather than being designed into the system. • no single point(s) of control. Rouse, 2000
  21. 21. William Worrall Mayo, MD “Left open for further thought and research”
  22. 22. The world is a complex system of systems Communication $ 3.96 Tn Transportation $ 6.95 Tn Leisure / Recreation / Clothing $ 7.80 Tn Healthcare $ 4.27 Tn Food $ 4.89 Tn Infrastructure $ 12.54 Tn Govt. & Safety $ 5.21 Tn Finance $ 4.58 Tn Electricity $ 2.94 Tn Education $ 1.36 Tn Water $ 0.13 Tn Global system-of-systems $54 Trillion (100% of WW 2008 GDP) Same Industry Business Support IT Systems Energy Resources Machinery Materials Trade Legend for system inputs IBM analysis based on OECD data. Note: Size of bubbles represents systems’ economic values. Arrows represent the strength of systems’ interaction. Source: IBM Institute for Business Value analysis of Organisation for Economic Co-operation and Development (OECD) data.
  23. 23. ©2011 MFMER | slide-27 System integration
  24. 24. Human beings make mistakes because the systems, tasks and processes they work in are poorly designed. Dr. Lucian Leape Every system is perfectly designed to get the results it gets. Dr. Donald M. Berwick Systems approach to improve patient safety
  25. 25. Transforming healthcare: a safety imperative L Leape, D Berwick, C Clancy, et al. Qual Saf Health Care 2009; 18:424-428
  26. 26. Swiss Cheeses Model ©2011 MFMER | slide-30
  27. 27. Outcome + Safety + Service Value = Cost over time Leveraging for Highest Value Smoldt RK, Cortese DA. Pay-for-performance or pay for value? Mayo Clinic Proceedings 2007;82:210-3
  28. 28. Systems Approach to Improve Patient Safety Martinez, et al. Anesth Analg 2010 110: 307-311
  29. 29. “ 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.” The Complexities of Physician Supply and Demand: Projections Through 2025. 2008 AAMC http://www.aamc.org/workforce
  30. 30. 2011, Health IT and Patient Safety: Building Safer Systems for Better Care, Committee on Patient Safety and Health Information Technology; Institute of Medicine
  31. 31. 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)
  32. 32. System Interventions 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.
  33. 33. WHO Global Priorities for Patient Safety Research Bates DW, et al. Global priorities for patient safety research. BMJ 2009;338:b1775
  34. 34. Structure, process or outcome: which contributes most to patients' overall assessment of healthcare quality? • Experiences regarding process aspects explained most of the variance in the global rating (16.4– 23.3%), followed by structure aspects (8.1–21.0%). Experiences regarding outcome did not explain much variance in the global rating in any of the patient groups (5.3–13.5%). • What is patient-centered care? BMJ Qual Saf doi:10.1136/bmjqs.2010.042358
  35. 35. “We can’t solve problems by using the same kind of thinking we used when we created them”
  36. 36. Delivery System
  37. 37. Order (2 lanes !) Pay Pickup System Design Thinking Service centered = Customer centered
  38. 38. Escape Fire, Berwick, 2006 Mistake Proofing/Force Functioning
  39. 39. • designing the system to prevent errors • designing procedures to make errors visible when they do occur so that they may be intercepted • designing procedures for mitigating the adverse effects of errors when they are not detected and intercepted Nolan, 2000 BMJ Department of Health and the Design Council in England 2003
  40. 40. Common patient safety improvement efforts • Culture • Crew resource management • Event reporting: close-claim; near- miss • Root cause analysis • Human factor design • Simulation • Technology • Lean, six-sigma • Etc.
  41. 41. Terminology • Model vs. Simulation (noun) Model can be used WRT conceptual, specification, or computational levels Simulation is rarely used to describe the conceptual or specification model Simulation is frequently used to refer to the computational model (program) • Model vs. Simulate (verb) To model can refer to development at any of the levels To simulate refers to computational activity Steve Park and Larry Leemis
  42. 42. Clinical Micro-system Clinical Delivery System Patient Providers Processes Complexity/SOP Bottleneck/ Waste/ no value added Education/Training Supply/Demand
  43. 43. • Simulation is the imitation or representation of one act or system by another. • Healthcare simulations can be said to have four main purposes – education, assessment, research, and health system integration to facilitate patient safety... • Simulations may also add to our understanding of human behavior in the true–to–life settings in which professionals operate.
