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Complexity, Reliability and Their Roles in
Healthcare Delivery Today
Peter Fine
President and CEO
Banner Health
Discussion Agenda
• Challenges and Opportunities For Healthcare Redesign
• Evolution of Health Care Delivery in Modern Era
• Evolution of Financing Health Care in US
• Banner’s Organizational Design in Response
• Some Clinical Improvement Results
A Summary:
Challenges and Opportunities
• Challenges
– Financial – “The belief in waste”
– Consumer – “Help me navigate” and “It’s my money now”
– New Complexities – “Knowing what to do is no longer enough” • The new role for the science of reliability
– The Anchor of our Past
– The Threat to the Professional • “Doctored: The Disillusionment of an American Physician” - Sandeep Jauhar
• Opportunities
– The Force of the Market
– Disruptive Competition
– A New Emphasis on Clinical Knowledge and “Managing Health”
Three Phases of Clinical Delivery
in the Modern Era*
1. Understanding and Classifying Disease
2. Defining Treatments
3. Designing Care Delivery
* David Cutler, Harvard Health Economist
I. “Classifying Disease”
1900
First issue of the “International
Classification of Diseases”
• “ICD-1”
• Causes of death (191)
Residential Medical Office, Otego, NY
1900
Advent of truly effective therapies:
• Vaccines for childhood
illnesses including polio
• Significant use of penicillin
• New drugs for glaucoma,
arthritis
• First organ transplant
II. “Defining Treatments”
1950
Colorado physician, Life Magazine, 1948
III. “Designing Care Delivery”
2000
A Response to:
– - Q:
– - R
– - S
– - T
III. “Designing Care Delivery”
2000
A Response to:
– - Q: Quality (and Reliability), the Boeing Story
– - R
– - S
– - T
“Reliability”
Isn’t 99% accuracy pretty good?
“If we had to live with 99.9% (10-3) , we would have:
• 2 unsafe plane landings per day at O’Hare
• 16,000 pieces of mail lost every hour
• 32,000 bank checks deducted from the wrong account every hour”
W.E. Deming
JAMA Vol 272 (23), 21 Dec. 1994, 1851-57
The “Human” Role
• What we do well:
– Judgment
– Prioritization
– Empathy
• What we do not so well:
– Vigilance
– Overcoming biases/habits/confidence mismatches
– Simultaneous multiples
Is knowledge sufficient?
“Fallibility is part of the human condition”
“We can’t change the human condition”
“We can change the conditions under which people work”
James Reason, author of “Human Error”
Strategies used to improve reliability in health care: – System Design:
• Automation, Decision support
• Adoption of evidence/consensus based practices
• Consistent processes, “teams” of care
• Address human factors with Bundling, Redundant design
– A Culture that encourages “Making safe choices”
III. “Designing Care Delivery”
2000
A Response to:
– - Q: Quality (and Reliability), the Boeing Story
– - R: Retail (New Expectations)
– - S: Safety (The Hidden Incidents)
– - T: Transforming business and service models
Three “Phases” of
Financing Healthcare
1960’s – 70’s: “Insured Care”
• Growth of Commercial Insurance • Medicare 1965 • The notion of “cost plus” and “reimbursement” • Cost Curve:
– % GDP in 1960: 5.3% – % GDP in 1970: 7.2%
1980’s – 90’s: “Managed Care”
