How real world data drives safer, consistent, quality health care for all

By Q-Centrix | September 1, 2022

Victor Wang, Senior Vice President of RWD at Q-Centrix, has been working with real world data for his whole career and has seen the usage and potential of this data grow from something novel to something crucial in health care and drug development efforts.

Real world data and evidence are changing the future of healthcare

Beginning his career in life sciences consulting, Victor developed an early appreciation for various health-related data’s value and limitations. Notably, he encountered difficulties while leveraging insurance claims information to identify whether treated patients were part of the population of interest.  

This ambiguity made it difficult to answer key questions about drug performance and revealed the gaps in standard health data types. And while clinical trial data is made for analysis, it does not always provide the information or testing environment needed to know if a new treatment or drug will work for the wide range of comorbidities, races, ages, etc., in the real world.  

As health equity and increasing competition continue to drive health care developments across the industry, leaders need a different type of data to conduct research, manage facilities, and design program initiatives to benefit all patients. For those who can leverage real world data appropriately and consistently, Victor has seen potent impacts: 

“As the health care industry has started leveraging data science, the nuances of all the different types of data, and discovered just how rewarding the resulting insights can be, the excitement for real world data has snowballed accordingly.

What is real world data, and where does it come from? 

Real world data is any health data not captured within a clinical or prospective trial.  

Victor explains, “[Real world data] spans clinical health record data to insurance claims to patient-generated or patient-reported information, and more. Even data from your Apple watch can be considered real world data. That said, the foundational steppingstone starts with data generated by hospitals and clinics outside of trials. This is the data that allows you to understand the clinical context for the rest of the data generated by a patient’s interaction with the healthcare system.” 

 RWD can come from a wide range of sources, including: 

  • Electronic health records – EHRs/EMRs 
  • Claims and billing 
  • Product and disease registries 
  • Patient-generated data, including in-home use 
  • Mobile devices that can gather data on overall health status 

The impact of real world data and real world evidence on health care decisions.  

With real world data sources as abundant as they are in the modern world, Victor’s career has allowed him to appreciate just how many questions can be answered with these data sets. One of his most engaging projects involved helping inform life sciences’ understanding of research in rare patient populations using patient-reported data and EMR information to guide cancer and rare disease research.  

Victor has also become intimately familiar with the challenges of this unstructured data. 

“We learned that the data structure on its own was just too messy, and we needed approaches to go through and pull out the valuable information. We developed a real respect for the complexity of this data, what it took to use it correctly, and just how many new questions we could answer.”

Through these experiences, Victor saw first-hand where real world data has begun to make a difference and where substantial, untapped potential remains.  

Pursuing that potential was what initially led Victor to continue his career at Q-Centrix, where the team is highly familiar with unlocking high-fidelity value in unstructured data, having worked with over 1,200 hospitals and health care systems across the country.  

Pharma and life sciences companies 

To date, pharmaceutical and life sciences companies have been the predominant groups leading the real world data movement. These companies’ resources and analytical capabilities have allowed them to access the new world of knowledge before others.  

Use cases from a pharma and research perspective include designing and executing more thorough clinical trials, finding suitable patient populations more efficiently, driving new drug label expansion in various diseases, and understanding post-launch comparative effectiveness analyses. 

Care delivery 

While still in the early stages, real world data usage has already allowed major players in the health care community to develop new guidelines, research initiatives, and decision support tools for clinical practice. It is also used to increase accuracy in payer interactions and manage market access discussions.  

However, despite all the good already accomplished, Victor recognizes the opportunities providers still possess to fully leverage their data’s value. With access to the proper analytical support attained by pharma and life sciences, health systems and hospitals can also reap the rewards of real-time insights from a broad population. 

Many hospitals lack the necessary technological or personnel resources to use this data to the extent that pharma and life science companies can. As a result, many hospitals come to us wanting to work with a life science company and have a research question in mind. They generally know they have the patients for it but do not always have the protocols or processes to clean that data and create a research-grade dataset. Those processes and that clean, usable data is what we’re able to provide.

Partnerships and advanced technology are often the two supporting systems that help hospitals take the next step in developing real world data management processes for research quickly and with minimal investment. 

Clinical trials 

Historically, clinical trials have relied on cleanly defined variables. Patients can only be enrolled after screening, and tests are run in specific centers. The resulting data is, therefore, often a skewed version of the actual patient population: typically white and with a very particular disease profile. Clinical trial data, consequently, often differ from real-world results. Outside the trial, patients are starting treatment sicker, possess different co-morbid conditions, and are of other races, ethnicities, or even ages than the trial data population.  

