Session #7 – Organizing For Analytics Success
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Transcript of Session #7 – Organizing For Analytics Success
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Session #7 – Organizing For Analytics Success
Current Session
Submit a Question
Poll Question
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Hotel Wi-Fi• HASummit14• PW: analytics
App Questions?• 3 app helpers• Raise hand with
mobile device• Walk to back
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Holly RimmaschChief Clinical Officer, Health Catalyst
Session #7 Organizing for Analytics Success
Ms. Holly Rimmasch is Chief Clinical Officer at Health Catalyst. Prior to joining Health Catalyst, Ms. Rimmasch was an Assistant Vice President at Intermountain Healthcare and was integral in promoting integration of Clinical Operations across hospitals, ambulatory settings and managed care plans. Holly has spent the last 17 years dedicated to improving clinical care including implementation of operational best practices. Ms. Rimmasch holds a Master of Science in Adult Physiology from the University of Utah and a Bachelor of Science in Nursing from Brigham Young University.
Mr. Barlow is a co-founder of Health Catalyst. He oversees all technical client operations. Mr. Barlow is a founding member and former chair of the Healthcare Data Warehousing Association. He began his career in healthcare over 22 years ago at Intermountain Healthcare and acted as a member of the team that led Intermountain’s nationally recognized improvements in quality care and reductions in cost. Mr. Barlow holds a BS from the University of Utah in health education and promotion.
Steve Barlow Co-Founder and Senior Vice President of Client Operations, Health Catalyst
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Where Do We Start?
Cumulative %
% of Total Resources Consumed for each clinical work process
50%
7 CPFs Number of Care Process Families (e.g., ischemic heart disease, pregnancy, bowel disorders, spine, heart failure)
21 CPFs
80%
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Effective Approach to improvement: Focus on “Better Care”
Excellent OutcomesPoor Outcomes
# of Cases
Current Condition
• Significant Volume• Significant Variation
Excellent Outcomes
# of Cases
Option 2: Identify Best Practice “Narrow the curve and shift it to the right”Strategy• Identify evidenced based “Shared Baseline”• Focus improvement effort on reducing
variation by following the “Shared Baseline”• Often those performing the best make the
greatest improvements
Mean
Focus on Best Practice Care Process
Model
Poor Outcomes
1 box = 100 cases in a year
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Internal Variation vs Resource ConsumptionY
- Axi
s =
Int
ern
al V
aria
tion
in R
esou
rces
Con
sum
ed
Bubble Size = Resources Consumed
Bubble Color = Clinical DomainX Axis = Resources Consumed
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Three Systems of Care Delivery Overview
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Analytic System
Content System
Deployment System
Evidence gathering & evaluating
Knowledge assets (e.g. Order Sets)
Starter sets
Value stream maps
Patient safety protocols
Standard “Knowledge” Work
Team Structures
Roles
Fingerprinting
Implementation
Standard “Organizational” Work
Data driven prioritization
Calculations
Definitions
Enterprise Data Warehouse
Data visualization
Standard “Measurement” Work
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Analytic System Core Activities
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Analytic System
Content System
Deployment System
Unlocking Data to Drive Measurements
Automating the Broad Distribution of
Information
Discovering Patterns in Data
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Strong Analytic System
Non value-add Value-add
Understanding the question
Hunting for data
Interpreting dataData distribution
Gather, compiling or running
Weak Analytic System
Strong Analytic SystemThe majority of time is spent analyzing and interpreting data
Understanding the questionHunting for data
Interpreting data
Data distribution
Gather, compiling or running
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Less Transformation
Provider
Patient
Bad Debt
Diagnosis Procedure
Facility
EncounterCost
Charge
Employee
Survey
House Keeping
Catha Lab
Provider
Census
Time Keeping
More Transformation Enforced Referential Integrity
