Practicing for the Next Pandemic with Real-World Data (RWD)

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Mac Bonafede, Ph.D., MPH, VP of Real World Evidence at Veradigm

Data reporting challenges during the current pandemic relate to the lack of connectivity between public health and information technology (IT) reporting systems throughout the country. While access to real-world data (RWD) helps address this situation, the solution goes beyond simple accessibility.

Real-world data represents data collected outside of randomized clinical trials, such as patient data from electronic health records (EHRs), mobile and smart devices, claims and billing activity and patient data registries. RWD is data that was most often collected for some purpose other than research or evidence generation. Because of this designed broader use, RWD typically includes information from a broader group of patients rather than a specific population and disease status in a clinical trial.

Generated from RWD, real-world evidence (RWE) results from a series of processes that must happen in a specific order. Embedded in this process is the origination of the RWD that sits at the core of any RWE insights development. Before being available for RWE generation, the underlying data element needs to move through the clinical workflow, and the parallel data generation process, before it gets into the hands of researchers. By nature, this process is often a commercial activity so the connection between IT and public health has not always been the highest priority.

The COVID-19 pandemic upended that relationship by making public health the single highest priority, forcing but also empowering RWD providers to look at their data in new and creative ways to identify more actionable information out of their data, faster. As with everything in the COVID-19 pandemic, the definition of ‘fast enough’ changed.

A Shift in the Framework for Thinking about RWD

The “practice” for the next pandemic must recognize that the conditions where people live, learn, work and play affect their health and health outcomes, that is, the social determinants of health (SDoH) as defined by the Centers for Disease Control and Prevention. The inclusion of SDoH data in patient data registries requires a shift in the framework for thinking about RWD.

This evolution was underway before the Covid-19 pandemic. RWD is developed and maintained for purposes other than research where these data become tools to guide or document clinical management, healthcare payment, regulatory decision-making and treatment protocols. RWE researchers must continue to push on those underlying non-research activities to include SDoH measures, especially when they are not a necessary part of those underlying activities that generated the data.

For example, a patient’s socioeconomic status is not needed to facilitate payment for a medical claim. However, if we captured that data element, we could gain a better understanding of how socioeconomic status relates to payment for healthcare services, potentially including the likelihood of receiving appropriate follow-up care or treatment persistence. The claims adjudication process is simply focused on facilitating payment but leaving out these SDoH elements precludes any deeper analysis, including predictive analytics, that could inform and improve the claims payment process. The painful reality is that the need for better SDoH data through RWD is not new. These efforts were underway, but the pandemic was a stark reminder that these gaps have undeniable but avoidable consequences.

Untapped Real-World Data Resources

Researchers know disparities and gaps exist, a reminder that better, more timely data can help prioritize where to focus as challenges emerge. Proactive development of tools, such as the Covid-19 Dashboard, will help guide outreach to underserved communities in the next pandemic. Tools like this can help proactively seek out areas with anticipated disparities in care, regardless of the reason for those disparities (e.g., reduced access, patient reluctance). They can also help challenge assumptions about what researchers think they know about utilization and access patterns.

Large RWD sources provide an almost untapped resource for monitoring diagnosis patterns or changes over time. With a little coordination, large data providers could create recurring data queries on vital diagnoses to track potential upticks in real-time. This approach benefits all communities but particularly those that may not have active surveillance programs already in place.

As the definition of RWD continues to grow and expand, so will the incorporation of unique and previously untapped data sources along the way, such as the White House Covid-19 Community Profile Report. Larger sample sizes of the same types of data are not enough. Although the phrase has fallen a bit out of fashion, we already have ‘Big Data’. We need more than just more data; we need deeper data that is relevant and actionable. It’s significant to see so much growth in deep data as the whole industry moves towards deeper, bigger data.

Future Pandemic Priorities for Use of Real-World Data

While the world continues to navigate the Covid-19 public health emergency, healthcare and public health researchers know they must address and eliminate current data disparities to ensure more accurate analysis. Here are three priorities to work on now in preparation for future pandemic outbreaks.

1. Interoperability. Secure exchange of patient health information is paramount, both within and across systems. That will allow researchers to transition large-scale surveillance efforts away from a series of manual queries run separately at each data source or installation.

2. Access. The existing wealth of untapped RWD might have led to vital insights in the early days of the COVID-19 pandemic. For example, each hospital system or integrated delivery network has a deep perspective on their element of clinical care but often doesn’t have the RWE resources or data rights to glean insights from that data. How many RWE insights are missing because it sits in a cache of untouched data?

3. Coordination. With the Covid-19 pandemic, several private entities took the initiative to drive vital research. This collaborative approach brought together several RWD providers to tackle several different research workstreams and offers a familiar and effective path to follow during future public health emergencies.

For example, Miter Health formed the COVID-19 Healthcare Coalition in March 2020 and brought together several RWD providers to tackle several different research workstreams. While the data streams are no longer updated, this alliance served for two years as an effective resource for relevant data and updates on the COVID-19 pandemic.

Organizations participated in these volunteer collaborations because it was the right thing to do. That philosophy remains since these same groups now plan to develop a template for what these collaborations can and should look like.

The healthcare industry now generates 30% of the world data volumea number expected to increase to 36% by 2025. Any practice for the next pandemic relies on secure data access and analysis from interoperable electronic health records and other sources, a process that requires collaboration across all populations.


About Mac Bonafede

Mac Bonafede, Ph.D., MPH, is Vice President of Real World Evidence at Veradigm, an Allscripts company, where he leads a team of data scientists, statisticians, and epidemiologists in real-world evidence generation.



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