LAI Healthcare Research
Prof. Debbie Nightingale
Jorge Oliveira and Jordan Peck
Massachusetts Institute of Technology
October 14, 2009
Agenda
•
Research Motivation and LAI Alignment
•
LAI Healthcare Research Pipeline
•
Overview of Research Projects
•
Final Comments
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 2
Research Motivation
Life Expectancy at Birth
and GDP Per Capita
 Over 16% of US GDP spent in healthcare expenses
Cost
2005 OECD Data
 Hospital care represents 30.8% of total expenditure
 49% of expenditure concentrated in only 5% of
population
 Individuals over 65 years old expected to increase
over 50% by 2020
 98,000 deaths attributed to medical errors
Quality
 Adults on average only receive 55% of recommended care
 Emergency Departments are overcrowded nationwide
 Provider fragmentation unable of creating sufficient volume
 45 million Americans are uninsured
Access
 Fragmented provider network, 75% being small or single practices
 Recent survey indicated 40% of Americans received uncoordinated care
 Fragmented payment systems, health plans, information systems, etc
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 3
Cross Industry
Enterprise Challenges
Aerospace
Healthcare
•
Overarching commitment to ensure
global peace and security
•
Overarching commitment to provide
world class medical care
•
Incumbent higher, faster, farther
mindset
•
Incumbent overuse, underuse, and
misuse mindset
•
Declining defense dollars after Cold
War (fewer military aircraft programs;
industry consolidation)
•
Overburdened healthcare expenditure
as a % of GDP (proliferation of
fragmented disjointed providers)
•
Inherently complex industry:
•
Inherently complex industry
• Multiple stakeholders with misaligned
• Multiple stakeholders with misaligned
objectives and numerous constraints
objectives and numerous constraints
• Capital Intensive
• Complex product development
•
Uncertain outcome in contract awarding
http://lean.mit.edu
• Capital Intensive
• Complex service provision
•
Uncertain outcome in value sharing
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 4
LAI - A Consortium Dedicated To
Cross Industry Enterprise Performance
• Enable Enterprises to effectively, efficiently and reliably
create value in a complex and dynamic environment
• Enable focused and accelerated transformation of
complex enterprises
• Collaborative engagement of all stakeholders in
Government, Industry and Academia
• Understand, develop, and institutionalize principles,
processes, behaviors and tools
Parallel issues/needs in healthcare!
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 5
Agenda
•
Healthcare Research Motivation and LAI Alignment
•
LAI Healthcare Research Pipeline
•
Overview of Research Projects (JO,JP, and JM)
•
Final Comments
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 6
LAI Healthcare Research Pipeline
Ongoing Research
•
•
•
High Performing Hospital Enterprise Architectures (Jorge Oliveira)
•
•
NEWDIGS Drug Development ESAT (Judy Maro and Debbie Nightingale)
New England Veteran Affairs (Jordan Peck)
Multiple Class Projects from Integrating the Lean Enterprise and Enterprise
Architecting
Impact of Advanced DNA Sequencing Technologies on Clinical Microbiology
Processes (Rob Nicol)
Existing Proposals in Enterprise Systems
•
•
NEWDIGS Phase II
PTSD Systems Study
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 7
Agenda
•
Research Motivation and LAI Alignment
•
LAI Healthcare Research Pipeline
•
Overview of Research Projects
• Jorge Oliveira
• Jordan Peck
• NEWDIGS (Debbie Nightingale/Judy Maro)
• PTSD (Debbie Nightingale)
• DNA Sequencing
•
Final Comments
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 8
Agenda
•
Research Motivation and LAI Alignment
•
LAI Healthcare Research Pipeline
•
Overview of Research Projects
• Jorge Oliveira
• Jordan Peck
• NEWDIGS (Debbie Nightingale/Judy Maro)
• PTSD (Debbie Nightingale)
• DNA Sequencing
•
Final Comments
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 9
Health Care is a Complex
Socio-Technical System
“Simply stated, the US does not
have a health care system.”
Regulator
Payer
William Brody, President of Johns Hopkins
University, 2007
Nursing
Home
Hospital
Operating
Rooms
Nurse
Psychiatrist
Physician
Supply
Technician
http://lean.mit.edu
Medical
resident
Interest
Groups
Specialist
Care
Ancillary
Services
Pharmacy
Pharmacy
Inpatient
Units
Emergency
Department
Cleaning
Insurer
Primary
Care
Flu Clinic
Labs
Labs
Patient
Provider
Home
Care
Supplier
Primary
Care
Radiology
“…the strategies [hospitals]
develop and implement to
compete have a
significant effect on costs,
quality, and access to care.”
