Population Health Analytics: Improving Care One Patient at a Time
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Transcript of Population Health Analytics: Improving Care One Patient at a Time
© 2014 Health Catalyst
www.healthcatalyst.comProprietary and Confidential
© 2014 Health Catalyst
www.healthcatalyst.comProprietary and Confidential
Improving Care One Patient at a Time
February 4, 2015
Population Health Analytics
© 2014 Health Catalyst
www.healthcatalyst.comProprietary and Confidential
The Buzzword: Population Health ManagementWhat does it really mean?
• Managing the health outcomes of a population of
patients with a similar condition?
• Going at risk with payers for the outcomes of a
population of patients (Fee-for-Value)?
• Using care management to improve outcomes for
high-risk, high-cost patients?
• Engaging patients and communities for better
health outcomes?
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Common Thread: Outcomes
Provide the highest quality care
with an optimal care experience
for a population of patients
at the lowest appropriate cost
3
Quality Outcomes
Experience Outcomes
Cost Outcomes
The key population health management question:
How do we systematically improve outcomes for a
population of patients, one patient at a time?
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3 Ingredients of Fire
4
Fire
Fuel
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3 Ingredients of Fire
5
Fire
Fuel
What should we be doing?
How are we
doing?
How do we
transform?
Content System
Outcomes
Improvement
3 Ingredients of Outcomes Improvement
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A Tautology…
6
"Every system is perfectly designed to get the results it gets.”
- Dr. Paul Batalden
... so re-design your system to get better results.
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How systematic are we at Outcomes Improvement?
7
Fire
Fuel
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Content System
Outcomes
Improvement
3 Systems for Outcomes Improvement
8
What should we be doing?
How are we
doing?
How do we
transform?
© 2014 Health Catalyst
www.healthcatalyst.comProprietary and Confidential9
Content System OverviewWhat should we be doing?
9
Map the Process Care improvement map – Includes workflow & clinician's decision-flow across care continuum
Identify Common Problems - Potential ImprovementsSpecific AIM Statements for outcomes and process to measures for focused improvement
Scope the problem – Define Precise Patient RegistriesSpecific clinical inclusion and exclusion criteria for the sub-cohort of patients for the AIM
Adopt Standardization Aids Checklists, order sets, and protocols to make it easy for clinicians to choose the best action
Produce Actionable Visualizations Scorecards and dashboards that promote best practice behaviors and invite action
© 2014 Health Catalyst
www.healthcatalyst.comProprietary and Confidential10
Infr
astr
uctu
re: H
ostin
g / H
ard
wa
reAnalytics System OverviewHow are we doing?
10
e.g. EPSi,
Peoplesoft,
Lawson
e.g. Lawson,
Peoplesoft,
Ultipro
Subject Area Mart Designer
Source Mart Designer
EMR
EMR FinancialPatient
Sat. HR Administrative Claims
FinancialPatient
Sat.HR Administrative Claims
e.g. Epic, Cerner
NextGene.g. Press Ganey,
NRC Pickere.g. API Time
Tracking
e.g. Medicare
Private Payers
Shared Frameworks & Tools for improvementComorbidity Analyzer, Registry Repository, Attribution Modeler, Common
Definition Repository, Hierarchies, CAFE, Atlas, IDEA, Eventalytics,
Geospatial, Risk & Severity Profiling, etc
Metadata Driven ETL Engine
Enterprise Data Warehouse Platform
Analyze and Interpret Data
• Show correlation and causation
• Integrate clinical, financial, and
patient experience data
• Predict outcomes and prescribe
actions
Shared Reoccurring Data Tasks
• Cohort Definitions
• Patient/Provider Attribution
• Severity/Comorbidity Analysis
• Calculation/Term Definition
• Comparative Repositories
Source Data Integration
• Automatically co-locate data from
different source transactional
systems (EMR, Claims, Financial,
Patient Satisfaction)
• Automatically connect data
together with key identifiers
(Patient, Location, Provider)
Infrastructure
• Security and Auditing capabilities
• Metadata Repository
© 2014 Health Catalyst
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Deployment System OverviewHow do we transform?
