WE ARE. Data-driven Social Determinants of Health for Life

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1 WE ARE Data-driven Social Determinants of Health for Life Douglas Goldstein Deanne Primozic Kasim April 2018

2 TABLE OF CONTENTS DATA KNOWS YOU... 1 The "WE ARE" DataStream.2 Data Everywhere. Data Defines and Drives our Lives DataStreams to Harness Data-driven SDoH Solutions... 4 "WE ARE" - Data-driven SDoH Influencing Medical Costs and Outcomes... 8 Healthy Organizations and Communities Apply SDoH and Data to Improve Health "WE ARE" Powers Doing It Better About the Authors References All rights reserved Santesys Solutions i

I. Data Knows You Who are you? Today the data knows! DataStreams are being created by each of our mobile and Internet-connected devices moment by moment each and every day.

3 I. Data Knows You Who are you? Today the data knows! DataStreams are being created by each of our mobile and Internet-connected devices moment by moment each and every day. In fact, 90% of all data created in the history of humankind has been created in the last few years. We are talking in excess of two quintillion bytes of data a day being generated. A quintillion is a billion, billion; the data generated by our interactions with the Web, Twitter Ò, Amazon Ò, every Google Ò search, text message, photo taken, command sent to Alexa and all our other actions recorded as digital data is the number TWO followed by 18 zeros! The challenge in healthcare today is knowing the elements and characteristics of the DataStreams as they relate to the overall Determinants of Health. The goal is to ethically and legally harness data to develop new products and services that can improve health quality and lower costs, while delivering value and profitability within sustainable organizations. There are four broad Determinants of Health zones influencing our longevity, quality of life and total costs of health care. These zones include: 1) Multi-omic, biological analyses including our genetic, proteomic, microbiome and other omic profiles 2) Social Determinants of Health (SDoH) including economic, social and environment factors 3) Medical care, which is actual clinical care delivered and recorded, and 4) Health Behaviors including a person s daily behaviors (e.g., activity, nutrition, sleep and coping skills). The percentages in Figure 1 are a synthesis of the authors analyses of multiple information sources. The key observation is that our social, environmental and individual health behavior factors impact up to 70% on the total cost and outcomes of care within the industry. Figure 1. Determinants of Health 1

In our digital world there are six primary DataStreams that can be applied to address health challenges: 1) Social Data; 2) Multi-omic (biological) Data; 3) Medical Data; 4) Financial Transactions

4 In our digital world there are six primary DataStreams that can be applied to address health challenges: 1) Social Data; 2) Multi-omic (biological) Data; 3) Medical Data; 4) Financial Transactions Data; 5) Digital data (from wearables, Internet-connected devices (e.g., IoT), mobile app use, etc., and 6) Public sources of data (e.g., census data, neighborhood crime and real estate reports, public health data and more). All of these six DataStreams are profiled in this article, with additional focus on health-related behaviors and data-driven SDoH factors. In today s world, healthcare decisions and treatments can be customized with the help of the data being created and tracked by nearly every one of us every minute of every day. II. The WE ARE DataStream Our focus includes understanding the many SDoH-related dimensions, and extracting targeted, relevant data points from the growing six DataStreams in productive ways that were not possible a few years ago. WE ARE is an easy way to understand all the underlying dimensions involved in analyzing the total impacts of SDoH factors. In the past the adage was you are what you eat. Today it is we are the data we generate! The summary of WE ARE below is expanded in greater detail throughout the article. Figure 2. WE ARE Data-driven Social Determinants of Health 2

5 W = Work - A person and their family employment circumstances can influence overall stress levels, physical impact on the body (excessive sitting or heavy, manual labor), mental health and overall lifestyle. E = Environment Where you live determines the quality of water, air and food available to you. The place where you grew up impacts early childhood development and the habits impacting your adult life. A = Abilities and Addictions - Each of us has created a positive set of abilities or skills that help manage activities of daily living. And each of us can have negative addictions (e.g., drug, food, Internet and others), and/or other forms of negative behaviors. R = Relationships - People with sustained, positive relationships have lower mortality rates. Loneliness and isolation are proven to negatively impact mental health and overall health status. The Relationships element includes the cultural context and social status surrounding us. E = Education - A person s education level strongly influences employment opportunities and social standing. Another component within the education category is health literacy, which is defined as the ability to understand and manage both the medical and financial complexities of our healthcare system. The imperative is to understand the SDoH dimensions and the underlying DataStreams available to our organizations to improve processes and create new solutions. This requires the wise application of data science, technology, processes and human ingenuity to develop solutions that deliver value and improve the human condition. III. Data Everywhere. Data Defines and Drives Our Lives. By 2019 it is estimated that 67% of the world s population will have a mobile phone 1. Our actions everyday create a vast number of digital data points recording our actions through the mobile and Internet-connected devices that digitize our lives. These digitized data trails are being bought, sold and traded every day. Every credit card purchase, Internet search, use of a mobile app and/or voice command to our virtual agents (e.g., Alexa, Siri or Cortana) is transformed into digital data that is analyzed and stored for future use by you or others. All of your personal data points are tracked and sold multiple times and become part of your digital data biography. This biography of You (or pieces of it) is stored across the databases of Google Ò, Apple Ò, Amazon Ò, Facebook Ò, mobile app creators and thousands of companies including data brokers. The data explosion will continue with over 200 billion IoT devices by 2020 sensing, tracking, and predicting our every action, based on Intel Corporation analysis. All of these connected devices generate a true tsunami of data to be bought and sold to accelerate consumer purchasing behavior, but can also be harnessed for health and wellness purposes. The health industry s challenge is how to use all of this collective and individual data to improve individual, 3

