Opening Keynote

Dan BurtonSeptember 7, 2016

Topics

o Attendee analytics

o Themes for this year’s summit

o Outcomes improvement at scale

o Our commitment to you

Attendee Analytics

How would you best characterize your organization?

74%

4%

7%

3%

8%

4%

64%

4%

7%

2%

12%

11%

57%

6%

4%

2%

19%

12%

A) Healthcare provider

B) Healthcare payer

C) Healthcare association

D) Government entity

E) Consultant or services provider

F) Healthcare solution vendor

2016

2015

2014

How long have you been involved in healthcare?

17%

20%

32%

31%

18%

19%

31%

32%

19%

15%

30%

36%

A) 0 - 5 years

B) 5 - 10 years

C) 10 - 20 years

D) Over 20 years

2016

2015

2014

On a scale of 1 to 3, which stage would best describe where your

organization is in adopting analytics?

31%

49%

20%

33%

46%

21%

1-Beginning stage

2-Middle stage

3-Advanced stage

2016

2015

On a scale of 1 to 3, in your opinion, how successful has your

organization’s population health initiatives been to date?

18%

65%

17%

9%

59%

32%

1-Not successful

2-Moderately successful

3-Very successful

2016

2015

How rapidly do you think the US is moving towards a value-

based reimbursement model?

41%

46%

13%

A) Moving too slowly

B) Moving at the right pace

C) Moving too quickly

2016

What impact do you think value-based reimbursement will

have on the quality of care?

2%

19%

79%

1-Worse or somewhat worse

2-About the same

3-Somewhat better or better

2016

Which group will most significantly effect and drive successful

accountable care models in the future?

22%

31%

47%

19%

33%

48%

A) Government entities

B) Physicians and physician groups

C) Hospitals / Health Systems

2016

2015

Which new data sets do you feel will be the most important in

the new value-based care models?

36%

39%

22%

3%

A) Patient-reported outcomes

B) Social determinants of health data

C) Activity-based costing data

D) External demographic data

2016

What was your most memorable fad of the 80's?

12%

6%

23%

27%

32%

A) Cabbage Patch Dolls

B) Care Bears

C) Rubik's Cube

D) Trivial Pursuit

E) Video Arcades

2016

What was your favorite video game of the 80's?

11%

8%

29%

29%

23%

A) Donkey Kong

B) Frogger

C) PAC-MAN

D) Super Mario Brothers

E) Tetris

2016

Which was your favorite 80's TV show?

18%

35%

7%

15%

25%

A) The A-Team

B) Cheers

C) Hill Street Blues

D) Miami Vice

E) The Wonder Years

2016

Themes for HAS ‘16

Themes for HAS ‘16

o Achieving scale in outcomes improvement

o Realizing ROI from analytics investment

o Training & developing analysts

o Implementing effective governance

o Managing the volume to value transition

Keynote Presentations

Anne Milgram(former New Jersey Attorney General)

Criminal Justice Analytics and Insights

for Healthcare

Jay T. Bishoff, MD, FACS(Intermountain Healthcare)

Reducing Waste at Intermountain Healthcare:

The Vision, Mission, and Tools to Change

Everything

Toby Freier(President, New Ulm Medical Center)

Population Health: Lessons from One of the

Nation’s Most Innovative Rural Community

Models

Don Berwick(Former CMS Administrator, Founding CEO of IHI)

Can Clinicians Take the Lead in Health Care

Reform?

Craig Strauss, MD, MPH(Cardiologist, Medical Director, Minneapolis Heart

Institute for Healthcare Delivery Innovation)

Leveraging Data and Strong Partnerships To

Thrive In The Land Between Volume And Value

David F. Torchiana, MD(CEO, Partners HealthCare)

PHM is Here to Stay

(And We Need Better Data to Get it Right)

Liz Wiseman(Best Selling Author, Speaker, and Executive Advisor)

Rookie Smarts: The Power of Not Knowing

Session Name Type

UPMC’s System-Wide Change to Service Lines— Supported by Activity-Based Costing: The Blueprint to Healthcare Improvement Efforts Case Study

Predictive Analytic Models – a Must in the Journey to Reducing Readmissions Case Study

Actionable Analytics: From Predictive Modeling to Workflows Case Study

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie or Die Education Session

Building an Enterprise Analytics Organization Case Study

FHIR’d up about Clinical Data Intelligence: Cleveland Clinic’s Real Time Decision Support System Technical Session

Patients Don't Measure Quality Care—They Experience it Case Study

From the Boardroom to the Bedside – Using Analytics to Drive a Culture of Continuous Improvement Case Study

An 85% Prediction Model? Advances in Sepsis Prediction at Johns Hopkins Case Study