• National Insurance Companies • HMO Legislation 1974 • Blue Cross and Blue Shield Merger 1982 • Product Innovation: HMO, PPO, POS • Case Rate, Diagnosis Related Group Payments • Cost Curve:
– % GDP in 1980: 9.1% – % GDP in 1990: 12.2%
2000’s - : “Accountable Care”
• FFS P4P, Bundling, Provider Risk, Accountable Care Org’s • Outcome based payment penalties • Growing concerns around clinical issues: patient safety,
reliability, geographic variation • Cost Curve:
– % GDP in 2000: 13.8% – % GDP in 2010: 16.4%
“Sales” “Engineering” “Manufacturing”
Corporate Support Services
17
Integrated Accountable Care
Delivery
System
Care Mgmt/Design Banner
Health Network
18
“Sales” “Engineering” “Manufacturing”
System Operations Team
Integrated
Delivery Team
Clinical Product
Design Team
Strategic
Growth Team
Inte
gra
ted A
ccounta
ble
Care
Ente
rpri
se
Banner Health Approach
Organizational Structures which:
• Honor the contributions of clinician experts
• Leverage the “Operating Company Model”
• Take advantage of the Board which is “on-board”
• Recruit deep physician talent for leadership
• Train clinicians in leading change
• Encourage the multi-disciplinary approach
• Engage engineering expertise
• Deploy technology to simplify care
“Engineering” New Models
• Research Practices
• Reach Consensus on requirements
Define
• Describe reliable workflow and roles
• Develop tools
Design • Communicate
and train
• Address issues
• Monitor
Implement
Clinical Consensus Groups
CRITICAL
CARE
Nidhi Nikhanj
Gary Foster
WOMENS
HEALTH
Michael Urig
Ellen Anthony
CV SURGERY
Michael
Maxwell
Marianne
LaFleur
PEDIATRICS
Bill Schneider
Sandra Marken
BEHAVIORAL
HEALTH
Gagan Singh
Nancy Sylvester
PHARMACY &
THERA-
PEUTICS
Joe Lozon
Nathan
Spence
CARE MANAGEMENT COUNCIL
ED
David Cohen
Dan Lingle
CARDIOLOGY
Paul Hurst
Dana Lauer
ANESTHESIA
Josh
Bloomstone
Kelly Kiefer
HOSPITAL
MEDICINE
Cheryl O’Malley
Terri Paulus
NEURO-
SCIENCES
Norm Wang
Al Wildman
MEDICAL
IMAGING
Threasa Frouge
Erica Dorward
PRIMARY
CARE
Mary Ellen
Dirlam
Heidi Costello
INFECTIOUS
DISEASE
Edwin Yu
Joan Ivaska
ORTHO
David
Jacofsky
Young An
NEPHROLOGY
Dharminder
Marwah
Debbie Kohm
ONCOLOGY
Daniel
Chamberlain
Kathy Altergott
LONG TERM
CARE
Natalya
Faynboym
Kelly Johnson
SURGERY
Jon King
Nancy
Adamson
PULMONARY
Rajeev Saggar
Chuck Ramirez
NICU/Newborn
Greg Martin
Kathleen
Walker
PALLIATIVE
CARE
M Joseph
Kristine
Salmon
Implementation Science *
4 Groups of Variables which Influence Adoption
1. The External Environment (i.e. Payment changes)
2. Organizational Structure (i.e. an IDS)
3. The Character of the Change (i.e. Power of the Evidence)
4. The Processes Used (i.e. Design, Decision Making, Leader
accountabilities, etc.)
Fisher ES, Shortell SM, Savitz LA. Implementation Science – A Potential Catalyst for
Delivery System Reform. JAMA. 2016;315(4): 339-340.
Some Improvement
Results
0
100
200
300
400
500
600
700
800
900Q
1 2
010
Q2 2
010
Q3 2
010
Q4 2
010
Q1 2
011
Q2
20
11
Q3 2
011
Q4 2
011
Q1 2
012
Q2 2
012
Q3 2
012
Q4 2
012
Q1 2
013
Q2 2
013
Q3 2
013
Q4 2
013
Q1 2
014
Q2 2
014
Q3 2
014
Q4 2
014
Q1 2
015
Q2 2
015
Q3 2
015
Q4 2
015
--OB Clinical Practice
adopted on 11/18/2010
--$930K in Savings annually
