Population Health Management, Risk Modeling, and Patient

With the growing availability of health data, healthcare delivery is moving beyond individual care to population health management. Using technology and analytics, population health management shifts care from immediate treatment to predictive and preventative care. Cambridge Healthtech Institute and Clinical Informatics News’ 4th Annual Population Health Management, Risk Modeling, and Patient Stratification taking place April 4-5, 2016 at the Seaport World Trade Center in Boston, MA, will bring together thought leaders from the payer, provider, healthcare finance, analyst, technology platform and vendor communities for insightful discussions on implementing a population health management strategy.


Final Agenda

 


Day 1 | Day 2 | Download Brochure

Monday, April 4

7:00 am Registration and Morning Coffee

8:00 Keynote Session: Obtaining Insights and Improving Outcomes with IT Innovation

Chairperson: Gowtham Rao, M.D., Ph.D., Chief Medical Informatics Officer, BlueCross BlueShield of SC

Nicholas Marko, M.D., Chief Data Officer (CDO), Geisinger Health System

Adrienne Boissy, M.D., Chief Experience Officer, Director, Center for Excellence in Healthcare Communication, Cleveland Clinic; Editor in Chief, Journal of Patient Experience

Jason Burke, System VP & Chief Analytics Officer, UNC Health Care
Micky Tripathi, President & CEO, Massachusetts eHealth Collaborative

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10:10 Coffee Break in the Exhibit Hall with Poster Viewing


POPULATION HEALTH MANAGEMENT: TURN DATA INTO A STRATEGIC ASSET

10:55 Chairperson’s Remarks

Eric_GlazerEric Glazer, MBA,CEO, Shared Purpose Connect; Host, Population Health Executive Roundtable; Board Member, Society for Participatory Medicine

 

11:00 Preparing to Thrive in Healthcare’s Upcoming Information Era - Lessons Learned from the Frontline

Leonard_DAvolioLeonard D’Avolio, Ph.D., President, Co-Founder, Cyft; Director, Informatics, Ariadne Labs

The digitization of health records, low cost biological testing, and a growing demand for evidence-based practice will soon create a healthcare industry of haves and have nots. Those that are able to turn data into a strategic asset will thrive. Those unable to think beyond storage, security, and “meaningful use” will not. Practical lessons learned will be shared from a decade of applying cutting edge informatics in government, industry, non-profit, and in the developing world.

11:30 Population Health Management and Quality Improvement: Analytics from an At-Risk-Health System’s Perspective

Gowtham_RaoGowtham Rao, M.D., Ph.D., Chief Medical Informatics Officer, BlueCross BlueShield of SC

ACOs and Integrated Delivery Networks (IDNs, IDSs) are at financial risk for achieving high value healthcare, where value is defined as the highest quality healthcare for a population of patients at the lowest possible cost. There is a spectrum of risk for these ACOs/IDNs when managing various populations and it is important for them to understand how to use data to better identify these risks. If these organizations manage their populations well, they will come ahead financially (a win-win). The presentation will share some examples and share an approach to: 1) identify patterns, 2) create rules, 3) identify opportunities to educate providers, and 4) implement change.

12:00 pm Population Health Management, Risk Modeling and Patient Stratification

Henry_ChungHenry Chung, M.D., Vice President, Chief Medical Officer, Montefiore Health System

This presentation will provide 5 steps to develop a successful population health management program, using real-world examples from a successful care management program. A unique approach was used in order to achieve a more “industrialized” approach to population health management, harnessing commoditized processes to create automated, data-driven, and scalable cross-team workflows that enabled the organization to refocus their efforts on the art and creativity of healthcare.

Linguamatics12:30 Clinical NLP to Support ACOs, Clinical Risk Monitoring and Population Health

Beaulah_SimonSimon Beaulah, Director, Healthcare Strategy, Linguamatics

As the ACOs model grows, it's more important to extract detailed patient information from free-text documents to provide the insights necessary for changing healthcare. Patient narratives, pathology and radiology reports are powerful because they communicate the uniqueness of each patient; NLP is therefore key to understanding patient- and population-level risk.