(Devers et al. 2003)
Admin staff
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 10
Greater Boston Hospital Case
•
Leading multi specialty physician led group practice
with national and international recognition (i.e.
neuro, liver, heart & vascular, etc)
2006 Highlights
• Emergency Visits:
• Total Beds:
• Total Staff:
• Total Income:
• Total Expenses:
• Operating Income:
Problem Statement
38,631
293
4263
$679,454,000
$628,525,000
$50,929,000
• Emergency Department (ED)
struggling to keep up with demand
• Long wait times in the ED and
patient leaving without being seen
• ED staff blame inpatient staff and
vice versa
• ED staff churn levels significant
What can be done to speed patient flow in the ED?
Where should a process improvement initiative focus?
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 11
Emergency Department VSM
Patient
Arrives
Registration::
Patient orders (paper)
Not L1
1
T System::
Patient chief complaint
MedTech Order Stack::
Patient orders (paper)
T System::
Priority assignment
(L1 :: L5)
L?
Blood lab:
Blood vials
T System::
Patient demographic,
Insurance, etc details
Follow-up if
tests show
an issue
Patient
leaves
Radiology Lab
Patient Tired of Waiting
L1
Triage
(room 1)
Check in
ED waiting
area
1
ED waiting
area
1
Not L1
Conduct
tests
(room 2)
Complete
Check in
L?
ED waiting
area
1
ED waiting
area
Measure
vital signs
1
Patient
placed in
ED bed
ED waiting
area
Assessment/
treatment
Patient in
ED bed
waiting
diagnosis
?
First EKG, blood
draw, then external tests
Patient
leaves
Yes
No /
“Tourist”
L1
Patient
ready?
Discharge
Note (1)
Note (2)
Patient
Arrives as Transfer
or EMS pick-up
Patient
Arrives as Transfer from
‘X’-Type Facility
x
Number of operators
Information flow
Patient flow
Patient idle
Patient
healthy
Re treat
patient
Phone:
Admitting Physician
requested
Patient
healthy
Patient
In ED bed
No
Note (3)
Note: (1) if bed not available, creative
process comes into play whereby a bed is
found for the patient (i.e. hallway, other)
Note (2): Check in initiated over phone and
completed once patient arrives.
Note (3): Some hospitals have an
agreement with Lahey where patients just
roll through the ER. ‘X’ is a fill-in until we
know what to call these types of facilities.
Note (1)
Note (3)
Pre Admit Tracking System:
Bed request
Note (1)
Patient direct
Diagnosis?
No
“Kick theto floor
tires”
Patient
Observation
Diagnosis?
“Kick the
tires”
Admit
patient
Admit
patient
Initiate
Patient Admit
Process
Check
patient
Ready?
Patient
In ED bed
Waiting for admit
physician
Admit Physician arrives
and checks patient
(visual & paperwork)
Yes
Sign orders
Note (2)
Inpatient
bed
available?
No
Moving Yes
Staff
available?
Transfer
Patient
Yes
Patient
In ED bed
x
Number of operators
Information flow
Note: (1) may involve additional tests, or lab
work
Note (2): Receiving floor requests ED to
‘hold onto’ patient for a period of time to
complete shift change or catch up on work
Note (3): After 11:00 p.m. Need to call Head
Nurse shift supervisor for bed assignment.
Patient flow
Patient idle
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 12
Emergency Department Analysis
Description of patient time spent in ED
Description of patient arrivals and departures
Simulation Modeling
Average time for each step of the patient process
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 13
Preliminary Findings
ED average length of stay considered problematic, but non-admitted
patients took 4 hours, whereas admitted patients took over 8 hours
Main
Findings
ED interacted well with some patient wards but not with others
ED heroic employee efforts said to be common rather than sporadic
ED metrics and strategic goals misaligned with overall hospital (X-Matrix)
Questions
For
Further
Study
Why was the ED managed as a silo rather than end-to-end?
Was the varying performance of ED interactions due to the payment model?
Could it be that different observed EA configurations were directly related to
the different observed performance levels?
“The problem of redesign gets harder and the evidence weaker as one
moves from the microsystem to the organization.”
Donald Berwick, President of Institute for Healthcare Improvement, 2002
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 14
Hospital Enterprise Architecture
Uninsured population; primary care
Diagnostic
unavailability; safety net compromised;
Non standardized admitting process;
patient boarding (i.e. admitted
patients held in ED due to lack of
inpatient beds); costly bolt ons
fee for service payment model
Policy / External Factors
Process
Focus on revenue generating
elective surgery; 16 strategic
objectives; ED absent of strategic
plan
Timely provision of care
compromised; overall hospital image
compromised
Organization
Products /
A
Services
Strategy
Knowledge
Low staff morale; physician cultural rifts; high volume
of staff churning; lack of productivity; finger pointing
between ED and elsewhere
Info/Infrastructure
Reliance on heroes and bed
czars; incomplete patient
record; high variation of
evidence based medicine within
and across providers
Fragmented information systems; costly proprietary software
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 15
“As Is” Enterprise Architecture
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 16
“To Be” Enterprise Architecture
Patient In the center of the
architecture
(Service-centered architecture)
Hospital processes oriented
around the patient
(Process-centered
architecture)
Information Technology
connects patient, knowledge,
process, organization
(IT/knowledge centered)
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 17
Overview of Research Methodology
Exploratory
Case 1
(Boston)
Literature
Review
• Literature Review
• Mostly health care
• Healthcare payment model
evolution (FFS, capitation,
etc)
• Hospital management
(functional, DRG, service
lines)
• Institutional dimension
(uninsured, cost, quality,
access)
• Lean best practice (Virginia
Mason, Mayo Clinic, etc)
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 18
Overview of Research Methodology
Exploratory
Case 1
(Boston)
Literature
Review
Research
Questions
• Research Questions
• How should hospital
enterprise performance be
measured?
