Guest Column | January 27, 2020

9 Technology Megatrends For Healthcare In 2020

By Scott Hampel, MedeAnalytics

Field Mobility Trends

Now that we’re one month into 2020, it’s becoming clear the data produced in the healthcare industry by providers, consumers and payers will power and propel our 9 megatrends. Healthcare data is the foundation on which we’re building everything from healthcare outreach for the underserved to new of Things-based healthcare programs to treatments designed just for you.

The thread that ties each megatrend to the next is data. Every megatrend has data at its foundation. And the challenge patients, providers, and payers will face is extracting and making sense of the 2,314 exabytes of healthcare data expected to be created this year.

The data exists, but do we really understand it? Can we use it to improve health? How will we protect it? In some ways we have, but there’s much work to do in the future. Without the use of high-powered data analytics, artificial intelligence and the internet of things, much of this data would simply sit unused and 2020 megatrends would be nothing more than ideas on a blackboard.

These are the healthcare technology megatrends for 2020.

  1. Healthcare Consumerism Continues Apace

A few years ago, healthcare consumerism was primarily defined as knowing your cholesterol numbers, keeping track of a few other personal health statistics and ensuring your doctor understands your wants and needs. Now, healthcare consumerism much more complex and complicated because of the use of wearables and internet-connected health devices, including smart speakers and at-home diagnostic devices, which create considerable amounts of data.

 “We are seeing a much larger focus on digital technologies and taking advantage of the analytics, data, and the technology that is out there,” explained Ferris W. Taylor, HealthCare Executive Group executive director. “Those have changed quite dramatically in the last five years or so. Data is much more readily available and it’s broader than just administrative data. We now have clinical data, lab data, social, economic, and demographic data. The analytical tools also are much more sophisticated.”

In addition to these larger initiatives, wearables are coming into their own. The wearables market continues to grow. In 2019, nearly 58 million people in the US, or 22 percent of the population, had wearables. By 2022, it’s estimated 67 million or 25.3 percent of the population will have them. Wearables and other healthcare devices connected to the internet could save the healthcare industry $300 billion by potentially reducing the need for some office visits.

Healthcare consumerism will continue to increase in 2020 as technology improves and drives new, faster and more robust wearables and home-based IoT devices are integrated with wearables, healthcare apps, and healthcare providers.

  1. Data Security And Privacy Will Be Tested

Every part of healthcare is producing massive amounts of data each day. Data is an appropriate segue to the next topic: data security and privacy.

There is a tacit agreement between the healthcare consumer and companies that these organizations will harvest and use their data. The healthcare consumer uses the website/app/wearable/smart speaker and the agreement is the company will use the data in just about any way it wants. This understanding, mostly unspoken, but seeing the light of day more often hasn’t stopped many people from using the devices, websites, and apps, although one study found Americans were slightly less likely to share basic information, like first and last name and address in 2019 compared to the previous year.

Our private health data, really all our data, face many risks. As data floats through the internet ether and eventually arrives at a multitude of servers owned by companies with varying levels of security, a lot of it will find its way to bad players interested in exploiting the information. Data exposed through hacks, phishing or lax data security protocols will make healthcare consumers wary and will negatively affect the healthcare industry’s reputation and finances. Healthcare data breaches cost the industry $4 billion in 2019. In 2020, it’s expected to be worse: More than 93 percent of healthcare organizations have experienced a data breach since Q3 2016, and 57 percent have had more than five data breaches during the same time frame. Not only has the number of attacks increased, but more than 300 million records have been stolen since 2015, affecting about one in every 10 healthcare consumers.

Unfortunately, in most cases, once a healthcare consumer’s data is stolen, it’s impossible to get it back.

As for data privacy, nonprofits and government entities are working toward protecting all consumer data, including healthcare data. “State-level momentum for comprehensive privacy bills is at an all-time high,” according to the International Association of Privacy Professionals. “After the California Consumer Privacy Act passed in 2018, multiple states proposed similar legislation to protect consumers in their states.”

No matter who’s involved in and responsible for securing personal health information—companies or the government—it ultimately falls to healthcare consumers to be hyper-vigilant and take the steps necessary to protect their data and ensure its use falls in line with their wishes.