LexisNexis HealthCare12:45 Luncheon Presentation: Stress Index and Population Health Management: Will The Integration of Medical/Rx Data & Socioeconomic Data Help in Identifying Hidden Pockets of Future Risk?

Asparouhov_OgiOgi Asparouhov, Ph.D., Chief Data Scientist, Clinical Solutions, LexisNexis Risk Solutions

Life events certainly impact health outcomes. To prove that, LexisNexis® embarked on a journey to prove the value of integrating Medical/Rx claim-based data and Socio-economic (SE) in predicting the level of future stress and the impact of stress on adverse outcomes. This session will review the methodology leveraged to measure stress as well as exclusions, to identify socioeconomic data attributes with direct correlation to health outcomes, and ultimately the results of this integration in terms of improved predictive power related to identifying high risk members who have near-term future savings potential that cannot be captured by other standard industry predictions.

1:30 Session Break


RISK MODELING AND PATIENT STRATIFICATION

2:05 Chairperson’s Remarks

Leonard_DAvolioLeonard D’Avolio, Ph.D., President, Co-Founder, Cyft; Director, Informatics, Ariadne Labs

 

2:10 Patient Stratification: And Then What? Managing High Risk Populations

John_MinichielloJohn Minichiello, MBA, Executive Director, Accountable Care Solutions, Steward Health Care Network

This talk will share practical provider experience in managing high risk populations, beginning with the initial risk stratification, to enrolling patients in care management programs, then ultimately measuring an ROI, including both metrics on staff processes and patient utilization outcomes. Populations include ACO, Medicare Advantage, Commercial, Bundled Payment and Employer sponsored plans. Attendees will understand: How to leverage risk stratification data; infrastructure to care manage high risk populations; metrics of measurement and ROI; what to look for in technology/systems; and methods of patient and provider engagement.

2:40 Precision Oncology in a Learning Healthcare System at the VA

Vick_KudesiaValmeek “Vick” Kudesia, M.D., Director, Clinical Informatics, Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Boston VA Healthcare System

The Department of Veteran Affairs has recognized the need to balance patient-centered care with responsible creation of generalizable knowledge on safety and effectiveness of Precision Medicine treatments. The VISN 1 clinical network and MAVERIC have created a new Precision Medicine-focused rapid learning healthcare system program called the Precision Oncology Program (POP), with an initial focus on lung cancer. The VA POP is a Precision Medicine initiative at scale that incorporates many of the pieces of a “future” informatics solution for our Healthcare system. POP includes patient insights and engagement, population management, and discovery of new knowledge. The knowledge and data generated by the POP will be a unique, continually growing, and vertically integrated repository.

OptumInsight3:10 The Value of Adherence Prescriptive Analytics – Targeting Specific Behaviors and Avoiding the PDC Blind Spot

Schilling_CraigCraig Schilling, Pharm.D., Vice President, Patient Programs, Optum

Organizations that target the most “obvious” patients for their medication adherence programs are missing out on a huge cost saving opportunity. Surprisingly, focusing on members just above and just below the 80% PDC threshold omits a significant number of individuals who would benefit from intervention, and without intervention, end up costing the health plan significant health care dollars. Learn about advancements in predictive modeling and prescriptive analytics to efficiently improve quality measures of adherence.


3:40 Refreshment Break in the Exhibit Hall with Poster Viewing


INTERACTIVE BREAKOUT DISCUSSION GROUPS

4:10 Interactive Breakout Discussion Groups

Concurrent breakout discussion groups are interactive, guided discussions hosted by a facilitator or set of co-facilitators to discuss some of the key issues presented earlier in the day’s sessions. Delegates will join a table of interest and become an active part of the discussion at hand. To get the most out of this interactive session and format please come prepared to share examples from your work, vet some ideas with your peers, be a part of group interrogation and problem solving, and, most importantly, participate in active idea sharing.
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5:10 Welcome Reception in the Exhibit Hall with Poster Viewing

6:10 Close of Day

6:15 - 8:45 pm Dinner Workshop: Root Cause Analysis in Healthcare Informatics and Analytics

Patricia Ingerick, MBA, MSHS, Director, The Geneia Institute

(Separate Registration Required)
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Day 1 | Day 2 | Download Brochure

