Healthcare Interoperability Poised to Solve COVID-19’s Big Data Crisis
Coronavirus highlights power of big data and the need for interoperability to improve population health. How can health plans lead the way?
What’s the single biggest weapon used by government, pharma, academic researchers, healthcare systems, and health insurers alike to combat the novel coronavirus pandemic? It’s data. Massive amounts of data. Unfortunately, we’ve said it before, and it bears repeating: healthcare has a data problem. And, like many things in healthcare, the current crisis has brought this deficiency into focus.
In this article we’re exploring the many uses of big data for the coronavirus and beyond and how health plans can overcome the obstacles to ingesting and processing data from a myriad of sources to achieve interoperability, positively impact population health and secure their competitive advantage.
Big Data and the Coronavirus: A Unique Use Case
Already, work involving advanced analytics applied to real-world data is seeing success in combating COVID-19. By analyzing publicly available datasets, scientific literature, social media information and their own data, progress of a sort has been made by different groups: from predicting adverse events in coronavirus patients to rapidly developing potential vaccines. But the propensity for healthcare, academics and industry to stick to their silos – and their information right along with them – has limited their potential for reliable successes.
Challenges to leveraging healthcare data
Despite generating a ton of healthcare data – most of it now digital – much of that data is still incomplete, irrelevant, inaccessible or a combination of these. And the sheer volume makes it difficult to overcome these deficiencies. By some estimates, we’re generating over 2,300 exabytes per year (one exabyte = one billion gigabytes), which is expected to grow at least 36% year over year through 2025.
While compute power has evolved to handle the sheer amount of information, this data is locked in silos. In the absence of clinical trial data – the gold standard – real-world clinical information from COVID-19 patients is the most useful in guiding medical decisions. Thanks to a decades-long push to digitize healthcare information, this data exists inside electronic health records. Despite the promise of digitization, EHRs have not made it easy to retrieve this crucial data.
Built as they were with billing efficiency in mind, most of the useful clinical data is stored as unstructured free text. And without a common architecture, labels are inconsistent, which makes sharing difficult – even in rare cases where data is complete. There are reports of providers unable to deliver detailed clinical data on coronavirus cases, largely because it would have to be printed or tediously copied from EHRs, then sent by fax or email, or manually entered into CDC forms.
Interoperability and collaboration offer keys to success
The new rules against information blocking have been delayed to free up resources devoted to the pandemic response, but the need for data interoperability has never been greater. When health data is shared, front-line providers are informed in real time on patient movement, health changes and diagnoses, allowing them to respond smartly.
According to the Office of the National Coordinator for Health IT’s Don Rucker, M.D., the current COVID-19 pandemic is a clear example of why the data sharing regulations are so critical. “Ironically, if we had this rule several years ago, we would be in a far better spot for knowing what’s going on with this pandemic. There are fundamental things about the biology of this virus that we don’t know, such as latency, duration of disease and how immunity is built up. It would be easier if we had richer clinical information streams.”
One success story demonstrates just how essential data interoperability is to identifying vulnerable populations and performing targeted outreach. The regional data network had already taken the steps to integrate health information from numerous providers in the area, so they were well positioned to respond quickly during the COVID-19 pandemic. But they were still limited to barely more than a third of the county’s population in this initiative, which shows there’s still plenty of work to be done.
Other successes tell a similar story. Working together, sharing information – even among competitors and others that don’t traditionally collaborate – accelerates the path toward viable coronavirus solutions. Making quality data more readily available should be the goal. As one expert in public health research puts it, “How can we continue to work together and invest in these infrastructures so that we can collect data, share that data, and analyze that data rapidly in pandemic situations? Or even in smaller-scale situations, like a localized outbreak of food poisoning or salmonella?”
Where is all this data coming from?
In 1950, the doubling time of healthcare data was 50 years; in 1980, 7 years; and in 2010, 3.5 years. Today, that rate is 0.2 years—just 73 days. These increasingly varied sources of digital data all offer value, though few health plans are able to ingest and parse all of them.