• How does hospital
enterprise architecture
relate to hospital enterprise
performance?
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 19
Overview of Research Methodology
• Exploratory Case 2 (London)
Exploratory
Case 1
(Boston)
Literature
Review
Research
Questions
• Multi specialty hospital: 872
beds, 43 wards, 18
operating rooms, ED, UK
leader
• Burning platform: meeting
18 Week target
Exploratory
Case 2
(London)
• Method: 1 month onsite;
grounded theory
methodology
• Despite different contexts
hospitals shared strategic
and operational issues
• Multiple configurations
present with varying
performance
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 20
Overview of Research Methodology
• Extended Literature Review
Exploratory
Case 1
(Boston)
Literature
Review
Extended
Literature
Review
Research
Questions
Exploratory
Case 2
(London)
• Multidisciplinary performance
literature (categorical, process,
systems)
• Longitudinal in-depth study of
Organizational theory literature
(organizational effectiveness
criteria; ideal and hybrid
organization types;
configurations; frameworks;
proven relevant constructs; etc)
• Healthcare literature (hospital
typology for sampling, hospital
internal structures for theoretical
sampling, etc)
• Research method refinement
(multi-level analysis; embedded
case studies; grounded theory;
hybrid methods; theory maturity;
etc)
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 21
Overview of Research Methodology
• Refined Research Questions
Exploratory
Case 1
(Boston)
Refined
Research
Questions
http://lean.mit.edu
Literature
Review
Extended
Literature
Review
Research
Questions
Exploratory
Case 2
(London)
Does hospital enterprise
architecture relate to hospital
enterprise performance? How?
a) How is hospital enterprise
performance currently measured?
b) How could hospital enterprise
performance measurement be
improved using lean enterprise
architecture principles?
c) What are different internal
organizational design configurations
capable of supporting higher
performance for different service
complexity artifacts?
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 22
Overview of Research Methodology
Exploratory
Case 1
(Boston)
Refined
Research
Questions
Literature
Review
Extended
Literature
Review
Research
Questions
Exploratory
Case 2
(London)
• Refined EA Framework
• Augmented version of LAI
EA Framework conveying
theoretical richness, clear
constructs, and guidelines
to allow for subsequent
empirical testing and
refinement.
• Enhanced knowledge of EA
characterization.
Refined EA
Framework
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 23
Overview of Research Methodology
Exploratory
Case 1
(Boston)
Literature
Review
Research
Questions
Refined
Research
Questions
Extended
Literature
Review
Exploratory
Case 2
(London)
Refined EA
Framework
Remaining
Field Work
Write Up
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 24
Agenda
•
Research Motivation and LAI Alignment
•
LAI Healthcare Research Pipeline
•
Overview of Research Projects
• Jorge Oliveira
• Jordan Peck
• NEWDIGS (Debbie Nightingale/Judy Maro)
• PTSD (Debbie Nightingale)
• DNA Sequencing
•
Final Comments
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 25
VA Mental Health – Boston
ESD.62J/16.852J: Integrating the Lean Enterprise
Ellen Czaika
Clayton Kopp
Orietta Verdugo
Zakiya Tomlinson
Jordan Peck, Facilitator
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 26
X-Matrix
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Quality Improvement
Complience -VA Code of
Patient Concern & JCAHO
Evidence Based Care (inc.