11
Improvement Capacity AssessmentEvaluation of organizational capacity for change, current capabilities, and gaps
GovernanceData Governance/Data Stewardship and Advanced Organizational Governance & Prioritization
Improvement MethodologySystematic improvement incorporating LEAN / PDSA principles, AGILE software development, etc.
Accelerated Practices TrainingSystematic training of Adaptive Leadership, Quality Improvement/LEAN skills, and Technology
11
© 2014 Health Catalyst
www.healthcatalyst.comProprietary and Confidential
Content System
Outcomes
Improvement
3 Systems for Outcomes Improvement
12
What should we be doing?
How are we
doing?
How do we
transform?
© 2014 Health Catalyst
www.healthcatalyst.comProprietary and Confidential13
Content System OverviewWhat should we be doing?
13
Map the Process Care improvement map – Includes workflow & clinician's decision flow across care continuum
Identify Common Problems - Potential ImprovementsSpecific AIM Statements for outcomes and process to measures for focused improvement
Scope the problem – Define Precise Patient RegistriesSpecific clinical inclusion and exclusion criteria for the sub-cohort of patients for the AIM
Adopt Standardization Aids Checklists, order sets, and protocols to make it easy for clinicians to choose the best action
Produce Actionable Visualizations Scorecards and dashboards that promote best practice behaviors and invite action
© 2014 Health Catalyst
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Care Improvement Map
Sepsis and septic shock
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Identify Potential ImprovementsProcess AIMs and Outcome Goals
Transformation Process
Starter Set
Content
Implement
InterventionMeasure &
Sustain
Review &
Select AIM Define CohortIterate on
Metrics
Heart Failure: AIM #1
Starter Set
Content
Implement
InterventionMeasure &
Sustain
Review &
Select AIM Define CohortIterate on
Metrics
Heart Failure: AIM #2
Process Improvement AIM:
Improve Follow-up Visit Scheduling
From 43% to 90% by October 31, 2015
Process Improvement AIM:
Improve Medication Reconciliation
From 58% to 80% by June 30, 2015
Heart Failure Outcome Improvement Goal:
Maintain and Improve Cardiac Function = Increase % of HF population with
adequate cardiac function from 64% to 80% by December 31, 2015
2-4 Process Improvement AIMS should produce a significant outcome improvement
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Standard Patient RegistryStart with administrative codes
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Supplemental ICD9 (38,250)
Medications
(72,581)
Problem List
(22,955)
ICD9 493.XX (29,805)
Additional
Potential Rules
(101,389)
17Total Count of Distinct Patients = 106,714
Precise patient registryMove to clinically defined cohorts
Standard Registry
Precise Patient Registry
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18
Adopt Standardization Aids
or Knowledge Assets
Admits/1000 members
IP days/1000 members
OP visits/1000 members
Procedures/1000 members
ED visits/1000 members
Readmissions/1000 members
UtilizationWho should
get the care?
Cost/case
Cost/procedure
OR minutes
L&D minutes
Other LOS
Order Sets
Workflow
Cost per case
Nursing hours by unit
OR minutes
L&D minutes
Cycle times
Cost per ancillary test
Environmental services
What care
should be
included?
How can care
be delivered
efficiently ?