Enterprise Data Model (Technology Vendors)
FINANCIAL SOURCES
ADMINISTRATIVE SOURCES
EMR SOURCES
DEPARTMENTAL SOURCES
Pt. SATISFACTIONSOURCES
EDW
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EMR SOURCES
Oncology
DiabetesHeart
Failure
Regulatory
Pregnancy Asthma
Labor Productivity
Revenue Cycle
Census
Pt. SATISFACTIONSOURCES
DEPARTMENTAL SOURCES
FINANCIAL SOURCES
ADMINISTRATIVE SOURCES
Redundant Data Extracts
Independent Data Marts (Healthcare Point Solutions, EMRs)
EDW
Less TransformationMore Transformation
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Metadata (EDW Atlas), Security and Auditing
Diabetes
Sepsis
Readmissions
Common, linkable vocabulary
FinancialSource Marts
AdministrativeSource Marts
DepartmentalSource Marts
EMR Source Marts
Patient Satisfaction Source Mart
FINANCIAL SOURCES
ADMINISTRATIVE SOURCES
EMR SOURCEs
DEPARTMENTAL SOURCES
Pt. SATISFACTIONSOURCES
Adaptive Data Model
Less TransformationMore Transformation
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Analytic System Exercise
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The Enterprise Shopping Model
Produce
Meat
Dairy
Dry Goods
__ Apples__ Pears__ Tomatoes__ Carrots
__ Beef__ Ham__ Chicken__ Pork
__ Milk __ Eggs__ Cheese__ Cream
__ Pasta__ Flour__ Sugar__ Soup
__ Celery__ Banana__ Melon__ Grapes
__ Turkey__ Sausage
__ Lamb__ Bacon
__ 2% Milk __ Half & Half__ Yogurt__ Margarine
__ Baking soda__ Rice__ Beans__ B. Sugar
E n t e r p r i s e S h o p p i n g M o d e l
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Apples
Tomato Soup
Flour
Milk
Turkey
Lettuce
Sugar
Beans
Hot dogs
Banana
Noodles
Yogurt
Your Shopping List
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Get eggs
Buy flowers
Get tires rotated
Pick up dry cleaning
Additional Items
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Less Transformation
Provider
Patient
Bad Debt
Diagnosis Procedure
Facility
EncounterCost
Charge
Employee
Survey
House Keeping
Cath Lab
Provider
Census
Time Keeping
More Transformation Enforced Referential Integrity
Enterprise Data Model (Technology Vendors)
FINANCIAL SOURCES
ADMINISTRATIVE SOURCES
EMR SOURCES
DEPARTMENTAL SOURCES
Pt. SATISFACTIONSOURCES
EDW
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Using a Independent Mart Shopping Model
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https://dl.dropboxusercontent.com/u/355034/CATALYST%2090%20Second.mp4.zip
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The Independent Mart Shopping Model
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Dairy Dry Goods
__ ½ cup of butter__ ½ cup milk__ 2 eggs
__ 1 cup white sugar__ 1 ½ cups all-purpose flour__ 2 teaspoons vanilla extract__ 1 ¾ teaspoon baking powder
Independent Mart Shopping Model
Cake
Trip #2 to the Store
How many recipes do you need to make?
Trip #1 to the Store
Dairy Dry Goods
__ 4 eggs __ 2 c shortening
__ 1 c sugar__ 2 c brown sugar__ 2 t baking soda__ 2 t vanilla__ 1 t salt__ 4-5 c all-purpose flour __ 4 cups chocolate chips
Independent Mart Shopping Model
Chocolate Chip Cookies
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EMR SOURCES
Oncology
DiabetesHeart
Failure
Regulatory
Pregnancy Asthma
Labor Productivity
Revenue Cycle
Census
Pt. SATISFACTIONSOURCES
DEPARTMENTAL SOURCES
FINANCIAL SOURCES
ADMINISTRATIVE SOURCES
Redundant Data Extracts
Independent Data Marts (Healthcare Point Solutions, EMRs)
EDW
Less TransformationMore Transformation
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The Adaptive Shopping Model
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A d a p t i v e S h o p p i n g M o d e l
__ ________________________ ________________________ ________________________ ________________________ ________________________ ________________________ ________________________ ________________________ ________________________ ________________________ ______________________
__ ________________________ ________________________ ________________________ ________________________ ________________________ ________________________ ________________________ ________________________ ________________________ ________________________ ______________________
Store: __________________________________________________
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Shopping List Revisited
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Additional Items Get eggs
Buy flowers
Get tires rotated
Pick up dry cleaning
Once you are home, can you make these recipes?