Through Educational
Residencies)
Become World Class
Research Hospital
Accessible Care
12 012
s
Tobacco Measure
Mental Health Access
Waiting Times - Clinic
Mental Health Outpatient
Impatient Service
Enterprise
Metrics
0 0 0
Metrics vs. Processes
 Strong alignment with
outpatient treatment and
clinic wait times
 Missing metrics for key
processes
– Transfers to inpatient
– Program referrals
values such as:
– Operating within budget
– Well-documented
monetary transactions
Processes vs. Values
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Discharge from Inpatient
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Residential Treatment
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Transfer from Residential to
Inpatient
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Discharge from Residential
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Transfer to Outside Facility
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Referral to Residential
s
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4 2 2
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Research
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Referral to Inpatient
13 8 5
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Outpatient Treatment
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Human Resources
1
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Payroll
1
w
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Quality Assurance
1
s
w
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Inpatient Treatment
Transfer from Inpatient to
Residential
Facilities and Maintance
1
w
s
Stakeholder
Values
Stakeholder
Values
Metrics
w
w
13 9 4
Walk-in to Outpatient
Purchasing (Supplies &
Services)
0 0 0
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 Strong alignment in areas
of service, research, &
quality
 Processes addressing the
least stakeholder values
are primarily patient
movement
http://lean.mit.edu
1 0 1
0
0
3
0
0
0
w
s
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Transfer from VA ER to
Inpatient
Transfer from Urgent Care
to Inpatient
Transfer from Outside ER
to Inpatient
0 0 0
0 0 0
 Gap lies in aligning goals to
s
s
s
Strategic
Objectives
Key Processes
s
Mental Health Measure
s s
MH: SMI - MHICM Capacity
s
Residential Program (REACH)
 Strong alignment with
areas in service, care, &
research
0 5 6
MHICM Program - Day Program
Methadone Clinic
Values vs. Goals
s
s
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Upstanding member of local community
s
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Efficient Resource Management
Accurate and well-documented monetary
transactions
s
s
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12 2 3 1 5
23 1 1 0 1
35 3 4 1 6
Reasonable expectations and respectful
treatment of employees
Research Advancement
Knowledge Transfer
Communication and Implementation of VA
culture and values
s
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Operating within budget
s
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1
3
4
Fair Wages for services
Sufficient Inpatient and Outpatient Capacity
s s
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Clean, High Quality Facility
ss
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Accurate Patient Records
Availability of medications, supplies, and
equipment
s
s
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Safety/Security of premises
s
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Timely and accurate information flow
s
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01313s
Vocational Industry Program
documented
 Research is a goal but not
measured locally
s
01212s
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5 6 4 3 0 1 5 3 0 2 1
7 7 5 4 4 5 7 5 2 3 4
Serve Boston Healthcare
System
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Team Oriented - Integrated
Care
s
01313s
Substance Abuse Outpatient Program
Substance Abuse Intensive Outpaitent
Program
 Goals are not formal or
2 1 2 0 2 2
5 5 4 4 5 4
7 6 6 4 7 7
Timeliness of diagnosis and treatment
Quality of patient experience (minimal
discomfort respectful etc )
 Very strong alignment with
most metrics on target
2
5
7
Correctness of diagnosis and treatment
2 2 2 2 2 2
4 4 4 4 4 4
6 6 6 6 6 6
Strategic
Goals
Metrics vs. Objectives
 Strong Alignment
 Weak Alignment
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 27
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Quality Improvement
Complience -VA Code of Patient
Concern & JCAHO
Evidence Based Care (inc. Through
Educational Residencies)
Become World Class Research
Hospital
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Accessible Care
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Strategic
Objectives
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Quality Improvement
Complience -VA Code of
Patient Concern & JCAHO
Evidence Based Care (inc.
Through Educational
Residencies)
Become World Class
Research Hospital
Accessible Care
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Stakeholder
Values
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•
•
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Very Strong Alignment Between Strategic Goals and Metrics
Indicative of a Strong Top Level
Metrics are chosen by national and reported regularly
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http://lean.mit.edu
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System
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MHICM Program - Day Program
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Program
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2
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0
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s
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transactions
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culture and values
s
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s
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s
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s
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equipment
s
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2
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Safety/Security of premises
s
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0 13 13
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2
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1
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2
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2
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2
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2
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Impatient Service
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Program
2
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6
9
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5
7
6
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7
5
2
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© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 28
3
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metrics.
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results rather than directly measuring
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Walk-in to Outpatient
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1
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http://lean.mit.edu
1
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© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 29
Transfer from VA ER to Inpatient
s
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Key Processes are primarily focused on
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are taken into account.
w
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w
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© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 30
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System
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Complience -VA Code of
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Through Educational
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Research Hospital
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Impatient Service
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Program
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Stakeholder Values vs. Strategic Objectives
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Once again the top level design of the VA system leads to strong
strategic objectives that are carefully aligned to the stakholder
values as seen from the top.
