medical simulation 2.0: improving value-based healthcare delivery

©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

Disclosures

• No financial COI

©2011 MFMER | slide-3

Mayo Clinic Multidisciplinary Simulation Center

Fellows

AnesthesiologistMedical

Pulmonologist

Intensivist

Simulation Medicine

Statistician

Administration

Informatics

ER medicine

Research Coordinator

Collaborators

PediatricianMETRIC (Multidisciplinary Epidemiology and Translational Research in Intensive Care)

Multidisciplinary Collaboration

Dr. Hutian Lu

Dr. Susan Lu, Sura K Ak Qudah

Dr. Ashish Gupta

Dr. Mark Van Oyen, Pooyan Kazemian

Bjorn, Berg

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.

©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-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

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 result of medical errors.

• Total cost $17- $29 billion

*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 GDP)~ 30% may be waste

USA

Green LW. Making research relevant: if it is an evidence-based practice, where's the practice-based evidence? Family Practice 2008; 25: i20–i24

“Blue Highways” on the NIH Roadmap

Practice-basedresearch

Phase 3 and 4 clinicaltrialsObservational studiesSurvey research

Basic scienceresearch

Preclinical studiesAnimal research

Human clinicalresearch

Controlledobservational studiesPhase 3 clinical trials

T1Case series

Phase 1 and 2clinical trials

Clinical practice

Delivery of recommendedcare to right pt at right timeIdentification of new clinicalquestions and gaps in care

T2

Translationto humans

T2Guideline

developmentMeta-analyses

Systematicreviews

Translationto patients

T3Dissemination

researchImplementation

research

Translationto practice

Westfall JM et al: JAMA 297:403, 2007

Bench Bedside Practice

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/

Temporal Trends in Rates of Patient HarmResulting 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

Complexity in ICU

Critical Care at MayoCardiac SurgeryMedical Cardiac

Medical

Mixed

Neurology

Pediatric

Thoracic and Vascular

Transplant

Surgical/trauma

Neonatal

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 and management. The Bridge, 38(1), Spring 2008.

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

William Worrall Mayo, MD

“Left open for further thoughtand research”

©2011 MFMER | slide-25

System integration

Human beings make mistakes becausethe systems, tasks and processes theywork 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

Transforming healthcare: a safety imperative

L Leape, D Berwick, C Clancy, et al. Qual Saf Health Care 2009; 18:424-428

Swiss Cheeses Model

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Outcome + Safety + ServiceValue =

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

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 theseshortages. 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

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

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)

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.

WHO Global Priorities for Patient Safety Research

Bates DW, et al. Global priorities for patient safety research. BMJ 2009;338:b1775

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

“We can’t solve problems by using the same kind of thinking we used when we created them”

Delivery System

Order (2 lanes !)

PayPickup

System Design ThinkingService 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 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

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.

Terminology

• Model vs. Simulation (noun)Model can be used WRT conceptual, specification, or computational levelsSimulation is rarely used to describe the conceptual or specification modelSimulation is frequently used to refer to the computational model (program)

• Model vs. Simulate (verb) To model can refer to development at any of the levelsTo simulate refers to computational activity

Steve Park and Larry Leemis

Clinical Micro-system

Clinical Delivery System

Patient Providers Processes

Complexity/SOPBottleneck/ Waste/

no value addedEducation/Training Supply/Demand

• 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. 

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 Ltd

The 11 dimensions of simulation applications

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.

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

©2011 MFMER | slide-50

Patient Outcomes

Masteryn=26

Controln=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

Skill Acquisition CurveImpact of Zero-Risk Training

CP1345275-1

Clinical competence

Me

tric

ass

ess

me

nt

(e.g

., co

mp

osi

te s

core

)

Time

Traditional training

Safety standard

Simulation-based training

Dong et al, Chest 2010

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.

ALL MODELS ARE WRONG BUT SOME ARE USEFUL

George Box

Simulation in Healthcare

Simulation 1.0

• Simulation as subject

• At simulation center

• EducationTraining effectivenessPsychometric qualitiesEcological validity

Simulation 2.0

• Simulation as tool

• Everywhere

• Daily practicesSystem integrationHuman factorsUsability of device, process, etc.

O Research

O Education

O Clinical Practice

Military Simulation Spectrum

J G Taylor, Modeling and Simulation of Land Combat, ed L G Callahan, Georgia Institute of Technology, Atlanta, GA, 1983

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/tasksObservation “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

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)

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

Complexity of Sepsis Resuscitation in ICUComplexity 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 RTPharmacist

Nurse

Time

Bas

elin

e

Pat

ien

t O

utc

om

e,

Pro

vid

er S

atis

fact

ion

s

Trial and error

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http://www.economist.com/node/174411 http://www.wired.com/magazine/2011/12/ff_causation/all/1

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, Simulation in manufacturing and business: a review, European Journal of Operational Research 203 (2010), pp. 1–13

Simulation-based Engineering and Science

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Simulation and Healthcare Delivery

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

©2011 MFMER | slide-71

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

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Project 1: Sepsis Workflow Redesign

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

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

Comparison of Provider Scheduling

©2011 MFMER | slide-75

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

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 MEOWpatient outcomeprovider satisfaction

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Project 4: Education Game: The Friday Night at ER ™

Professional Society

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

• 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

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. Management Engineering for Effective Healthcare Delivery: Principles and Applications. Hershey, Pennsylvania, USA: IGI Global; 2011.

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

©2011 MFMER | slide-87

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