Cake: 1 cup white sugar 1 ½ cups all-purpose flour 2 teaspoons vanilla extract 1 ¾ teaspoon baking powder ½ cup of butter ½ cup milk 2 eggs
Cookies: 2 cups shortening 4 large eggs 1 cup sugar 2 cups brown sugar 2 t vanilla 1 t salt 2 t baking soda 4 cups all-purpose flour 4-5 cups chocolate chips
Baking Powder•Baking Soda •Buy a new couch •Get oil change•Chocolate Chips•Buy yarn and knitting supplies •Vanilla extract
And Even MoreInitial List•Apples•Tomato Soup•Flour•Milk•Turkey•Lettuce
Sugar
Beans
Hot dogs
Banana
Noodles
Yogurt
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Metadata (EDW Atlas), Security and Auditing
Diabetes
Sepsis
Readmissions
Common, linkable vocabulary
FinancialSource Marts
AdministrativeSource Marts
DepartmentalSource Marts
EMR Source Marts
Patient Satisfaction Source Mart
FINANCIAL SOURCES
ADMINISTRATIVE SOURCES
EMR SOURCEs
DEPARTMENTAL SOURCES
Pt. SATISFACTIONSOURCES
Adaptive Data Model
Less TransformationMore Transformation
#HASummit14
Poll Question #1 - Analytic
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How would you describe your analytics and enterprise data warehousing approach? (choose the best answer that applies)
a. We do not currently have a centralized analytics data repository (e.g., enterprise data warehouse-EDW)
b. We have an EDW based on the enterprise data model approach
c. We have an EDW based on the independent data mart approach
d. We have an EDW based on the adaptive or late-binding architecture approach
e. Unsure or not applicable
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Content System Core Activities
Defining a Clinically Driven Patient Cohort
Using Evidence to Identify Three Types
of Waste
Standardizing Care Delivery through
Shared Baselines.
Analytic System
Content System
Deployment System
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Strong Content System
Time
Measured in Weeks
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Habit of allFront-line Clinicians
at Every Facility
New Clinical or Operational Best Practice
Knowledge Discovered
Measured in Years
Strong Content System
Weak Content System
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Clinical Content System Components
How do we accelerate Evidence Integration into Care Delivery?
Evidence Based Population Management Content: Outcome, process and balanced metrics related to improvement AIM statements, intervention indications, triage criteria, order sets, indications for referral, patient and provider education materials, predictive algorithms, care guidelines and protocolsEvidence Based Patient Safety Content: Outcome, process and balanced metrics related to improvement AIM statements, At risk screening criteria, safety protocols, near miss and incident tracking
What Types of Waste are created without standard work? Ordering Waste: Populations (Heart Failure, Diabetes, etc.)Workflow Waste: Departmental Patient Injury Waste: Patient Safety
How can data accelerate Waste Elimination?Value Stream Maps, A3s, Standard Work starter sets, Outcome, process and balanced metrics related to improvement AIM statements
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Content System Exercise
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Find as many numbers sequentially from 1 to 50 in 20 seconds.
On your mark…Get set…GO!
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ROUND #1
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35
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3 8
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Find as many numbers sequentially from 1 to 50 in 20 seconds.On your mark…Get set…GO!
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ROUND #2
25 1 29 5 41 35 45 33 15 49 9 23 31 13 3 19 27 3917 21 7 53 37 43 47
14 50 4 36 8 28 24 18 2 26 38 16 46 20 6 34 48 1022 32 12 42 30 40 44
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Find as many numbers sequentially from 1 to 50 in 20 seconds.On your mark…Get set…GO!
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1 2 4 5 7 8 10 12 14 153 6 9 11 13 16
17181920212223242534 33 32 31 30 29 28 27 26
50494746444341393736 484542403835
START
END
ROUND #3
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Poll Question #2 - Content
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Rate the level of content standardization (choose the answer that best applies)
a. No standardization. Our clinicians use their best judgment based on their individual training
b. We have begun to standardize some content (e.g. CPOE to implement standardized order sets – provided by our EMR vendor) We have not yet created standard content for both workflow and clinical domains across the continuum of care
c. High degree of standardization, including standardized content for ambulatory and inpatient care management and utilization criteria. The same workflow and care delivery content is followed and measured regardless of what unit or facility a patient enters
d. Unsure or not applicable
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Deployment System Core Activities
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Analytic System
Content System