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s
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2
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2 1
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s
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w
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Hospital
s
w
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4
Research Advancement
s
3
1
4
Reasonable expectations and
respectful treatment of employees
s
s
1
2
3
Sufficient Inpatient and Outpatient
Capacity
s
w
2
0
2
Fair Wages for services
Team Oriented - Integrated Care
w
2
3
5
Operating within budget
w
2
5
7
Availability of medications, supplies,
and equipment
w
4
1
5
Accurate Patient Records
s
Timely and accurate information flow
2
4
6
4
0
4
s
Timeliness of diagnosis and treatment
Quality of patient experience (minimal
discomfort respectful etc )
2
4
6
1
3
4
s
Correctness of diagnosis and treatment
2
4
6
1
4
5
Serve Boston Healthcare System
Accessible Care
2
4
6
1
6
7
Clean, High Quality Facility
2
5
7
9
10
10
9
5
7
6
5
7
5
2
5
3
5
3
4
3
2
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 31
Stakeholder Value Comparison
Enterprise Value Delivery to Stakeholder
High
VA Leadership
Patients
Based on Discussion
Doctors
Community
Tax Payers
Universities & Residents
Politicians
Hospital Management
Based on X-Matrix
Patients
Partner Hospitals
Employees
Doctors
Hospital Management
Employees
Pharmacy
Supply Chain
VA Leadership
Finance
Volunteers
Tax Payers
Partner Hospitals
Homeless Shelters
Community
Supply Chain
Politicians
Volunteers
Pharmacy
Finance
Universities & Residents
Low
Stakeholder Relative Importance to Enterprise
High
Methodology
 Inferred Stakeholder Importance from Strategic Objects & Value Delivery from the
Key Processes
 Used weighting algorithm to calculate positions
 More research & data needed on weights, and to validate results.
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 32
Stakeholder Value Comparison
Enterprise Value Delivery to Stakeholder
High
VA Leadership
Patients
Based on Discussion
Doctors
Community
Tax Payers
Universities & Residents
Politicians
Hospital Management
Based on X-Matrix
Patients
Partner Hospitals
Employees
Doctors
Hospital Management
Employees
Pharmacy
Supply Chain
VA Leadership
Finance
Volunteers
Tax Payers
Partner Hospitals
Homeless Shelters
Community
Supply Chain
Politicians
Volunteers
Pharmacy
Finance
Universities & Residents
Low
Stakeholder Relative Importance to Enterprise
High
Methodology
 Inferred Stakeholder Importance from Strategic Objects & Value Delivery from the
Key Processes
 Used weighting algorithm to calculate positions
 More research & data needed on weights, and to validate results.
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 33
Veteran Affairs
Boston Mental Health
Enterprise Architecting
May 13, 2009
Team:
Oladapo Bakare
Jordan Peck
Orietta Verdugo
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 34
Current Architecture
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 35
Candidate Architectures
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 36
Candidate Architectures
Illness Based
Serious MI
Vocational
Sexual Abuse
Residential
Inpatient
Vocational
Outpatient TBI
Residential
Inpatient
Vocational
PTSD & SA
Outpatient
Residential
Pros:
•
•
Continuous care in a given category can be easily tracked and
traced
Flexible if new mental disorders, programs, or illnesses arise in the
future
Cons:
•
•
Many patients fall into more than one category
Wasted resources on programs that have low volume or excess
capacity
Patient Length of Stay
Vocational
Residential
Outpatient
Inpatient
Vocational
Outpatient
Residential
Inpatient
Outpatient
Short Term
Pros:
•
Homeless Prog.
Resources can be maximized through each department
Long Term
Urgent Care
Inpatient
Outpatient
PATH
RISE
REACH
LT Stay
Private Homes
Cons:

Unbalanced system with excess capacity in some units and
overflow in others

Patients currently transition between some or all of the programs

Metrics will be focused on local maximization rather than
focusing on optimal flow across the organization
http://lean.mit.edu
Intermittent
SAARP
WITRP
Programs
Homeless
CWP
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 37
Candidate Architectures
Psychology
Profession Expertise
Pros:
•
•
Allows medical staff to create optimal treatment plans by working within their
specialty
There is a direct connection with leadership team and employees
Cons:
•
•
Difficult to collaborate with other specialties
Supervisors will not be capable of treating specific illnesses
SMI & UC
Psychiatry
Inpatient
SMI & UC
Residential
Nursing
Inpatient
Vocational
Residential
Outpatient
SMI & UC
Administration
Vocational
Inpatient
Outpatient
Residential
SMI & UC
Vocational
Inpatient
Social Worker
Outpatient
Residential
SMI & UC
Vocational
Inpatient
Outpatient
Residential
Vocational
Outpatient
Area Based
Pros:
•
•
Community
CBOCs
Leadership oversight is more direct and site specific
Initiating change in each location is more manageable
Private Homes
Homeless Prog.