Tuesday, April 5

7:30 am Morning Coffee


IDENTIFYING HIGH UTILIZERS TO MANAGE RISK AND IMPROVE QUALITY

8:05 Chairperson’s Remarks

Beaulah_SimonSimon Beaulah, Director, Healthcare Strategy, Linguamatics

 

8:15 Co-Presentation: Population Health Management: Empowering the Patient and Improving Outcomes through Innovative Patient Engagement

Dipti_Patel-MisraDipti Patel-Misra, Ph.D., Chief Data and Analytics Officer, CEP MedAmerica

 

 Joshua_Tamayo-SarverJoshua Tamayo-Sarver, M.D., Ph.D., CMIO, CEP America

With recent changes in healthcare around improving costs, interventions are becoming more patient centric. What can we in healthcare leverage from other industries in terms of patient engagement? What works and what does not? How do you lower costs and improve outcomes, while improving patient satisfaction? Let’s have a conversation around specific patient engagement data needs, models, and expected outcome.

8:45 Merging Data across Systems to Identify High Utilizers and Impactful Interventions

Dov_MaroccoDov Marocco, Chief Innovation and Improvement Officer, Santa Clara Valley Health and Hospital System

The Santa Clara Valley Health and Hospital System uses an Epic-based data warehouse to merge records from multiple systems to identify patients most in need of care coordination or other transitional needs. As a result, we are able to identify the patients who use our system the most frequently, are most in need of intervention, and identify patients “upstream” that could potentially become high utilizers by segmenting the population according to risk factors and intervening earlier.

Knowledgement9:15 Driving Insight into Patient Health Risks, Costs and Outcomes with Big Data Analytics

Arellano_MattMatt Arellano, Managing Partner, Healthcare, Knowledgent






Reynolds_BillBill Reynolds, Healthcare Partner, Knowledgent

The concepts of Population Health Management (PHM) have long been a goal of many healthcare organizations with the primary barrier being the necessary investment, data sharing and risk modeling that is necessary to delivery upon the vision. Given the introduction of new technology and risk sharing agreements with other organizations in the healthcare ecosystem, Provider groups now have the incentive to invest in the necessary capabilities to deliver upon PHM. Come explore the ways organizations are driving better disease specific risk scoring and other analytical opportunities to enhance the PHM process.

9:30 Behavioral Based Analytics: The Evolution of Risk Stratification and Patient Engagement in Population Health

Dominique_Morgan-SolomonDominique Morgan-Solomon, Morgan-Solomon Consulting; former Chief Operating Officer, Steward Medical Group

This session will challenge traditional predictive models and risk stratification approaches as the basis for population health programs. As the requirements and needs of patients, providers and health care delivery systems become more complex, analytic tools will have to become more specific in identifying behavioral, social and other non-bio/medical determinants of health as opportunities to better target patient populations to drive outcomes in a value based health care paradigm.

9:45 Coffee Break in the Exhibit Hall with Poster Viewing

10:30 The Foundational Approach to Population Health Analytics

Bryan_BennettProfessor J. Bryan Bennett, MBA, Executive Director, Healthcare Center of Excellence

The shift from a fee for service business model to one based on population health requires healthcare organizations to not only understand the health of the patients in their portfolio but also, predict potential future health challenges. This presentation will help organizations understand the building blocks that must be in place to effectively compete using healthcare analytics. Guidelines for analytics implementation will be reviewed as well as presenting how it can be used to compete using healthcare analytics.

11:00 Population Health Strategy, Infrastructure, and Technology: Results at Partners Healthcare

Adrian_ZaiAdrian Zai, M.D., Clinical Director of Population Informatics, Laboratory of Computer Science, Massachusetts General Hospital

Dr. Adrian Zai will share his experience at Partners Healthcare implementing a successful Population Health Management strategy in Boston’s Massachusetts General Hospital and Brigham and Women’s Hospital. Dr. Zai will provide a general overview of technology strategies, infrastructures, and PHM results achieved at Partners Healthcare in 2014. Specifically, he will focus on the IT strategies and tools that were used in the PHM implementation including its demonstrated impact on outcomes. Topics covered will include 1) clinically relevant metrics, 2) areas of divergence of data, 3) centrally vs. federated implementations, and 4) key takeaways for successful change.