Indications for Intervention
Diagnostic algorithms
Indications for Referral
Triage Criteria
Treatment and Monitoring
Algorithms
Health Maintenance and
Preventive Guidelines
Standardized Follow-up Checklist
Post-acute care order sets
IP (SNF, IRF)
Home health, Hospice
Clinical Ops Procedure Guidelines
Knowledge
Asset Type
Substance Selection Clinical Supply Chain
Management
Admission Order Sets Supplementary Order Sets
Pre-Procedure Order Sets
Post-procedure Order Sets
Bedside Care Practice Guidelines
Discharge Checklist
Patient Injury Prevention Protocol
Risk Assessment
Transfer Checklist
Question to
ask
Examples Possible Measures
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Home
(Patient Portal)
* To Invasive
Care Processes
Clinic Care
Non-recurrent
Clinic Care
ChronicAcute Medical
IP Med-Surg
Acute Medical
IP ICU
Invasive
Medical
Invasive
Surgical
Diagnostic Work-up
Bedside care
Triage to Treatment Venue
Substance
Preparation
Invasive*
Subspecialist
Chronic
Disease
Subspecialist
Screening & Preventive Symptoms
Procedure
Indications for Intervention
Diagnostic algorithms
Indications for Referral
Triage Criteria
Preventive, Diagnostic, Triage
and Clinic Care, Algorithms;
Referral & Intervention
Indications (scientific flow)
Utilization
Treatment and
Monitoring
Algorithms
Treatment and Monitoring Algorithms
Health Maintenance and
Preventive Guidelines
Substance Selection
Substance Selection
Clinical Supply Chain Management
Admission Order SetsAdmission Order Sets
Supplementary Order Sets
Pre-Procedure Order Sets
Post-
procedure
Order Sets
Order sets and indications for
selection of substances and
clinical supplies (scientific-flow
focus)
Order Sets
Post-procedure Care
Discharge
Bedside care practice guidelines, risk
assessment and patient injury prevention
protocols, bedside care procedures,
transfer and discharge protocols
Standardized
Follow-up
Post-acute
care order sets
IP (SNF, IRF)
Home health
Hospice
Clinical ops procedure guidelines and
patient injury prevention
Implementation of protocols
based on MD orders and clinical
operations-initiated activities
(Lean/TPS workflow focus)
Workflow
Care
Process
Models
Value
Stream
Maps
MD Population Knowledge Assets
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= Negative Impact = Positive or Negative = Positive Impact
Knowledge Asset
Type
Discounted
FFS Per Diem
Per Case Bundled Per CaseCondition
Capitation
Full
CapitationCMS Commercial CMS Commercial
Workflow
Diagnostic Variation
Standing Orders
Medication Selection
Triage
Patient Safety
Ambulatory Treatment
and Monitoring
Indications for Referral
Indications for
Intervention
Payment structure considerations
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Poll Question #1Content System
What types of standardized content have you implemented to support Population Health Management? 192 respondents
A. Just Starting – 42%‒ We have not standardized content to support Population Health Management.
Our clinicians use their best judgment based on their individual training.
B. Mid-Journey – 49%‒ 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. Mature – 9%‒ We have implemented standardized content to manage ambulatory and inpatient
care management (e.g., ambulatory treatment algorithms, order sets, bedside care protocols) and utilization criteria (e.g., diagnostic algorithms, triage criteria, indications for referral and intervention) regardless of what unit or facility a patient enters the same workflow and care delivery content is followed and measured.
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Content System
Outcomes
Improvement
3 Systems for Outcomes Improvement
23
What should we be doing?
How are we
doing?
How do we
transform?
© 2014 Health Catalyst
www.healthcatalyst.comProprietary and Confidential24
Infr
astr
uctu
re: H
ostin
g / H
ard
wa
reAnalytics System OverviewHow are we doing?