6 family, and community health status, while understanding and abiding by data privacy and security requirements and value-based boundaries. New data is generated every nanosecond from all of our collective actions, and the key challenges health leaders must address are: Data leadership; specifically, the growing talent gap is becoming more critical Data explosion accelerating Data complexity expanding, and Data velocity increasing. It is a general tenet that most people seek overall health and well-being. We spend our lives seeking good food (sometimes too much of that), supportive friends and family, clean water, fulfilling jobs and a sustainable world that we can all live in. Then illness strikes and changes the picture. The tenacity is for people and our health community as a whole to look for the quick fix in a pill or medical treatment. Upwards of 60 to 70% of the total cost of health care and outcomes improvement are related to SDoH factors and individual behaviors. The industry must continue the focused shift from reactive to preventive care through the use and analysis of new data sources throughout the entire health ecosystem. Successful organizations addressing this shift will incorporate strategic leadership, big data capabilities and infrastructure to ethically ingest and transform key data elements. These new sources of data elements must also be used intelligently to create and improve ways to structure clinical care and care management processes, including the use of non-traditional care supports (e.g. nutrition services, home health aides, transportation services). Want the complete chapter? Contact us: doug@efuturist.net dkasim@santesys.net 4

7 ABOUT THE AUTHORS Douglas Goldstein Douglas is a leader in accelerating growth of bio-health and digital companies through leadership and innovative business development that delivers value and results. As an entrepreneur and intrapreneur he has crafted innovative solutions using technology, data analytics, process improvement and human ingenuity. He is a thought leader in digital therapeutics, population health and precision health. He is the author of 11 books health and technology including ehealthcare: Harness the Power of e-commerce and e-care and Medical Informatics 20/20 Quality and EHRs through Collaboration, Open Solutions and Innovation. As a thought leader he has delivered over 300 speeches and workshops for leading health and life sciences organizations. Recently, Doug served as the Innovation Officer for the Inova Center for Personalized Health, where he led the development of new value and outcome-based clinical and business relationships with global life sciences and medical device companies. The Inova Center for Personalized Health is a 117-acre campus in Northern Virginia that is being transformed into a translational research, drug discovery and innovation center. doug@efuturist.net / Phone: Deanne Primozic Kasim (@DKasim) Deanne is an accomplished healthcare and health IT subject matter expert, researcher, consultant and speaker. Technology is ahead of current policy and regulation in healthcare and life sciences, and Deanne specializes in finding key opportunities amid change and chaos to create sustainable market and business advantages. Deanne is passionate about keeping the patient/consumer as the focus of the industry, despite the latest IT application, device or fad. Specialty areas of focus include: consumer empowerment tools and processes; the new generation of clinical and operational analytics; best practices to address the complex needs of safety net populations; care/disease management solutions; precision medicine; and emerging reimbursement and care delivery models. In her current role with Change Healthcare, Deanne interprets legislative, regulatory and industry trends to drive business decisions, and inform product strategy and roadmaps. Deanne is also the founder and managing partner of Santesys Solutions, a boutique research and advisory group focused on leveraging information and analysis to direct effective investments, healthcare programs, solutions and IT products. dkasim@santesys.net / Phone:

8 REFERENCES 1. Paul Sawers, 5 billion people now have a mobile phone connection, according to GSMA data, 2017, (Accessed March 15, 2018). 2. U.S. Centers for Disease Control, Sources for Data on SDOH, ( (Accessed March 20, 2018). 3. U.S. Centers for Disease Control, Data Set Directory, ( (Accessed April 10, 2018). 4. U.S. Centers for Medicare and Medicaid Services, Press Release, (( (Accessed April 14, 2018). 5. Amazon Web Services, ( (Accessed April 10, 2018). 6. Google, ( (Accessed April 9, 2018). 7. U.S. Office of Disease Prevention and Promotion, ( (Accessed April 10, 2018). 8. National Association of Community Health Centers, PRAPARE Implementation and Toolkit, ( (Accessed April 10, 2018). 9. Blue Zones Project, ( (Accessed April 10, 2018). 10. HICCup (Health Initiative Coordinating Council, 2018, ( (Accessed April 15, 2018). 11. Assessing the Impact of The Heart of New Ulm Project: A Population-Based Program to Reduce Cardiovascular Disease, a presentation at the American Heart Association EPI/Lifestyle 2017 Scientific Sessions. 12. Changes in cardiovascular risk factors after 5 years of implementation of a populationbased program to reduce cardiovascular disease: The Heart of New Ulm Project. American Heart Journal 2016, DOI: /j.ahj New Ulm community heart health screening data. 6

Advances and Perspectives in Health Information Standards

Advances and Perspectives in Health Information Standards HL7 Brazil June 14, 2018 W. Ed Hammond. Ph.D., FACMI, FAIMBE, FIMIA, FHL7, FIAHSI Director, Duke Center for Health Informatics Director, Applied