Outpatient
Cons:
•
•
Scalability of any one location is limited to capacity constraints
Quality of treatment programs may vary across locations
http://lean.mit.edu
Brockton
Urgent Care
Inpatient
Outpatient
Residential
SAARP
WITRP…
Jamaica Plain
Urgent Care
Inpatient
Outpatient
Residential
SAARP
WITRP…
West Roxbury
Urgent Care
Inpatient
Outpatient
Residential
SAARP
WITRP…
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 38
VA
BM
H
Design Parameters
Functional
Requirements
Maximize Veteran Quality of Life
Identify Patietns with Mental Illness
Treat Cause and Effect of Mental Illness
Integrate Patient Back into Community
Pa
ti
& ent
Co Id
m en
m tif
un ic
ity ati
Re on
Tr
lat
ea
io
tm
ns
en
tP
ro
gr
am
Pa
s
tie
nt
Re
-In
te
gr
at
io
n
Candidate Architectures
X
X
X
X
X
Axiomatic
Pros:
•
•
Director responsibilities are clear and aligned
Connection between leadership and treatment
professionals are more transparent
Cons:
•
•
Departmental imbalance due to program sizes and
patient needs
Requires significant re-organization of the enterprise
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 39
Architecture Evaluation
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 40
Architectures at a Glance
Illness Based
Short Term
Serious MI
Homeless Prog.
Vocational
Residential
Outpatient
Vocational
Sexual Abuse
Residential
Inpatient
Vocational
Outpatient TBI
Residential
Inpatient
Vocational
PTSD & SA
Outpatient
Residential
Current State
PATH
RISE
REACH
LT Stay
Private Homes
SAARP
WITRP
Private Homes
Homeless Prog.
Outpatient
Brockton
Intermittent
Programs
Homeless
CWP
Urgent Care
Inpatient
Outpatient
Residential
SAARP
WITRP…
Professional
Community
CBOCs
Long Term
Urgent Care
Inpatient
Outpatient
Inpatient
Vocational
Outpatient
Residential
Inpatient
Outpatient
http://lean.mit.edu
Area Based
LOS
Jamaica Plain
Urgent Care
Inpatient
Outpatient
Residential
SAARP
WITRP…
West Roxbury
Urgent Care
Inpatient
Outpatient
Residential
SAARP
WITRP…
Psychology
SMI & UC
Psychiatry
Inpatient
SMI & UC
Residential
Nursing
Inpatient
Vocational
Residential
Outpatient
SMI & UC
Administration
Vocational
Inpatient
Outpatient
Residential
SMI & UC
Vocational
Inpatient
Social Worker
Outpatient
Residential
SMI & UC
Vocational
Inpatient
Outpatient
Residential
Vocational
Outpatient
Axiomatic
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 41
Concept Scoring Matrix
Architecture Evaluation
Enterprise Architecture Concepts
Selection Criteria
Agility
Scalability
Quality
Accessibility
Standards Compliance
Customizability
Demonstrability
Safety
Responsiveness
Serviceability
Survivability
Weights
9.00%
3.25%
15.00%
9.00%
3.25%
15.00%
15.00%
3.25%
15.00%
9.00%
3.25%
Total Score
Rank
Continue
Current State
Weighted
Rating
Score
3
0.27
3
0.10
3
0.45
3
0.27
3
0.10
3
0.45
3
0.45
3
0.10
3
0.45
3
0.27
3
0.10
3.00
Expertise
Weighted
Rating
Score
1
0.09
2
0.07
3
0.45
3
0.27
3
0.10
2
0.30
1
0.15
2
0.07
1
0.15
4
0.36
5
0.16
2.16
Used CurrentLOSWeighted
Rating
Score
State as
2
0.18
benchmark
2
0.07
2
3
3
2
3
3
2
3
2
0.30
0.27
0.10
0.30
0.45
0.10
0.30
0.27
0.07
2.40
Illness
Weighted
Rating
Score
1
0.09
2
0.07
4
0.60
3
0.27
3
0.10
2
0.30
3
0.45
4
0.13
2
0.30
3
0.27
1
0.03
2.61
Area
Weighted
Rating
Score
3
0.27
1
0.03
2
0.30
4
0.36
3
0.10
1
0.15
2
0.30
3
0.10
3
0.45
1
0.09
4
0.13
2.28
Axiom
Weighted
Rating
Score
5
0.45
3
0.10
4
0.60
3
0.27
3
0.10
5
0.75
4
0.60
4
0.13
4
0.60
3
0.27
3
0.10
3.96
2
6
4
3
5
1
No
No
No
No
No
Develop
1-5 Success Ranking for Architectures
5=high, 1 = low
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 42
Proposed Architecture
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 43
Transformation Plan
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 44
Matrix of Change
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 45
PhD Focus
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 46
Predictability = Control
Health Care Professionals are starting to recognize predictability
Wednesday
Spread of Time in ER (Mean+/-Standard Deviation)
T15
T16
T17
T18
T19
T20
T21
T22
T23
T24
W1
W2
W3
W4
W5
W6
W7
W8
W9
W10
W11
W12
W13
W14
W15
W16
W17
W18
W19
W20
W21
W22
W23
W24
T1
T2
T3
T4
T5
350
+σ
300
Mean
250
-σ
200
150
100
50
0
ESI 1
1
2
3
ESI 2
4
ESI 3
ESI 4
ESI 5
5
•Emergency Severity Index (ESI)—a five-level emergency department triage algorithm that provides clinically relevant
stratification of patients into five groups from 1 (most urgent) to 5 (least urgent) on the basis of acuity and resource needs.