Deployment System
Organizing for Scalable Improvement
Applying Agile Principles to Care Improvement
Accelerate Root Cause Analysis by Combining
Analytics and Lean Principles
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Strong Deployment System
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Baseline Performance
Improvement with focused project
team
Inability to sustain gains
over time
Weak Deployment System
Baseline Performance
Improvement with permanent
integrated teams
Gains sustained over
time
Strong Deployment System
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Population Health Hierarchy
“Ordering of Care”
12 Clinical Programs Cardiovascular
133 Care Process Families Heart Failure
1610 Care Processes Acute Myocardial Infarction
Primary CareCare
ProcessFamilies
e.g.,Diabetes
CV
CareProcessFamilies
e.g.,Heart
Failure
W&C
CareProcessFamilies
e.g., Pregnancy
GI
CareProcessFamilies
e.g., Lower GIDisorders
Resp-iratory
CareProcessFamilies
e.g., Obstructive Lung
Disorders
Neuro Sciences
CareProcessFamilies
e.g.,Spine
Disorders
Musculo-skeletal
CareProcessFamilies
e.g., Joint
Replace-ment
Surgery
CareProcessFamilies
e.g.,Urologic
Disorders
GeneralMed
CareProcessFamilies
e.g.,Infectious Disease
Oncology
CareProcessFamilies
e.g., BreastCancer
Peds SpecCare
ProcessFamilies
e.g.,Peds
CV Surg
Mental Health
CareProcessFamilies
e.g., Depressio
n
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Organization of teamsClinical and technical
Provides steady state domain governance and oversight
GUIDANCE TEAM
Refines Work Group output and leads implementation
CLINICALIMPLEMENTATIO
NTEAM
Provides a forum to develop and/or refine clinical content and analytics feedback
WORKGROUP
Oversees data governanceSupports developmentof clinical content and
analytics feedback
CONTENT AND
ANALYTICSTEAM
Provides overall governance and prioritization of initiatives
SENIOR EXECUTIVE
LEADERSHIP TEAM
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Care Process Family
Case Count Rank
LOS Hours (Capacity)
Rank
Total Charges
Rank
Total Direct Cost Rank
Total Direct Cost
Opportunity Rank
Organizational Readiness
(1 to 10)1 = most ready
Trauma 9 2 2 3 3
Ischemic Heart Disease
3 7 1 2 2
Infectious Disease 6 3 3 1 1
Pregnancy 1 1 7 4 8
Heart Failure 10 8 4 5 5
Joints 11 13 8 6 16
Normal Newborn 2 6 20 24 32
GI Disorders 4 4 6 7 4
Lower Respiratory 5 5 5 8 6
Ranking Comparison
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Organizational Teams
Women & Children’s Clinical Program Guidance Team
Pregnancy SAM
PregnancyMD LeadRN SME
Knowledge Manager
DataArchitect
Application Administrator
Guidance Team Leads
= Subject Matter Expert= Data Capture
= Data Provisioning & Visualization
= Data Analysis
Normal Newborn SAM
Normal Newborn MD LeadRN SME
GynecologySAM
GynecologyMD LeadRN SME
• Permanent Teams• Integrated Clinical and Technical members• Supports Multiple Care Process Families
MD Lead
Nurse Lead
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Information Management
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DATA CAPTURE
• Acquire key data elements• Assure data quality• Integrate data capture into operational
workflow
DATA ANALYSIS
• Interpret data• Discover new information in the data
(data mining)• Evaluate data quality
DATA PROVISIONING
• Move data from transactional systems into the Data Warehouse
• Build visualizations for use by clinicians• Generate external reports (e.g., CMS)
Knowledge Managers (Data quality, data stewardship and
data interpretation)
Application Administrators (optimization of source systems)
Data Architects(Infrastructure, visualization, analysis, reporting)
= Subject Matter Expert
= Data Capture
= Data Provisioning
= Data Analysis
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Standard “Organizational” Work OverviewKickoff AIM Statement
Implementation Design Launch Approval Results Review
• Mission• Cohort Discover• Data Analysis and
Review• Best Practices• Building Multiple
Potential AIM statements
• Supplement content
• Refine Cohort• Refine Metrics• Develop Draft
Visualizations• Develop
Recommended AIM statement #1
• Cluster Reps Obtain Front Line Input
• Finalize Cohort• Develop Additional
metrics based on feedback
• Develop Additional Visualizations to support
• PDSA cycle
• Cluster Reps Obtain Front Line Input
• Improvement Plan • Implementation Plan• Develop cluster rep
assignments, and deliverables
• Collect cluster rep feedback
• Prepare Initial Results from AIM statement #1
• Summarized report for historical review
• Refine, recommend AIM statement #2
MonthlyTasks and
Checkpoints
7 Steps(Work Streams)
1.Gather Knowledge Assets
2.Define Cohort
3.Select AIM Statement
4.Select, Build, Refine Metrics
5.Develop Implementation Planfor Process Improvement
6. Implementation
7. Measure Progress
Select Initial Metric Build and Refine Build and Refine Build and Refine
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Deployment System Exercise
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Round 1
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Only the Clinician can talk
The Architect cannot look at the drawing (no mind reading)