  44. 44. Simulation based medical education
  45. 45. The 11 dimensions of simulation applications. Gaba D M Qual Saf Health Care 2004;13:i2-i10 ©2004 by BMJ Publishing Group Ltd The 11 dimensions of simulation applications
  46. 46. Medical Education • Study the effectiveness of simulation based medical education (SBME) • Developing valid outcome assessment instrument, stretch measurement endpoints from the simulation lab into clinical practice (association studies) • Provide highly reliable data for decision support and high-stakes testing.
  47. 47. ©2011 MFMER | slide-51 Simulation-based objective assessment Discern Clinical Proficiency in Central Line Placement, Dong, et. al, 2010
  48. 48. ©2011 MFMER | slide-52 Patient Outcomes Mastery n=26 Control n=24 Adjusted Analysis OR (95%CI) p-value # Patients/Repairs 48/72 38/58 Intra-op Complications* At least one of any type 5 (7) 17 (29) OR 0.15 (0.04, 0.59) 0.006 Post-op Complications* At least one of any type 4 (9) 15 (26) OR 0.17 (0.04, 0.74) 0.018 Overnight Stay* 5 (7) 12 (21) OR 0.37 (0.08, 1.67) 0.20 *N (%) Simulation-Based Mastery Learning Improves Patients Outcomes in Laparoscopic Inguinal Herniorrhaphy, Benjamin Zendejas, MD, MSc
  49. 49. Skill Acquisition Curve Impact of Zero-Risk Training CP1345275-1 Clinical competence Metricassessment (e.g.,compositescore) Time Traditional training Safety standard Simulation-based training Dong et al, Chest 2010
  50. 50. The First Research Consensus Summit of the Society for Simulation in Healthcare • Simulation for Learning and Teaching Procedural Skills: The State of the Science • Simulation-Based Team Training in Healthcare • A Path to Better Healthcare Simulation Systems: Leveraging the Integrated Systems Design Approach • The Study of Factors Affecting Human and Systems Performance in Healthcare using Simulation • Literature Review: Instructional Design and Pedagogy Science in Healthcare Simulation • Evaluating the Impact of Simulation on Translational Patient Outcomes • Research Regarding Methods of Assessing Learning Outcomes • Research Regarding Debriefing as Part of the Learning Process • Simulation-Based Assessment of the Regulation of Healthcare Professionals • Reporting Inquiry in Simulation Simul Healthc. 2011 Aug;6 Suppl:S1-9.
  51. 51. ALL MODELS ARE WRONG BUT SOME ARE USEFUL George Box
  52. 52. Simulation in Healthcare Simulation 1.0 • Simulation as subject • At simulation center • Education Training effectiveness Psychometric qualities Ecological validity Simulation 2.0 • Simulation as tool • Everywhere • Daily practices System integration Human factors Usability of device, process, etc.