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 47
Simulation and Modeling
How can we model Control Options and Interventions
How do the people fit in?
How well can solutions cross between
hospitals?
VA Boston, MA
VA Togus, ME
VA Manchester, NH
Source: www.VA.gov
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 48
Agenda
•
Research Motivation and LAI Alignment
•
LAI Healthcare Research Pipeline
•
Overview of Research Projects
• Jorge Oliveira
• Jordan Peck
• NEWDIGS (Debbie Nightingale/Judy Maro)
• PTSD (Debbie Nightingale)
• DNA Sequencing
•
Final Comments
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 49
CBI’s NEW Drug Development ParadIGmS
(NEWDIGS)
Mission – Objective - Measures
Mission:
Objective:
Measures:
To improve
therapeutic product
innovation in
healthcare.
Involving all
stakeholders,
catalyze true
transformational
change across the
product development
spectrum globally.
Reduced cost and
time-to-market for
genuinely innovative
products that
significantly improve
health and provide
enhanced value for
healthcare.
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology Page 51
Consortium of Stakeholders
Biomarker
s
Consortiu
m
FDA & Other
HHS Agencies
NGOs
MIT Center
for
Biomedical
Innovation
BIG
Health
Providers
Duke Clinical
Trial
Transformational
Program
Patient
Advocacy
Payers
Diagnostics
Systems
Integrators
Biotechs &
Pharmas
Sentinel
Initiative
C-Path
Critical
Path
Initiative
s
52
Core Issues - Driving Forces
•
•
•
Changes in definition of “product”
•
•
•
Primacy of investor optics
Changes in definition of “stakeholder/customer” needs
Changes in appreciation of the complexity of the science &
the multimodal nature of the solution
Changes in both internal and public perception of risk
Conservative culture of industry and antique assumptions –
e.g., competition & infrastructure
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology Page 53
Key Organizational Attributes
•
Delivers dramatically increased value over the current
approach (faster, more efficient, reduced resource
expenditure without compromise in outcomes).
•
Is integrated with an outcomes-based reimbursement
environment, finding solutions focused on patient outcomes
driven by patient and payor value as well as
scientific/medical community value
•
•
Understands market and customer(s) health needs
Focuses on integrated healthcare solutions and is not tied to
developing one particular product (i.e., responsive to market
need, flexible, adaptive)
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology Page 54
Key Organizational Attributes
•
Designs solutions that intervene earlier in the disease
continuum including prevention.
•
Lean and highly collaborative with all stakeholders from
across the entire value chain.
•
Informed by knowledge generated internally and externally
(through pre-competitive, cross-stakeholder data
sharing/collaboration) and processes that enable rapid-cycle
learning (e.g., Learning Healthcare System).
•
Has relationships with best-in-class providers of solution
components (industry, academia, non-profits), and
collaborates effectively with them to develop solutions.
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology Page 55
10-15 Year Vision (?): NEWDIGS Innovation Spheres
1) Discovering &
Developing
New Products
(current focus of
NEWDIGS)
2) Enhancing the Value
of Existing Products
(eg, personalized
medicine, drug combos, ?
biosimilars, etc.)
3) Optimizing
Care Delivery
Processes
(e.g., integrating
personalized
medicine into care
delivery; pt.
“compliance”)
56
Proposed Initial Workstreams
Workstreams
1)
2)
3)
4)
5)
New Paradigms: Modeling, Simulation, & Decision Support
Data, Evidence, and Decision-making
Regulatory Policy Design
NEWDIGS
Organizational Design (? hold for now)
Other TBD….
#1
New Paradigms:
Modeling,
Simulation,
Decision-Support
Demonstration
Projects
(TBD)
#2
#3
Process
Knowledge
IT
• What decisions must be made, when, and by whom?
• What evidence is required to inform these decisions?
• What data is required to generate the necessary evidence?
• What can we do in NEWDIGS to optimize all of the above?
Policy &
External
Factors
Regulatory
policy as
enabler of
scientifically
& ethically
sound
innovation
#4
Products &
Services
Organization
Organizational
Design –
NEWDIGS and
the broader
Learning
Healthcare
System
57
Agenda
•
Research Motivation and LAI Alignment
•
LAI Healthcare Research Pipeline
•
Overview of Research Projects
• Jorge Oliveira
• Jordan Peck
• NEWDIGS (Debbie Nightingale/Judy Maro)
• PTSD (Debbie Nightingale)
• DNA Sequencing
•
Final Comments
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 58
Systems based approach to PTSD
Warrior - Centric
Recruitment
Training
Deployment
Re-integration** Re-Deployment**
Final Integration to Civilian Population
Interface with VA
Lifecycle of PTSD in the Military
Phase I - Current State Analysis: Descriptive Research designed to understand the system
• Model each phase of the lifecycle (“system”) of PTSD and the interfaces between each phase
• Multi-scale: Top down/ Bottom up
• Outcome: Define Problem
Phase II - Model Creation and Validation: Descriptive Research designed to represent the system
