Big data can be used to make a big impact on health benefits by dropping costs, improving quality and patient health, all in real time.
Over the past several years a term that consistently finds its way into many data and analytics discussions is: “BIG DATA”. Although the term seems simple enough (large amounts of data), most experts suggest the real definition of the term goes well beyond the quantity of data:
“Extremely large and diverse datasets that may be analyzed to reveal patterns, trends, and associations, that could lead to better decisions.”
Put this way, Big Data offers an opportunity to make an immediate and lasting impact in the cost and quality of health benefits. Let’s explore for a few minutes the connection between Big Data and health benefits, and more importantly, how we can leverage it to “reveal patterns, trends, and associations” that could result in “better decisions” across the full health benefits spectrum and ultimately reduce cost and improve quality of care in real-time.
LARGE AND DIVERSE DATASETS
Healthcare is at the epicenter of Big Data with massive amounts of data created from a myriad of healthcare activities that result from patients and providers managing health. More specifically, any time a patient visits a healthcare provider (physician, pharmacy, lab, etc.) many rows of data and countless data elements are being captured and curated into usable datasets. The National Institutes of Health estimated in a report from 2016 that data from EHR systems in the U.S. will hit 25,000 petabytes annually by 2020 which is up from just 500 petabytes in 20121(1 petabyte = 1 million gigabytes). This estimation does not take into account the many other sources of healthcare data including medical and pharmacy claims data. Rest assured, the size of data in the larger healthcare domain meets the “extremely large” requirement of Big Data.
REVEAL PATTERNS, TRENDS, AND ASSOCIATIONS
Let’s consider the impact of leveraging Big Data to identify trends within a very specific area of health benefits. Increased pharmacy benefit spending predominantly fueled by increased utilization of specialty medications is a widespread, well-known, and persistent trend. However, determining the root causes, the micro and macro impact, and the best strategies for managing this trend requires a deeper analysis across much more than just pharmacy claims data. It requires accessing and analyzing diverse datasets that relate to one another in some way, comprising Big Data.
Although there are a host of methodologies to analyze Big Data to elicit previously undiscovered trends including data mining, BI platforms, predictive analysis, artificial intelligence, etc., the only way to get the full picture into patient health patterns, trends, and associations is by expanding the reach into all other accessible data sources that will provide much more clarity into what can be done to drive up quality and reduce cost. For example, combining pharmacy and medical claims data with medical records is a solid start for enriching data resources. Intensifying the data search by adding pharmaceutical research, consumer behavior, or even employer data when available will further identify distribution, quality, utilization, management, and/or cost trends that were likely obfuscated when analyzing pharmacy claims in a vacuum.
Ultimately, the desired end result is improvement. Whether improvement comes through lower cost, more appropriate utilization, or other ways depends largely on our ability to use the data and inferred trends to make better decisions.
Consider the following results from a poll conducted by Geneia/National Alliance of Healthcare Purchaser Coalitions2:
97% of employers believe that advanced analytics are essential for making benefits and/or wellness program decisions
90% said that near-real-time data is imperative to realizing costs savings
83% agree that using advanced analytics to understand how employees use healthcare services, who the high-risk employees are and how to intervene effectively is the only way to lower costs and improve financial results
Nearly all employers surveyed feel that making benefits decisions to effectively manage their programs requires real-time use of massive amounts data. However, they also struggle with the ever-growing massive amounts of data and their inability to quickly make informed decisions. They can see the intended results of Big Data but are struggling to effectively use it.
A BIG OPPORTUNITY FOR HEALTH BENEFITS
All the necessary ingredients for a valuable transformational market change is at our fingertips that will enable us to more fully optimize health benefits through Big Data:
We have mountains of healthcare data at our fingertips that continues to accumulate at an accelerating pace, yet we still predominantly depend on individual silos of data to make crucial decisions.
We have access to comprehensive and highly accurate tools that will enable careful analysis of the data to identify trends and patterns in cost and utilization, yet we largely still request the same tired reports that look for the same problems that have existed for years.
Artificial intelligence, automated data analysis, and smart alerts are proven technologies to help us make incredibly informed decisions in real-time about individual and population health, yet we are still utilizing annual client reviews as a delivery mechanism for making recommendations and encouraging decision making.
Despite the relatively complicated nature of Big Data, leveraging it within health benefits to achieve desired results is within our grasp. The big opportunity for health benefits is for employers, brokers, providers, administrators, and benefits managers to work together to expand their ability to deliver cost and quality results by fully embracing the expanded definition of Big Data: “extremely large and diverse datasets that may be analyzed to reveal patterns, trends, and associations, that could lead to better decisions.”
Brandon Newman has 25+ years working in managed care. He is the CEO and Founder of Xevant and Co-Founder of ScripPoint
1. Clemens Scott Kruse, MBA, MHA, MSIT, PhD,Challenges and Opportunities of Big Data in Health Care: A Systematic Review, JMIR Med Inform, 2016 Nov 21, Web, https://medinform.jmir.org/2016/4/e38/
2 Survey Finds Advanced Analytics Are Important Healthcare Decision Making Tool for Employers, Information Gap Exists Between Users and Non-Users, National Alliance of Healthcare Purchaser Coalitions, 2016 Oct 12, Web, https://www.prnewswire.com/news-releases/survey-finds-advanced-analytics-are-important-healthcare-decision-making-tool-for-employers-information-gap-exists-between-users-and-non-users-300342190.html