11:30 Luncheon Presentation (Sponsorship Opportunity Available) or Lunch on Your Own

12:15 pm Session Break


MANAGING POPULATIONS THROUGH INTEGRATED CARE COORDINATION AND PREDICTIVE ANALYTICS

Special Shared Session

12:55 Chairperson’s Remarks

Adrian_ZaiAdrian Zai, M.D., Clinical Director of Population Informatics, Laboratory of Computer Science, Massachusetts General Hospital

 

1:00 Achieving Success in a Capitated Pediatric Population through Integrated Care Coordination

Kimberly_ConkolKimberly Conkol, RN, CCM, MSN, Director, Care Coordination, Partners for Kids, Nationwide Children’s Hospital

Partners for Kids (PFK) is a physician hospital organization and an affiliate of Nationwide Children’s Hospital that holds the financial risk for 330,000 Medicaid children in Ohio. To achieve the triple aim of improving costs, experience and health, the organization entered into delegated relationships with managed care plans in which care coordination is provided on their behalf. This presentation will describe the informatics process, tools, and resources that resulted in decreases in emergency room visits, inpatient admissions and length of stay. Participants will learn about implementing a successful care coordination model combining process and technology to provide a high quality, integrated patient experience within an accountable care organization.

1:30 Improving Utilization and Care Coordination Using Real Time Predictive Analytics

Dev_CulverDev Culver, CEO, HealthInfoNet

Through the Maine Health Information Exchange, health systems, ACOs, Medicaid, and physician practices use real time predictive risk scores within their daily work flows to target high risk patients for proactive care management. The real time scores allow clinicians and care managers to start the post discharge care management as soon as the patient presents for care. Organizations have been successful in reducing unnecessary readmissions, improving the appropriateness of emergency room utilization, and proving better care coordination for the at risk population.

2:00 INTERACTIVE CAPSTONE PANEL: Leveraging Analytics to Create a Personalized Approach to Population Health: The Psychology of Patient Engagement

Moderator:
Eric_GlazerEric Glazer, MBA, CEO, Shared Purpose Connect; Host, Population Health Executive Roundtable; Board Member, Society for Participatory Medicine

When it comes to patient engagement population health leaders often focus on clinical variables and predictors but ignore a human being’s motivations for doing things. If organizations were able to leverage analytics to understand people’s motivations more, they could then design appropriate engagement tactics to leverage this motivation and in turn improve outcomes of their population health initiatives. During our roundtable we will discuss approaches various organizations are taking, challenge traditional thinking and explore the potential impact you can make when properly combining great technology and psychology. Questions we will explore are:

  • Why are most predictive models not as effective as they need to be?
  • Which data sets have you used successfully to better understand patient behavior (psychology)?
  • Which approaches have you deployed to better leverage the motivation of your patients?
  • How are organizations taking lifestyle variables into consideration when measuring risk? 
  • What is example of how lifestyle based analytics is being out into practice?
  • How long do patient engagement programs typically stay impactful?
  • What are the different ways you are you measuring patient engagement?

2:30 pm Closing Remarks


Join the Bio-IT World Community Plenary Keynote Session & Reception!

4:00 – 5:00 Bio-IT World Plenary Keynote Presentation
Heidi L. Rehm, Ph.D., FACMG, Chief Laboratory Director, Laboratory for Molecular Medicine, Partners Healthcare Personalized Medicine; Clinical Director, Broad Institute Clinical Research Sequencing Platform; Associate Professor of Pathology, Brigham & Women’s Hospital and Harvard Medical School

5:00–7:00 pm Networking Reception in the Bio-IT World Exhibit Hall


Day 1 | Day 2 | Download Brochure

Concurrent Conference Tracks:


Track 1: Value-Based Delivery Models and Cross-Industry Data Collaboration
Track 2: Coordinated Care, Patient Engagement and Connected Health
Track 3: Population Health Management, Risk Modeling, and Patient Stratification
Track 4: Achieving Global Interoperability in Healthcare Datasets and Systems




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