Business Intelligence, Accessed 4/22/2015
Data: Women’s Health Data Cube
Adhesion Barrier in OB
Josh Noble (CPA), 04/04/2016
Data: Quality Advisor, TSI
0%
10%
20%
30%
40%
50%
60%
70%
80%1
Q 2
00
8
2Q
20
08
3Q
20
08
4Q
20
08
1Q
20
09
2Q
20
09
3Q
20
09
4Q
20
09
1Q
20
10
2Q
20
10
3Q
20
10
4Q
20
10
1Q
20
11
2Q
20
11
3Q
20
11
4Q
20
11
1Q
20
12
2Q
20
12
3Q
20
12
4Q
20
12
1Q
2013
2Q
20
13
3Q
20
13
4Q
20
13
1Q
20
14
2Q
2014
3Q
20
14
4Q
20
14
1Q
20
15
2Q
20
15
% CT Scans % Ultrasounds
% of Peds Appendicitis Patients Who Received an Abdominal/Pelvic CT Scan or Ultrasound
63.6%
39.9%
7.4%
40.8%
9.6%
14.8% 15.5%
68.9%
54.1%
47.3% 51.0%
36.5% 34.4%
43.8%
34.9%
53.0%
2008 - 2015 CT Scan vs Ultrasound Use
74%
68%
71% 69%
75% 74%
71%
62%
72%
68%
65%
60%
48%
50%
42%
37%
51%
44%
49% 49% 48% 48%
44%
50%
54%
44%
52%
41%
30%
35%
40%
45%
50%
55%
60%
65%
70%
75%
80%Q
1 2
00
9
Q2
20
09
Q3
20
09
Q4
20
09
Q1
20
10
Q2
20
10
Q3
20
10
Q4
20
10
Q1
20
11
Q2
20
11
Q3
20
11
Q4
20
11
Q1
20
12
Q2
20
12
Q3
20
12
Q4
20
12
Q1
20
13
Q2
20
13
Q3
20
13
Q4
20
13
Q4
20
14
Q2
20
14
Q3
20
14
Q4
20
14
Q1
20
15
Q2
20
15
Q3
20
15
Q4
20
15
Peds Asthma Inpatient Chest X-Ray
Josh Noble (CPA), 3/4/2016
Data: Quality Advisor, TSI
Reduce Variation in Blood Utilization
Orthopedic: Hip/Knee
16.6%
12.5%
8.4% 7.8%
7.8% 8.0%
6.9% 6.7%
3.2% 0.9%
1.6% 0.60% 0.60%
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
1Q
20
13
2Q
20
13
3Q
20
13
4Q
20
13
1Q
20
14
2Q
20
14
3Q
20
14
4Q
20
14
1Q
20
15
2Q
20
15
3Q
20
15
4Q
20
15
1Q
20
16
Clinical Performance Analytics, Accessed 05/17/2016
Mature Initiatives Scorecard
Central Line Associated Blood Stream Infections (CLABSI)
2.35
1.78
1.63
2.09
1.19
1.86
1.52
1.13
0.86
0.66
1.10
0.60
1.35
0.93
0.19
1.00
0.88
0.94
0.93
0.95 0.95
0.41
0.61
0.51 0.51
0.72
1.46
0.84
0.0
0.5
1.0
1.5
2.0
2.5
1Q
,20
09
2Q
,20
09
3Q
,20
09
4Q
,20
09
1Q
,20
10
2Q
,20
10
3Q
,20
10
4Q
,20
10
1Q
,20
11
2Q
,20
11
3Q
,20
11
4Q
,20
11
1Q
,20
12
2Q
,20
12
3Q
,20
12
4Q
,20
12
1Q
,20
13
2Q
,20
13
3Q
,20
13
4Q
,20
13
1Q
,20
14
2Q
,20
14
3Q
,20
14
4Q
,20
14
1Q
, 20
15
2Q
, 20
15
3Q
,20
15
4Q
,20
15
ICU Central Line Infections per 1,000
Source: Acute Care Board Report, 5/17/2016
Early Elective Deliveries
21.8%
13.5%
5.2% 5.5%
2.8% 3.1%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
2010 2011 2012 2013 2014 2015
Banner Health System Leapfrog Data: Elective Deliveries < 39 weeks
System Leapfrog Target
Clinical Performance Analytics, Accessed 11/10/2015
Leapfrog Data
76% 77% 77%
79%
82%
84% 85%
87% 87% 86%
88% 88% 89%
89% 88%
89% 89%
65%
70%
75%
80%
85%
90%
95%
4Q
20
11
1Q
20
12
2Q
2012
3Q
20
12
4Q
20
12
1Q
2013
2Q
20
13
3Q
20
13
4Q
20
13
1Q
20
14
2Q
20
14
3Q
20
14
4Q
20
14
1Q
20
15
2Q
20
15
3Q
20
15
4Q
20
15
Intensive Care Patients
Research
indicates >60%
as positive
Clinical Practice:
Sepsis, Delirium
Identification,
Prevention and
Treatment
Clinical Performance Analytics, Accessed 01/15/2016
Critical Care Data Cube
Delirium and Coma Free Days
81.3 80.5
79.4
76.3
65.4 61.7
57.5
62.5
59.8 60.6
53.6
62.2 61.3 60.8 58.1 58.9 58.4
55.9
0
10
20
30
40
50
60
70
80
903Q
2011
4Q
2011
1Q
2012
2Q
2012
3Q
2012
4Q
2012
1Q
2013
2Q
2013
3Q
2013
4Q
2013
1Q
20
14
2Q
2014
3Q
2014
4Q
2014
1Q
2015
2Q
2015
3Q
2015
4Q
2015