24
e.g. EPSi,
Peoplesoft,
Lawson
e.g. Lawson,
Peoplesoft,
Ultipro
Subject Area Mart Designer
Source Mart Designer
EMR
EMR FinancialPatient
Sat. HR Administrative Claims
FinancialPatient
Sat.HR Administrative Claims
e.g. Epic, Cerner
NextGene.g. Press Ganey,
NRC Pickere.g. API Time
Tracking
e.g. Medicare
Private Payers
Shared Frameworks & Tools for improvementComorbidity Analyzer, Registry Repository, Attribution Modeler, Common
Definition Repository, Hierarchies, CAFE, Atlas, IDEA, Eventalytics,
Geospatial, Risk & Severity Profiling, etc
Metadata Driven ETL Engine
Enterprise Data Warehouse Platform
Analyze and Interpret Data
• Show correlation and causation
• Integrate clinical, financial and
patient experience data
• Predict outcomes and prescribe
actions
Shared Reoccurring Data Tasks
• Cohort Definitions
• Patient/Provider Attribution
• Severity/Comorbidity Analysis
• Calculation/Term Definition
• Comparative Repositories
Source Data Integration
• Automatically co-locate data from
different source transactional
systems (EMR, Claims, Financial,
Patient Satisfaction)
• Automatically connect data
together with key identifiers
(Patient, Location, Provider)
Infrastructure
• Security and Auditing capabilities
• Metadata Repository
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Strong Analytic System
Non value-add Value-add
Understanding the question
Hunting for data
Interpreting data
Data distribution
Gather, compiling or running
Weak Analytic System
Strong Analytic System
The majority of time is spent
analyzing and interpreting data
Understanding the question
Hunting for data
Interpreting data
Data distribution
Gather, compiling or running
25
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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 Modeling (Many Technology Vendors)
FINANCIAL SOURCES
(e.g. EPSi, Lawson,
PeopleSoft)
ADMINISTRATIVE
SOURCES
(e.g. API Time Tracking,
Lawson HR)
EMR SOURCES
(e.g. Cerner, Epic,
NextGen)
DEPARTMENTAL
SOURCES
(e.g. Apollo)
Pt. SATISFACTIONSOURCES
(e.g. NRC Picker, Press
Ganey)
EDW
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EMR SOURCES
(e.g. Cerner, Epic,
NextGen)
Oncology
DiabetesHeart
Failure
Regulatory
Pregnancy Asthma
Labor
Productivity
Revenue
Cycle
Census
Pt. SATISFACTIONSOURCES
(e.g. NRC Picker, Press
Ganey)
DEPARTMENTAL
SOURCES
(e.g. Apollo)
FINANCIAL SOURCES
(e.g. EPSi, Lawson,
PeopleSoft)
ADMINISTRATIVE
SOURCES
(e.g. API Time Tracking,
Lawson HR)
Redundant
Data Extracts
Dimensional Data Modeling (EMRs & Healthcare Point Solutions)
EDW
Less TransformationMore Transformation
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Metadata (EDW Atlas), Security and Auditing
Diabetes
Sepsis
Readmissions
Common, linkable
vocabulary
Financial
Source Marts
Administrative
Source Marts
Departmental
Source Marts
EMR
Source Marts
Patient
Satisfaction
Source Mart
FINANCIAL SOURCES
(e.g. EPSi, Peoplesoft,
Lawson)
ADMINISTRATIVE
SOURCES
(e.g. API Time Tracking)
EMR SOURCEs
(e.g. Cerner, Epic,
NextGen)
DEPARTMENTAL
SOURCES
(e.g. Apollo)
Pt. SATISFACTIONSOURCES
(e.g. NRC Picker, Press
Ganey)
Adaptive Data Modeling
Less TransformationMore Transformation
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Information Management
2929
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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Less Effective Approach “Punish the Outliers”
# of
Cases
Current Condition
• Significant Volume
• Significant Variation
# of
Cases
Option 1: “Punish the Outliers” or
“Cut Off the Tail”
Strategy
• Set a minimum standard of quality
• Focus improvement effort on those
not meeting the minimum standard
Mean
Focus on
Minimum
Standard
Metric
Excellent OutcomesPoor Outcomes Excellent OutcomesPoor Outcomes
1 box = 100 cases in a year
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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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Excellent OutcomesPoor Outcomes
# of
Cases
Excellent OutcomesPoor Outcomes
# of
Cases
Excellent Outcomes
# of
Cases
Poor OutcomesExcellent Outcomes
# of
Cases
Poor Outcomes
1
2
3
4
Var
iab
ility
High
Low
Resource ConsumptionLow High
Improvement Approach - Prioritization
32
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Internal Variation versus Resource ConsumptionY
-A
xis
= In
tern
al V
aria
tio
n in
Re
so
urc
es C
on
su
me
d
Bubble Size = Resources
Consumed
Bubble Color = Clinical DomainX Axis = Resources Consumed
1
2
3
4
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Prioritize: Pareto Analysis App
34
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0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
% of Total Cumulative %
35
X-Axis = Care Processes by resources consumed (High to Low)
Y-A
xis
= P
erc
en
t o
f to
tal
reso
urc
es c
on
su
med
Pareto Analysis >> Prioritization
Top 85 Care Processes account
for 80% of the opportunity (+45)
Top 40 Care Processes account
for 62% of the opportunity (+27)
Top 13 Care Processes account
for 34% of the opportunity
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Poll Question #2Analytics System
How is data from disparate transactional systems integrated? (e.g. EMR, Cost, Patient Satisfaction) 215 respondents
