Healthcare Executive Roundtable: Transforming Healthcare Outcomes through Blockchain and Data Analytics
Thursday, September 20, 2018 | 8:00 AM – 12:00 PM
Mid-America Club | 200 E Randolph St | 80th Floor | Chicago, IL 60601
About the roundtable
Chronic diseases, such as diabetes, cardiovascular disease, and obesity, are some of the costliest and most preventable diseases in the United States. According to a 2017 RAND Corporation analysis of 2014 Medicare Expenditure Panel Survey data, 90% of total healthcare expenditures were for individuals with one or more chronic disease, which make up around 60% of the U.S population. Authors of the same report found that, on average, individuals with five or more chronic diseases (12% of the population) spend 14 times more for healthcare services than individuals with no chronic diseases. (i)
Often, these diseases disproportionately affect patients of color, a population that faces the most acute healthcare disparities. According to the Centers for Disease Control and Prevention (CDC), the rate of diagnosed diabetes is 77% higher among non-Hispanic blacks, 66% higher among Hispanics, and 18% higher among Asians than among non-Hispanic whites. (ii) Another recent report found that African American women aged 18 to 44 were six times more likely to be hospitalized for high blood pressure than white women of the same age group. (iii) And the problem is not just national. Within Illinois, heart disease or stroke is responsible for 1 in every 3 deaths. (iv) Both conditions are more likely to affect patients of color, and heart disease is the leading contributor of the racial disparity in life expectancies. These disparities are also present in healthcare costs — a 2013 American Diabetes Association study found that African Americans have the highest per-capita healthcare costs for diabetes treatment: $9,540 compared to $8,101 for whites and $5,390 for Hispanics. (v)
As chronic diseases continue to disproportionately impact the most vulnerable, at-risk, and underserved patient populations, healthcare organizations and the entire industry must prioritize reducing healthcare disparities and creating a more equitable healthcare system for all. This effort is particularly important as the U.S. continues to undergo one of the most dramatic demographic shifts in our nation’s history.
For organizations that make addressing these challenges a priority, the proliferation of data analytics could hold the key to addressing the cost drivers of chronic diseases. Over the past decade, the amount of electronic healthcare data collected and stored has increased sharply. According to the CDC, the number of office-based physicians using the most basic of EHR/EMR systems to collect patient data was 18% in 2001. (vi) The physician participation rate has risen dramatically to 87% during the last CDC survey in 2015. (vii) According to the AHA, since 2008 the hospital adoption rate has risen from 9% in 2008 to 84% in 2015. (viii) Leveraging the power of this data to understand how to better prevent, manage, and treat chronic diseases can have a significant impact on reducing costs.
Over this same time period, healthcare technology has evolved in both complexity and the ability to capture more patient data. The increased adoption of EMRs means there will soon be over one billion patient encounters digitally recorded and stored each year, according to the NIH. (ix) This new abundance of data provides information on diagnosis, genetics, medications, and treatment approaches that was never before available. Furthermore, as blockchain develops and becomes more prevalent in the industry, healthcare technology systems may become interoperable — payers and providers may be able to more easily access longitudinal patient health information that is not currently accessible due to disparate technology systems. With a long-term, comprehensive view on individuals’ health, blockchain can facilitate the process of identifying variables that are most associated with chronic diseases and health disparities.
The sheer volume and velocity of data outpaces human cognition. At AArete, we leverage advanced analytics and machine learning to realize the potential of big data analytics for medical advancement. This ocean of new data allows us to sail to a new age of healthcare, one with answers to the most complex population health questions. With the proper analytics, payers and providers can reach out to patients at risk of developing diabetes, hypertension, or COPD. This actionable intelligence allows for prevention, early intervention, patient engagement, and the application of evidence-based medicine, which are keys to increasing quality outcomes and reducing overall cost.