Intensive Care Patients
> 20 hours
Improvement
Clinical Practice:
Sepsis, Delirium
Identification, Prevention
and Treatment
Clinical Cost
Avoidance of
$22 Million
Clinical Performance Analytics, Accessed 01/06/2016
Critical Care Data Cube
Length of Stay in Hours at ICU Level of Care
0.87
0.81
0.96
0.88 0.85 0.85
0.76
0.62 0.64
0.6 0.59
0.67 0.66 0.69
0.62 0.63 0.65
0.74
0.65 0.67
0.73 0.71
0.76
0.67
0
0.2
0.4
0.6
0.8
1
4Q
2009
1Q
2010
2Q
2010
3Q
2010
4Q
2010
1Q
2011
2Q
2011
3Q
2011
4Q
2011
1Q
2012
2Q
2012
3Q
2012
4Q
2012
1Q
2013
2Q
2013
3Q
20
13
4Q
2013
1Q
2014
2Q
2014
3Q
2014
4Q
2014
1Q
2015
2Q
2015
3Q
2015
Mortality Observed/Expected
All ICU Acute Care Patients
Clinical Practice:
Severe Sepsis
Delirium Intervention
Mortality outcomes are
>40% better than
predicted
Clinical Performance Analytics, Accessed 05/19/2016
Philips eSearch data
1.0 = Performance as Expected
Skilled Nursing Days Reduction Per 1000 Members
55
60
65
70
75
80
851
/1/2
01
5
2/1
/20
15
3/1
/20
15
4/1
/20
15
5/1
/20
15
6/1
/20
15
7/1
/20
15
8/1
/20
15
9/1
/20
15
10
/1/2
015
11
/1/2
015
12
/1/2
015
1/1
/20
16
Clinical Performance Analytics,
BHN Datamart : Michael Parris
BHN Inpatient Days Reduction Per 1000 Members
175
195
215
235
255
275
295
1/1
/20
15
2/1
/20
15
3/1
/20
15
4/1
/20
15
5/1
/20
15
6/1
/20
15
7/1
/20
15
8/1
/20
15
9/1
/20
15
10
/1/2
01
5
11
/1/2
01
5
12
/1/2
01
5
1/1
/20
16
BCBS AZ ADVANTAGE PIONEER ACO UNITED M/A
Pioneer ACO Quality Performance
• 1st in cost savings total in the country (!) at $29M,
• 3rd in the country in savings per beneficiary ($550)
• 2015 Performance is Projected
• Note: Our membership is one of the largest in US (>52k) and our physician network is the 3rd largest
62.2%
81.2%
87.6% 89.7%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2012 2013 2014 2015*
Overall Quality Score – Maximum 100 per CMS
MRSA Bacteremia Rate Reduction with Bathing Redesign
Infection Prevention
5/10/2016
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14201
4M
01
201
4M
02
20
14
M0
3
201
4M
04
201
4M
05
201
4M
06
201
4M
07
201
4M
08
201
4M
09
201
4M
10
201
4M
11
201
4M
12
201
5M
01
201
5M
02
201
5M
03
20
15
M0
4
201
5M
05
201
5M
06
201
5M
07
201
5M
08
201
5M
09
201
5M
10
201
5M
11
201
5M
12
Rate
per
1000 p
atient
days
MRSA Bacteremia Mean Target
Daily CHG
bathing in
ICUs
Theresa Lake, CPA, 8/24/2015
Cerner, TSI
0.0
20.0
40.0
60.0
80.0
100.0
120.02
Q 2
01
1
3Q
20
11
4Q
20
11
1Q
20
12
2Q
20
12
3Q
20
12
4Q
20
12
1Q
20
13
2Q
20
13
3Q
20
13
4Q
20
13
1Q
20
14
2Q
20
14
3Q
20
14
4Q
20
14
1Q
20
15
2Q
20
15
3Q
20
15
4Q
20
15
1Q
20
16
2Q
20
16
Primary Stroke Minutes to Intravenous Thrombolytic Therapy Times - Median
30%
40%
50%
60%
70%
80%
90%
100%
Jul-
11
Au
g-1
1
Sep
-11
Oct
-11
No
v-1
1
Dec
-11
Jan
-12
Feb
-12
Mar
-12
Ap
r-1
2
May
-12
Jun
-12
Jul-
12
Au
g-1
2
Sep
-12
Oct
-12
No
v-1
2
Dec
-12
Jan
-13
Feb
-13
Mar
-13
Ap
r-1
3
May
-13
Jun
-13
Jul-
13
Au
g-1
3
Sep
-13
Oct
-13
No
v-1
3
Dec
-13
% o
f TK
A C
ase
s A
chie
ved
Total Knee Arthroplasty Care Composite Catheter Avoidance and Day 0 Ambulation
Composite Average LCL UCLGuillermo Mendez, CPA, 8/24/2015
Cerner, MS4
Improvement
Composite Score 49.8%
30-Day Readmission 24.3%
Complications 18.5%
Length of Stay 7.5%