A. Just Starting – 37%‒ Analyst manually integrate data into spreadsheets.
B. Mid-Journey – 50%‒ We use one of our transactional systems (e.g. EMR or Financial) to
integrate a limited subset of data for some of our transactional systems for key operational reports.
C. Mature – 13%‒ We have implemented an Enterprise Data Warehouse Platform, fully
automated load from all of our transactional systems runs at least daily which integrates data based on common linkable identifiers (e.g. patient and provider IDs), with near-real time loads for selected data.
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Poll Question #3Analytics System
What technical tools do you use to move your organization away from reactionary, emotional decisions toward data-driven decisions? 193 respondents
A. Just Starting – 27%‒ We don't use any technical tools to help us with data driven
prioritization, although we have some reports.
B. Mid-Journey – 57%‒ We use some spreadsheet analysis and reports to evaluate options but
opportunities are still typically selected based on politics, a crisis or the most vocal advocate.
C. Mature – 17%‒ We have robust applications which provide our centralized clinical and
operational governance team with objective criteria for use in prioritizing improvement initiatives, including identifying our key processes based on size and variability.
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Content System
Outcomes
Improvement
3 Systems for Outcomes Improvement
38
What should we be doing?
How are we
doing?
How do we
transform?
© 2014 Health Catalyst
www.healthcatalyst.comProprietary and Confidential39
Deployment System OverviewHow do we transform?
39
Improvement Capacity AssessmentEvaluation of organizational capacity for change, current capabilities, and gaps
GovernanceData Governance/Data Stewardship and Advanced Organizational Governance & Prioritization
Improvement MethodologySystematic improvement incorporating LEAN / PDSA principles, AGILE software development, etc.
Accelerated Practices TrainingSystematic training of Adaptive Leadership, Quality Improvement/LEAN skills, and Technology
39
Organizational Assessment I October 15, 2014 I 40
Readiness Assessment Example1) Data Access Process
2) Registry Definition Process
3) Data Governance & Data Quality Process
4) Sustained Care Improvement Process
5) Standardized Criteria for Treatment & Venue
6) Cost Allocation Methodology
12) Data Integration Infrastructure
11) Missing Data Element Capture
10) Data-driven Prioritization
9) Prescriptive Modeling
8) Standardized Calculations & Definitions for Internal Reporting
7) Standardized Protocols for Population Health
Deployment
Content
Analytics
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Small Teams (Designs Innovation)
• Meet weekly in iteration planning meeting
• Build DRAFT processes, metrics, interventions
• Present DRAFT work to Broader TeamsOB
Innovators
Guidance Team (Prioritizes Innovations)
• Meet quarterly to prioritize allocation of technical staff
• Approves improvement AIMs
• Reviews progress and removes road blocksOB Newborn GYN
W&N
W&N
Innovators
Innovators
Early Adopters
Broad Teams (Implements Innovation)
• Broad RN and MD representation across system
• Meet monthly to review, adjust and approve DRAFTs
• Lead rollout of new process and measurementOB
W&N
W&N
W&N
Innovators
Early Adopters
Early Adopters
Executive Leadership Team
• Prioritizes sequence of formation of Guidance Teams
• Approves Board Level Outcomes Goals
• Reviews progress and removes road blocks
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Improvement Types
42
Outcomes
Improvement
Examples: Reduction in Mortality Rate; Hard
Cost Savings; Time Savings (Soft Cost);
Improved Health Function
Difficu
lty to
Ach
ieve
Process
Improvement
Examples: Process Step: % of Patients with
scheduled follow-up visit at discharge; Data