  53. 53. Military Simulation Spectrum J G Taylor, Modeling and Simulation of Land Combat, ed L G Callahan, Georgia Institute of Technology, Atlanta, GA, 1983
  54. 54. Human factor and Usability research • Using simulation as a tool to study human performance variation under different “stress conditions” (fatigue, cognition, workload, etc.) • Investigating provider behaviors/tasks Observation “in the wild” (Ethnography) Simulation environment • Conduct usability testing of devices instrument and processes, using information driven approach for new system design • Evaluation of the impact on clinical practices
  55. 55. 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)
  56. 56. 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
  57. 57. Complexity of Sepsis Resuscitation in ICU 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
  58. 58. Trial and error ©2011 MFMER | slide-63 http://www.economist.com/node/174411 http://www.wired.com/magazine/2011/12/ff_causation/all/1
  59. 59. How about the population at risk
  60. 60. Modeling & Simulation
  61. 61. Computer Simulation R. P. Science, New Series, Vol. 256, No. 5053 (Apr. 3, 1992)
  62. 62. Simulation in manufacturing and business: A review M. Jahangirian, T. Eldabi, A. Naseer, L.K. Stergioulas and T. Young, Simulation in manufacturing and business: a review, European Journal of Operational Research 203 (2010), pp. 1–13
  63. 63. Simulation-based Engineering and Science
  64. 64. ©2011 MFMER | slide-69
  65. 65. Simulation and Healthcare Delivery
  66. 66. System Engineering Tools for Healthcare Delivery Proctor P. Reid, W. Dale Compton, Jerome H. Grossman, and Gary Fanjiang, Editors, Committee on Engineering and the Health Care System, Institute of Medicine and National Academy of Engineering, 2005
  67. 67. ©2011 MFMER | slide-73 Systems Engineering: Modeling and Simulation • Using system engineering/operation research approach and readily available software(discreet event simulation, etc.) build a “test and learn” capacity to study system performance and identify the bottleneck, • provide re-designed alternatives to improve safety and efficiency of healthcare delivery system. • conduct a valid test of quality improvement innovations before clinical implementation
  68. 68. ©2011 MFMER | slide-74 Project 1: Sepsis Workflow Redesign
  69. 69. Sepsis Care Optimization by Discrete Event Simulation (S-CODES) Place Central Line Central Line Approval Etc, etc, etc Dong Y, Lu H, Rotz J, et al. Simulation Modeling of Healthcare Delivery During Sepsis Resuscitation. Critical Care Medicine 2009;37:A334
  70. 70. Project 2: Scheduling for Critical Care Fellows using Modeling and Simulation: The Trade Off Between Duty Hours and Hand-offs Fellow A Fellow B Fellow C 7 am 7 pm Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Handoffs 0 2 1 0 1 4 Provider Transfer Patient Handoff
  71. 71. Comparison of Provider Scheduling ©2011 MFMER | slide-77 Provider Transfers (H/L) per month Patient Handoffs (avg./mo) ICU Coverage (hrs/wk) Average Duty Hours (hrs/wk) Old Schedule 84 (84/0) 650 ± 4 294 73.5 New Schedule 112 (67/45) (+25%) 860 ± 5 (+33%) 312 (+6%) 62.4 (-15%) Janish, Dong, SCCM, 2011
  72. 72. Project 3: Time-motion observational study of multidisciplinary ICU rounding in a teaching hospital • To describe the current practice, and structure of the morning multidisciplinary round in the ICU practices (MICU, SICU) • Prospective field observation of ICU provides task (consultant, fellow, resident/intern, nurse, pharmacist) based on systems engineering approach • Task categories defined based on provider survey • Purpose strategies (work-flow redesign, new EMR interface) to improve the efficiency of ICU round, reduce MEOW patient outcome provider satisfaction
  73. 73. ©2011 MFMER | slide-79 Project 4: Education Game: The Friday Night at ER ™
  74. 74. Professional Society
  75. 75. Challenges and opportunities • Fragmentation of care delivery • Access information from various sources • Clinical implementation • System integration • Health IT (mobile, cloud, social networking, big data) • Provider education and change culture
  76. 76. • 1920’: BME, Biophysics, Medical Physics • 1943: German Biophysical Society • 1948: Annual Conference of Engineering in Medicine and Biology/Radiation Research Society • 1961: International Federation of Medical and Biological Engineering • 1968:Biomedical Engineering Society
  77. 77. Road map for better healthcare delivery
  78. 78. Road map for better healthcare delivery Dong Y, et al. ICU Operational Modeling and Analysis. In: Kolker A, Story P, eds. Management Engineering for Effective Healthcare Delivery: Principles and Applications. Hershey, Pennsylvania, USA: IGI Global; 2011.
  79. 79. Key Messages • The complexity of healthcare delivery systems contributes to preventable medical error and insufficient quality • Computer modeling/simulatio coupled with realistic patient simulation represents a potent catalyst in adapting systems engineering principles to healthcare • The medical community needs partnership with the systems engineering community to best deliver high value care
  80. 80. ©2011 MFMER | slide-89 Medicine: Human interactions
  81. 81. • email: dong.yue@mayo.edu • Blog: simdoc.wordpress.com • Twitter: dongyue • LinkedIn: • CiteUlike: simdoc
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