  1. Advanced Artificial Intelligence Goes Commercial

Advanced AI is moving away from opensource to commercial models for good reason. Open-source AI is generally opaque, however commercial models are frequently transparent and show the model used to arrive at an answer. If you’re using AI to question the validity of the physician's decision, for example, you need to know how the AI came to its conclusion. Data transparency must be very clear to ensure understanding.

Advanced AI is getting easier to use and more, generally, more available in healthcare. Many advanced AI companies now offer a library of AI models. Just select the model you want to use that applies to the problem you want to solve.

As we enter a new decade, transparent AI code and libraries of AI models will become the norm.

Practical use of AI in healthcare will continue to grow in 2020. It is far more important to use AI to drive healthcare value for all stakeholders—payers, providers, and patients—rather than employ it as a novelty designed to simply draw attention.

  1. Price Transparency Levels The Playing Field

I was asked recently, “If you could snap your fingers and solve one industry problem, what would it be?”

Price transparency would have to at least be in my top three challenges to solve. Healthcare pricing is just too complicated and secretive. There’s too much variance around the price of care across the nation. Most of the U.S. economy revolves around consumers purchasing goods and services based on known prices. It’s obviously somewhat of a Gordian Knot at this point with many historical contracts between payers, providers, and the government.  

The federal government is attempting to untangle the knot with new legislation designed to expose healthcare costs to healthcare consumers. “Hospitals will soon have to share price information they have long kept obscured — including how big a discount they offer cash-paying patients and rates negotiated with insurers…,” explains Kaiser Health News. “In a companion proposal, the administration announced it is also planning to require health insurers to spell out beforehand for all services just how much patients may owe in out-of-pocket costs. That measure is now open for public comment.”

There are, however, several lawsuits that have already been brought against the administration by hospitals seeking to keep the information secret.

  1. Telehealth Eliminates Distance

While telehealth has been a part of healthcare for decades, it wasn’t until the advent of faster computers, ubiquitous internet service, and easy-to-use peripherals that it really came into its own and made sense practically and financially to use as a large-scale method for education, diagnosis, and treatment.

“A growing number of physicians are overcoming the barriers of time and space to deliver the right care to patients when they need it, without patients ever having to leave the comfort of their own homes,” according to the American Medical Association.

In addition to using telehealth for those who may live a long distance from a healthcare provider, the service is becoming commonplace for the times when patients who live near a hospital, clinic or urgent care center don’t feel well enough or have the time to leave their homes. Telehealth has become an additional perk offered through health insurance.

As technology continues to advance, the challenge will be keeping up with the data produced by telehealth. We will have more opportunities to use telehealth to improve patient health and wellness, but we also must keep in mind that the additional produced from provider/patient contact must be integrated into the larger health record. Tapping into serious data management solutions will be crucial to extract information from this data.

  1. Precision Medicine For Individualized Treatment

By now many of us are familiar with and may have used DNA-based ancestry services. You swab your mouth and send it to a company that extracts and runs your DNA. Then the company returns a report detailing your heritage.

Precision medicine uses an individual’s DNA, and many other health markers, in much the same, but with a twist. DNA can be used to create customized medical treatments. “With its potential to improve treatment options and clinical outcomes for any number of diseases—including costly, hard-to-treat diseases such as cancer, neurological disorders, and rare genetic conditions—precision medicine is a growing area of interest for many health systems,” according to the Center for Connected Medicine. “Health systems are optimistic that the science will continue to advance to help providers use genetics and other individual variables to create novel treatments.”

While healthcare organizations are looking toward Precision Medicine to improve patient care and outcomes (83 percent), very few are ready to roll it out to patients today (70 percent say they have low maturity or have yet to deploy Precision Medicine), according to the Center’s report.

Nevertheless, there is a strong interest in developing more treatments using the concept. Significant amounts of healthcare data, including that used in Social Determinants of Health (SDH), will be needed to make Precision Medicine viable.

The NIH, through its All of Us Research Program, is working to collect the “largest, richest biomedical dataset of its kind” to support Precision Medicine.

  1. 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 U.S. 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.

  1. 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 healthcare 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:

  1. $3.6 trillion of annual spend in the U.S. 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.
  2. 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 percent trust in it.
  3. 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.

  1. 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;
  • Food;
  • Transportation;
  • 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 healthcare 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 I believe 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.

These are the success stories I’m looking forward to in 2020.

About The Author

Scott Hampel is president of MedeAnalytics.