Quality: % of Heart Failure Patients with
Ejection Fraction captured in EMR
Opportunity
Identification
Improvement
Examples: Potential $ Savings from Variation
Reduction (Key Process Analysis) ; Potential
$ Leakage reduction by encouraging
providers to refer patients in network
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Requirements Gathering
Project Plan/ Estimation
Use Cases/
Functional Specs
Design
Specifications
Code
Test
Fix / Integrate
High Level
Stories
Vision
Release 1
Release 2
Release 3
Release 4
$
$
$
$
$$
$$
$$$$$
Documentation
Customer
sees the
productValue to
the
Customer
Traditional
“Waterfall”
Agile
Sources: Adapted from various ideas taught by Alistair Cockburn
and Martin Fowler – see alistair.cockburn.us and www.thoughtworks.com
Traditional Approach vs. Agile Approach
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Accelerated Practices ProgramPREPARING HEALTHCARE TEAMS
TO ACCELERATE OUTCOMES IMPROVEMENT
Immersive Quality Improvement Training
• 8 Session Course - taught over 4-6 months, 2 ½ days per month
• Train the trainers – required for coaches and team leaders
• Quality Improvement Theory applied on actual project with 2-4 person team
Executive Training
• 2 day executive course taught quarterly
• Provides leadership visibility into training and high level principles
Just-in-time Training
• Library of 10-15 minute modules used as needed by permanent teams
• Readily available to clinical, technical and operational team members
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Poll Question #4Deployment System
How are teams organized to improve the quality of care and sustain improvements? 237 respondents
A. Just Starting – 33%‒ We have ad-hoc improvement teams organized on a project basis in a reactive
mode (e.g., to respond to a TJC sentinel event). After a project ends, many of the gains achieved may be lost because limited organizational infrastructure remains to sustain the gains.
B. Mid-Journey – 55%‒ Our Quality Resources Department provides support to Service Lines and
Departments apply quality improvement and workflow principles to improvement initiatives. Some individual units or facilities may focus on quality but dispersion of improvements to all units or all facilities is limited. Improvement is still project based.
C. Mature – 11%‒ We have organized permanent interdisciplinary cross facility teams, which include
clinical and technical subject matter experts with process improvement skills; these teams permanently own the quality, cost, safety and satisfaction of their care delivery domain. Senior executive leadership and Board meetings spend the majority of their time reviewing the goals and progress of these permanent improvement teams.
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Outcomes
Improvement
Content System
46
Science Project CentricPockets of excellence, Limited
roll-out of improvement across
all facilities
Research CentricAcademic ideas with no
practical application. Lots
of published papers.
Information System
Centric“If we build it they will
come.” Focus on reducing
information request queue.
Automation Centric“Paved Cow Paths”
(Process is automated but not
improved – many EMR
deployments)
Organization Centric
Management “Flavor of the month”
Clinicians disengage if evidence
and measurement are both
missing
LEAN CentricUn-sustainable Improvements.
Can’t manually measure
after 2 or 3 projects.
Ignite ChangeScalable & Sustainable
Outcomes Improvement in
Population Health
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Questions?
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Thank YouUpcoming Educational Opportunities
The Pioneers Take the Arrows and the Settlers Take the Land: Healthcare
Predictions for 2015
Date: February 11, 2015, 1-2pm, EST
Host: Dale Sanders, Vice-President, Strategy
Register @ www.healthcatalyst.com