“In the worst-case scenario, clinical trials theoretically don’t capture information relevant to you or me if we want to go on a particular drug or treatment. We do not know if it will work well or if we are prone to an acute adverse effect.”

According to Victor, real world data has begun to alleviate these concerns by providing a more holistic data set that allows and accounts for different types of patients and generates a more accurate understanding.  

The FDA 

The power of real world data has become so compelling that even the U.S. Food & Drug Administration has begun using the insights generated by this data to monitor the safety and adverse effects of new drugs and products, relying on the presented information to make regulatory decisions for the entire country.  

What is driving the health care industry’s acceptance of real world data and evidence? 

“Much of the industry’s momentum in accepting these data types has been driven by real world data companies and the FDA. Businesses with access to this data are doing commercial research in partnership with life sciences,” in Victor’s experience.  

Additionally, the success of real world data use has coincided with the massive surge in data availability – clinical data, genomics, socioeconomic data, and wearable biosensor technology, all of which collect health data rapidly.  

Companies across the health industry have begun to tap into this new ecosystem, recognizing the potential the data holds. That work has led to significant developments in analytical technology and nuanced evidence for an improved understanding of diseases. 

One group vastly underutilizing these data is health care providers themselves. Reflecting on the real world data and evidence movement, Victor comments on the missing link between those creating the data and those using it.  

It has always struck me that the hospitals are generating this data. However, hospitals have not historically played that active role in accepting this information or the techniques and research being conducted with the data generated. Our goal is to use our presence and influence to pull hospitals and their authority forward in these discussions about the validity of real world data.”

Real world data opening a worldwide view: what’s possible with RWD? 

The prospective applications for these data sources go far beyond what has been accomplished. Yes, real world data can increase speed, credibility, and efficiency when creating appropriate datasets and patient samples for clinical trials. However, the tactical use-cases for real-world data extend benefits for all areas of health care. 

Hospital management 

A lesser known but highly potent benefit of real world evidence is its ability to direct hospital management best practices, providing hospital and system leaders with concrete insights on resource allocation, physician recruitment needs, and other organizational tasks.  

Leaders make hiring and program direction decisions every day. With real world data, these leaders would have concrete evidence as to which physicians would provide the most benefit for their hospital and community based on specific patient population needs.  

Facilities such as the Carle Cancer Institute are already advancing hospital management using real world data, with others quickly joining them. 

Care and clinical decision-making 

Real world data and evidence can also support care improvement initiatives. Victor reflects on the opportunities available for parties with the motivation to pursue them, saying, 

“When you use all the data at your disposal – whether patient-reported or large-scale EMR clinical data – you can map a patient journey astonishingly well. Physicians develop hunches off a relatively small subset of patients each year, but we can confirm their hypotheses off sample sizes of their entire hospital system in a short time period.”

As for the future, Victor continues to be excited about the new frontiers real world data and evidence are creating for the industry. 

“A lot of the focus [for real world data usage] has been on oncology. While this is super important and a developing area with a lot of investment, cardiovascular conditions are overwhelmingly responsible for most deaths in the United States. At Q-Centrix, we consistently process a vast amount of cardiovascular data across 1,000 hospitals: there is so much potential for clinical trial development or connecting RWD studies. I am excited to see what our partners can do with this data. It feels like a market that historically has not had that much attention, and where the existing datasets have well-known gaps.

Leading health equity 

Helping deliver safer, consistent, quality health care for diverse patient populations is perhaps the most intriguing ability of real world data. The new data sources allow researchers and hospitals to collect significant quantities of data much more efficiently to understand the real-time impact of treatments and drugs on different individuals. The resulting insights explore not just what treatments work but for whom and when they work best. Envisioning the future of real world data application, Victor offers these final thoughts for health professionals: 

“Convincing people that this data, captured in near-real-time at the point of care, is of high quality and value continues to be a fantastic opportunity for us and extremely rewarding when you see the direct improvements in care, research, and even drug development that can come as a result.”

 

Want to learn more about the power of real world data and evidence? Check out a few additional resources from our team. 

White paper: Real world data best practices for clinical applications and evidence generation 

Online webinar: Developing a real world data model 

Reach out to Victor directly: victorwang@q-centrix.com