The Geisinger Hedged Unified Data Architecture Case Study

Improved Outcomes and a Proven ROI Model for Quality Improvement: Transforming Diabetes Care Case Study

Security Frameworks in Data Warehousing and Their Interplay with Healthcare Analytics Technical Session

Outcomes Improvement Governance: The Quest to Achieve More With Less Education Session

Integrating Detailed Patient Level Costs With Outcomes and Quality Metrics Case Study

Deploying Predictive Analytics: A Practitioner’s Guide Technical Session

Healthcare Analytics — Are You Just Buying a Car or Actually Planning to Go Somewhere? Education Session

New Competencies for Succeeding in Risk-based Arrangements Education Session

Do No Harm: Reducing Hospital-Acquired Conditions Through Cultural Transformation, Analytics, and Education Education Session

Partners’ Care Management Strategy: A 10-Year Journey Education Session

Turn Your Analysts into Data Detectives: Discvoreing Pttaerns in Dtaa Education Session

Powerful Ways to Use Hadoop in your Healthcare Big Data Strategy Technical Session

Leading Adaptive Change to Create Value Education Session

Population Health Management – Driving Improved Outcomes in Women’s Services Through Collaboration and Analytics Case Study

Improving Outcomes in a Value-Based Environment: Holistic Care Management for Complex Medical Conditions Case Study

How to Measure and Get an ROI out of your Outcomes Improvement Projects Education Session

Text Analytics: You Need More than NLP Technical Session

Improve Reported Outcome Measures With Standardized Care Processes Case Study

Breakout Session Topics & Type

Wave 1

Wave 2

Wave 3

Wave 4

Wave 5

Outcomes Improvement

at Scale

Question: What is necessary to scale outcomes improvement?

o Integrated literature review of competencies that contribute to

implementing and sustaining performance improvement

o Internal team of executives, clinicians, operational leaders, data

analysts/architects with > 300 combined years of organizational

improvement practice experience

o Determination and quantification of content validity and usability

in July 2016

Subject Matter Expert Contributors to Our Findings

Jim Adams, MBA, Executive Director, The Advisory Board.

Seth Bata, Director, Clinical & Business Analytics, Mission Health.

Terri L. Brown, MSN, RN, CPN, Clinical Specialist, Quality & Safety, Texas Children's Hospital.

Sreekanth Chaguturu, MD, Vice President of Population Health Management, Partners HealthCare.

Laura Craft, Research Director, Gartner Healthcare Industries Research Group.

Roopa Foulger, Executive Director, Data Delivery, OSF Healthcare.

Charles Macias, MD, Chief Clinical Systems Integration Officer, Texas Children’s Hospital; Associate Professor

of Pediatrics/Section of Emergency Medicine; Director, Center for Clinical Effectiveness and EBOC.

Lloyd Provost, MS, Statistician, Senior Fellow and Improvement Advisor for IHI (Institute of Healthcare Improvement).

Timothy Sielaff, MD, Chief Medical Officer and Senior Vice President, Specialty Care and Research, Allina Health.

Val Ulstad, MD, MPA, MPH, Chief Engagement Officer of Partners at Cascade Bluff.

Terrill Wolf, Manager, Data Architecture, Stanford Health Care.

Our Findings:

Five Keys To Outcomes Improvement Scale

Leadership, Culture, And Governance

Financial Alignment

Adoption

Best Practice

Analytics

Represents leadership, and organizational culture and structure needed to design a strategy for sustained, system-wide outcomes improvements.

Represents standard measurement work (data sources, visualizations, and analysis) needed to monitor and assess priorities, progress, and outcomes.

Represents standard ‘knowledge’ work (guidelines, protocols, and order sets) needed to guide and improve best practice.

Represents standard organizational work (teams, roles, processes, mindset changes) needed to transform.

Represents organizational and payer incentives and payment models to deliver high quality, cost effective, and patient centric care.

Operationalizing our Findings:

Outcomes Improvement Readiness Assessment

5 Keys to Outcomes Improvement. 22 Competency Statements.

Best Practice

2.0

Best Practice

Adoption

1.0

Adoption

Financial

Alignment

2.9

Financial Alignment

Analytics

3.1

Analytics

Leadership, Culture,

and Governance

4.1

Leadership, Culture, And Governance

Our Invitation:

Use this tool to build outcomes improvement capability

Access the assessment within the

HAS mobile application.

Thursday, at lunch time, you’ll have

an option to meet with experts who

can help you interpret your results.

Finally, we will share the aggregated

results from HAS attendees who

completed the assessment in our

Thursday wrap-up session.

Our Commitment to You

Our Commitment to You

o Focus on innovations helpful to healthcare

o No Health Catalyst sales pitches

o We’ll start and end on-schedule

o No long CEO speeches

Thank you.