• Drill down into identified gaps to develop possible solutions
• Outcome: Recommendations
Phase III - Implementation
** Will take into account multiple deployments.
http://lean.mit.edu
COLLABORATIVE INITIATIVES AT MIT
@
MASSACHUSETTS
© 2009 Massachusetts Institute of Technology
D. Nightingale,INSTITUTE
J. Oliveira,OF
andTECHNOLOGY
J. Peck 10/14/09 - 59
Motivation for Application to PTSD
•
Rising suicide rates among returning veterans and the
potential PTSD precursors
•
PTSD impact on health and well-being of
servicemembers and their families
•
PTSD impact on health services utilization within the
military and in affected communities
•
PTSD impact on national priorities for DoD
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 60
Potential Outputs
• Generate models as tools so that
policymakers can:
• Develop Insight on PTSD’s systemic impacts
• Identify Missed Opportunities and Misalignment among
•
•
•
current PTSD-related functions
Inform Resource Allocation for PTSD-related functions
Direct R&D Funding to Needed Areas
Reshape PTSD-related metrics to Monitor System
Performance
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 61
Starting Points for Research
•
•
•
•
•
•
Resource Allocation among Functions
Capacity Utilization and Demand Modeling for
Services
At-Risk Subpopulations
Active v. Reserve v. Guard Health Dynamics on
Return
Effects of Changing Suicide Policies
Effects on Family and Community
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 62
62
Agenda
•
Research Motivation and LAI Alignment
•
LAI Healthcare Research Pipeline
•
Overview of Research Projects
• Jorge Oliveira
• Jordan Peck
• NEWDIGS (Debbie Nightingale/Judy Maro)
• PTSD (Debbie Nightingale)
• DNA Sequencing (Rob Nicol – ESD/Broad Institute)
•
Final Comments
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 63
Motivation / Problem
> Antibiotic Resistance Surveillance: Key Healthcare Problem
–
–
–
–
Rapidly increasing resistance
Few effective antibiotics remain
Limited system level surveillance
Process improvement difficult
> Complex Healthcare Processes
–
–
–
–
Source: CDC; MRSA=methicillin-resistant Staphylococcus aureus; VRE=Vancomycinresistant enteroccoci; FQRP=Fluoroquinolone-resistant Pseudomonas aeruginosa
Large number of tasks and rapidly changing technology
Numerous disconnected stakeholders
Vast technical design space
Highly distributed information (tacit and explicit)
> Severe Health and Cost Impacts
– 2 Million hospital acquired infections per year
– $5 Billion (est.) and over 90,000 deaths per year
(source: IDSA)
© 2009 Robert Nicol, Engineering Systems Division, Massachusetts Institute of Technology
Key Questions
> How can the true system level
complexity of healthcare processes
be modeled and measured?
> How does this system level process
model and complexity measures
work on a real world healthcare
process design and implementation
effort?
> How does process complexity
impact change and adoption in
healthcare?
© 2009 Robert Nicol, Engineering Systems Division, Massachusetts Institute of Technology
Contributions
> Novel Network Based Process Representation and
Complexity Analysis Methodology (model)
> Novel Theory for Process Innovation Adoption as a
Function of Process Complexity (model observations)
> First Specification of a Whole Genome Clinical Microbiology
Process for MRSA Surveillance (test case for model)
> First Operational Demonstration of a Whole Genome
Clinical Microbiology Process for MRSA Surveillance
(test case for model and complexity measures)
> First Whole Genome MRSA Diversity Study
(real biological results showing policy change needed)
© 2009 Robert Nicol, Engineering Systems Division, Massachusetts Institute of Technology
Contributions (Significant Biology Too…)
MRSA Surveillance Process designed and implemented as
part of thesis yielded significant insight into MRSA biology
which in turn suggests system policy changes needed
Reference (should all be the same as this)
Multiple Genome Alignment of BWH Samples
Compared to Reference at the Top
>50 Genomes Sequenced
(<15 existed previously)
> All Supposed to be identical based on
current hospital diagnostics
> Significantly different! (look at length)
> Highlights need for surveillance and
policy changes
© 2009 Robert Nicol, Engineering Systems Division, Massachusetts Institute of Technology
Agenda
•
Research Motivation and LAI Alignment
•
LAI Healthcare Research Pipeline
•
Overview of Research Projects
•
Final Comments
http://lean.mit.edu
© 2009 Massachusetts Institute of Technology D. Nightingale, J. Oliveira, and J. Peck 10/14/09 - 68