The Architect can’t start drawing
Only the Architect can draw
The Clinician can only watch – no talking
1 minute to describe 1 minute to draw
1M59585756555453525150494847464544434241403938373635343332313029282726252423222120191817161514131211109876543210 1M59585756555453525150494847464544434241403938373635343332313029282726252423222120191817161514131211109876543210
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1M59585756555453525150494847464544434241403938373635343332313029282726252423222120191817161514131211109876543210
Round 2
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The Architect still cannot look at the drawing (still no mind reading capabilities )
You can interact as much as you want
You can erase and redraw
2 minutes to describe and draw interactively
1M59585756555453525150494847464544434241403938373635343332313029282726252423222120191817161514131211109876543210
#HASummit1447
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Poll Question #3 - Deployment
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How are teams organized to improve the quality of care and sustain improvements? (choose the answer that best applies)
a. We have ad hoc, reactive improvement teams organized on a project basis
b. Our quality department supports service lines and departments for quality and workflow improvement initiatives
c. We have organized, permanent, interdisciplinary, process improvement teams. These teams permanently own the quality, cost, safety and satisfaction of their care delivery domain
d. Unsure or not applicable
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Poll Question #4 - Deployment
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How do you align and prioritize improvement priorities across your organization? (choose the answer that best applies)
a. We don’t have alignment of our improvement priorities. We have free form improvement that is prioritized in silos across the organization
b. We have alignment of our improvement priorities within our hospital, but not across our entire enterprise
c. We have a very clear prioritization and governance process for our improvement priorities, tied to our strategic plan
d. Unsure or not applicable
#HASummit14 50
Problems with Missing SystemsInformation System Centric
If we build it they will come. Focus on reducing information request queue.
Research CentricAcademic ideas with no
practical application. Lots of published papers.
Organization CentricNULL SET
(Clinicians stop coming to meetings if evidence and measurement are both
missing.)
Analytic System
Content System
Deployment System
Science Project CentricPockets of excellence, Limited
roll-out of improvements.
LEAN CentricUn-sustainable Improvements.
Can’t manually measure after 2 or 3 projects.
Automation CentricPaved Cow Paths (Process is automated but not improved –
many EMR deployments.)
Healthcare Analytics Summit 14
Three Systems to Ignite Change
Analytic System
Content System
Deployment System
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Scalable & Sustainable Outcomes
Improved population healthCare delivery is evidenced based, improvements in cost and quality are scalable and sustainable
#HASummit14
In Summary
Don’t boil the ocean!
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Analytic System
Content
System
Deployment
System
Analytic System
• Be agile and adaptive
• Enable knowledge discovery
Content System
• Use best practices to understand and reduce waste
Deployment System
• Leadership is key
• Permanent structures and processes/systemic approach
• Dedicated resources
All 3 systems are needed.
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Analytic Insights
AQuestions &
Answers
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Session Feedback Survey
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1. On a scale of 1-5, how satisfied were you overall with this session?
1) Not at all satisfied2) Somewhat satisfied3) Moderately satisfied4) Very satisfied5) Extremely satisfied
2. What feedback or suggestions do you have? (free form text)
3. On a scale of 1-5, what level of interest would you have for additional learning on this topic (articles, webinars, collaboration, training)
1) No interest2) Some interest3) Moderate interest4) Very interested5) Extremely interested
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Upcoming Breakout Sessions
2:25 PM – 3:25 PM
9. Getting the Most Out of Your Data AnalystJohn Wadsworth, VP, Technical Operations Health Catalyst* This is a hands-on session
10. How to Make Analytics a Strategic, C-Level ImperativeJon Brown, VP and Associate CIO, Mission HealthGene Thomas, VP & CIO, Memorial Hospital Gulfport
11. Creating Physician EngagementBryan Oshiro, MD, CMO, Health CatalystChris D. Spahr, MD, Enterprise Quality Executive, CHW
12. User Group Kickoff & New Product RoadmapThomas D. Burton, SVP, Co-Founder, Health CatalystSteve Barlow, SVP & Co-Founder, Health CatalystHolly Rimmasch, Chief Clinical Officer, Health Catalyst* This is an interactive feedback session
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Location
Grand Ballroom D
Grand Ballroom A
Savoy
Venezia