- EHR
- Claims systems
- CRM
- Rx data
- PACs
- Lab data
- Clinical Trial Management systems
- ACOs/HIEs
- Genomics and research registries
- Wearables
- Apps
- IoT
- Chatbots
- Medical devices and sensors
- Social media
- Machine logs
- PHR systems
How Health Plans Can Push Data Interoperability Forward
Now that the pandemic has reinforced the need for improved sharing of healthcare information, what comes next? Like the push for EHRs to streamline healthcare billing, it’s likely health plans will again have to lead the charge in the journey to healthcare data interoperability. We outlined before 4 steps health plans can take to comply with the new information blocking rules. In addition to technical compliance, there are 3 things health plans can do to promote interoperability more broadly in the industry.
1. Adopt modern technology with interoperability in mind
The assortment of fragmented technology and manual systems currently in use at many health plans will no longer cut it. Every internal operations system – the claims adjudication system, CRM, fraud detection, payment integrity, provider outreach tools, member service chatbots and everything in between – must be able to “talk” to each other. Moreover, two-way interaction between external provider systems like EHRs and members’ apps of choice also will be required. Advanced integrative technology platforms like Pareo leverage modern APIs built on the FHIR standard to support interoperability.
2. Use A.I. to process data
Once health plans have ingested data from myriad sources, processing that information into real-time insights is the next logical step. But even with data interoperability standards in place, healthcare information is still likely to be largely inconsistent and unstructured. Applications of A.I. like supervised and unsupervised machine learning, natural language processing and more can help overcome these challenges, turning raw data into visualized business insights.
3. Share insights
Once a health plan has done the dirty work of ingesting and analyzing healthcare data, that’s where the real value of promoting interoperability comes in. Sharing insights with relevant stakeholders – providers, members, even other health plans – builds trust and the ability to realize the benefits of big data across the healthcare continuum.
Benefits of Big Data Interoperability
While healthcare data interoperability promises many benefits during a pandemic, innovations pursued now promise to pay dividends long into the future. We’ve written about a few of these during our recent series of articles covering long- and short-term effects of COVID-19.
For one, without data interoperability, the transition to value-based care is a non-starter. Sharing mutually beneficial information with providers is the foundation of fostering these valuable relationships. It’s up to health plans to take the reins on opening the lines of communication with providers, and supporting them with relevant clinical information can help them reduce costs while improving care.
The coronavirus pandemic has unfortunately affected members as well, particularly their healthcare coverage and finances. As a result, they have been more likely to delay needed care – even for chronic conditions that make them more vulnerable. At the same time, they are signaling they are more open than ever before to receiving communications from their health plan. This convergence provides an ideal opportunity for health plans to leverage big data insights for population health management efforts. Advanced technology like Pareo surfaces lists of those members most likely to need engagement and care to improve healthcare access, outcomes and quality.
Finally, greater information sharing allows health plans to make more informed decisions faster. Where are the errors, areas of high-risk and opportunities for driving changes? Access to the “big picture” ensures strategic planning that secures a health plan’s competitive advantage.
Health Plans Find Success with Tech-Forward Strategies
COVID-19 has thus far proved to be a harsh but effective teacher, not least by emphasizing the need for an interoperability record that helps to provide comprehensive clinical insights with a 360-degree view of members and patients. This initiative is only feasible through advanced technology. Those health plans with digital-first strategies already in place are better set up for success, but payers that lag can still make progress and secure their competitive advantage.
By adopting scalable comprehensive technology and leveraging modern interoperability standards, health plans can position themselves to excel at payment integrity, coordinated communication and population health efforts alike. As the COVID-19 crisis evolves – and in readiness for when the next healthcare crisis presents itself – payers will be able to lead the way in identifying those at risk based on their clinical predisposition, genetics, social determinants of health, and other factors as well as coordinating member and provider engagement.
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