By Scott Hampel, president of MedeAnaltyics
We conclude our 2020 Megatrends with an exploration of new players entering healthcare, the necessity and importance of data interoperability as well as social determinants. While each of these topics appear at first glance to be unconnected, there is a single thread that links them all: data.
Now on to 2020’s final Megatrends:
7. Unfamiliar healthcare players enter the fray
Amazon, Best Buy and Salesforce, well-known consumer-focused retailers (the former) to companies primarily familiar only to those in marketing or related fields (the latter), want to get into the healthcare, and they aren’t scared of the traditional barriers that have caused others to take a second look before embarking on the healthcare journey.
These businesses have two things in common when it comes to entering the healthcare arena:
- Access to a considerable amount of data; and
- Years of perfecting customer service.
“The US health industry is undergoing seismic change generated by a collision of forces,” according to the PwC Health Research Institute, “including the shift from volume to value, rising consumerism and the decentralization of care.”
This collision is helping new players enter the healthcare game at a time when healthcare consumerism is on the rise along with all the costs associated with healthcare. “Consumers are spending mostly their own money for basic healthcare services, and they want to see value for that money like they do in other industries. They want reasonable prices, convenient hours and locations, and great service—not exactly attributes for which traditional doctor’s offices or hospitals are known,” according to consulting firm Oliver Wyman Health.
Healthcare consumers appear willing to give an unknown healthcare entity like Amazon a try. Part of this willingness may stem from the fact that all patients are consumers. “Retailers put consumers in control, and their spaces are inspiring and engaging, whereas the traditional medical experience means waiting in a sterile, intimidating environment,” according to an article at HealthSpaces.
For success, these early entrants need to understand the huge amount of data they already have and will collect after starting new programs. The only way to that is through a comprehensive enterprise analytics program that brings understanding to the data by converting it into actionable information. Without analytics, including predictive analytics, simply having exabytes of healthcare data sitting on servers isn’t worth much to anyone and therein lies the dilemma. While many of these businesses have a considerable amount of data and will create even more, it remains to be seen how they will work with healthcare data, although Amazon, for example, has already taken steps in this direction.
No matter how the movement of non-traditional healthcare businesses plays out, data (how it’s used and interpreted) will decide the winners and losers.
8. Interoperability saves the day
Today, healthcare payers and providers are spending nearly $30 billion every year on analytics and using more than 415 different vendors for their analytics needs. This is a tremendous waste of resources and time. In time, we’ll see an accelerating trend toward interoperability of analytics solutions that cross clinical, financial and operational boundaries to enterprise analytics solutions.
The National Academies found, however, “Interoperability and data sharing between health care and social care are hampered by the lack of infrastructure, data standards, and modern technology architecture shared between and among organizations.”
I believe there are three reasons interoperability and analytics are difficult to implement in healthcare:
- $3.6 trillion of annual spend in the US and an estimated $1 trillion of it is wasted per a CMS research study. That results in an almost limitless amount of use cases for analytics.
- Recent digitization of healthcare is propelling massive growth in data, reaching 25 zettabytes by 2025. That is absolutely an ocean of data. There are thousands and thousands of different data sources. All of it needs to be painstakingly harmonized into consumable data formats. In healthcare, people make life or death decisions, particularly with clinical data, so there must be 100% trust in it.
- Data literacy, generally, is low. It’s still a relatively new field in terms of mainstream adoption. So, people struggle to understand and consume analytics. And in healthcare, there’s just a multitude of different consuming constituents, who all have different levels of knowledge and interest in the topic.
Enterprise analytics will dramatically increase the speed and efficacy of population health programs because when you have both fresh claims-based data and clinical analytics you can diagnosis, intervene and engage in care management programs far faster and with much greater confidence in the data and results. Enterprise analytics for the enterprise is where healthcare will be moving in 2020.
9. Social determinants of health for all
Many challenges face healthcare’s underserved. There are issues with food, housing, reliable transportation, steady employment, behavioral and mental health, and more. Each contributes to and is one element of SDH.
In communities around the world, public and private organizations are taking steps to address SDH-related issues and challenges that negatively impact a person’s health.
For the healthcare industry to find its way to new and innovative SDH programs and to identify those who may benefit, they must be found. While some organizations use referrals following face-to-face meetings with prospective program members, predictive analytics can be utilized to identify many potential enrollees quickly and efficiently, as well.
“Analytical capabilities in healthcare can be used to identify patterns of care and discover associations from massive healthcare records, thus providing a broader view for evidence-based clinical practice,” according to an article published in Technological Forecasting & Social Change. “Healthcare analytical systems provide solutions that fill a growing need and allow healthcare organizations to parallel process large data volumes, manipulate real-time, or near real-time data, and capture all patients’ visual data or medical records. In doing so, this analysis can identify previously unnoticed patterns in patients….”
Predictive analytics uses a large dataset and an algorithm to, in this instance, identify people who may benefit from help. The data could come from a variety of healthcare or socioeconomic sources, including healthcare facilities and community organizations, and might contain information about:
- Chronic conditions;
- Geo-spatial figures; and
- Billing codes.
The nonprofit eHealth Initiative identified data as crucial to understanding SDOH. “The importance of SDOH data in contributing to the complete picture of individuals and communities cannot be underestimated,” according to the organization.
An issue, however, is the slow adoption of predictive analytics in the healthcare industry at-large. “(R)ecent developments in data analytics also suggest barriers to change that might be more substantial in the health care field than in other parts of the economy,” according to an article published by Brookings. “Despite the immense promise of health analytics, the industry lags behind other major sectors in taking advantage of cutting-edge tools.”
Data on its own is inert: just waiting to be understood and then used. And that’s a major challenge for many organizations. It’s often trapped in different applications with no easy or convenient way to extract it. The National Academies of Sciences, Engineering, and Medicine released a report on social determinants and the ways it can be better incorporated into healthcare to improve health outcomes, and health and wellness. Data is a big part of making social determinants successful worldwide.
Recognition that data is the problem and the solution will be crucial to integrating social determinants within healthcare at-large in the future.
2020 and beyond
Every 2020 megatrend depends on data and analytics. Everyone involved in healthcare—from healthcare providers to payers to patients to the government—must work toward understanding, securing and managing the data they produce and control.
Healthcare, in general, is behind in terms of analytics adoption, but a big part of it is because of the complexity and magnitude of the environment in which we work.
Nevertheless, there must be a concerted effort among those involved to use analytics more. There will be hiccups along the way, more data breaches, companies that overstep or shirk their fiduciary responsibility, but there also will be many accomplishments, and new medical treatments and health services developed thanks to the use of data and analytics.