The Center for Healthcare Innovation’s and AArete’s 6th annual Healthcare Executive Roundtable brings together healthcare executives, key opinion leaders, and patient groups for an intimate and collaborative discussion on the intersection of data analytics and health disparities. The exclusive, limited-attendance roundtable is designed to provide the top thought leaders with the latest insights and ideas on how data analytics can address some of the large-scale health equity challenges that are driving costs and impacting our healthcare economy. The half-day roundtable brings these leaders together for a morning of collaboration and co-learning.
Distinguished Welcoming Remarks
Mr. Loren Trimble, MBA, CPA, is the Founder, CEO, and Managing Director of AArete, a global management consulting firm. His primary focus is setting the strategic direction of the firm and creating and molding AArete’s go to market strategy and execution. In addition to Mr. Trimble’s primary focus, he also plays a significant role in thought leadership for the firm and is at the core of AArete’s Knowledge Management CenterTM. Mr. Trimble lives and breathes every day his passion for excellence with AArete’s personnel and clients. Mr. Trimble has extensive business and operations strategy experience, serving clients globally in the following industries: healthcare- provider, payer and pharmaceutical, as well as higher education, distribution, consumer products, and business services. Specific areas of expertise include strategic cost reduction, revenue optimization, pre- and post-merger valuation and synergy integrations, and advanced data analytics. Before founding AArete, Mr. Trimble was a Managing Director and Strategic Sourcing Practice Lead at Huron Consulting. Before Huron, Mr. Trimble started the Strategic Sourcing services for Arthur Andersen, developing the methodology and refining the approach through numerous client engagements. Mr. Trimble has presented for a number of organizations and authored numerous articles. Mr. Trimble holds a Masters of Business Administration from The University of Chicago and a Bachelor of Accounting from The University of Iowa. Mr. Trimble is a CPA. He is a long term member of Rotary International and the AICPA.
Registration, Breakfast, & Networking
Introduction to Blockchain
Lunch & Networking
i. Buttorff, C., Ruder, T & Bauman, M (2017). Multiple Chronic Conditions in the United States. Retrieved from www.rand.org/content/dam/rand/pubs/tools/TL200/TL221/RAND_TL221.pdf.
ii. National Diabetes Fact Sheet, 2011: Fast Facts on Diabetes. (2010). Retrieved from https://www.cdc.gov/diabetes/pubs/pdf/ndfs_2011.pdf
iii. Cooper, S. R., et al. (2015). Elevated Hypertension Risk for African-Origin Populations in Biracial Societies: Modeling the Epidemiologic Transition Study. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4476314/
iv. Chronic Disease Burden Update, (2014). Retrieved from 2015http://dph.illinois.gov/sites/default/files/publications/volume3issue1feb2014womencvh.pdf
v. Kelly, L. R., (2015). Kelly Report: Health Disparities in America. Retrieved from https://robinkelly.house.gov/sites/robinkelly.house.gov/files/2015%20Kelly%20Report_0.pdf
vi. Hsiao, C. J., et al. (2014). National Health Statistics Reports. Retrieved from https://www.cdc.gov/nchs/data/nhsr/nhsr075.pdf#x2013;2012%20%5BPDF%20-%20347%20KB%5D%3C/a%3E%20
vii. Jamoom, E. & Yang N. (2016). Table of Electronic Health Record Adoption and Use among Office-based Physicians in the U.S., by State: 2015 National Electronic Health Records Survey. Retrieved from https://www.cdc.gov/nchs/data/ahcd/nehrs/2015_nehrs_web_table.pdf
viii. Henry, J. W. et al. (2016). Adoption of electronic Health Record Systems among U.S. Non-Federal Acute Care Hospitals: 2008-2015. Retrieved from https://dashboard.healthit.gov/evaluations/data-briefs/non-federal-acute-care-hospital-ehr-adoption-2008-2015.php
ix. Ross, M. K., Wei W. & Ohno-Machado L. (2014). “Big Data” and the Electronic Health Record. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4287068/