For this Q&A installment, we invited senior vice president of data and research, Victor Wang, to explore the opportunities for advancing research initiatives with effective clinical data management.
- The average hospital has far more data potential than they likely realize. Unlocking that potential is a critical next step in improving the quality of care.
- Real world data can inform activities that benefit the hospital, the research community, and patients.
- The data used needs to meet demands to answer research questions, optimize trials, and match patients to studies more quickly than ever.
- From producing clean datasets to leveraging the information for research and connecting with the broader research community, several unique opportunities are now available to partners.
Q: How does your work help hospitals deliver safer, consistent, quality health care for all?
Victor: My role is an extension of the broader Q-Centrix mission, which is unlocking the value of clinical data. I am focused on helping hospitals produce high-fidelity data that goes beyond registry reporting to deliver on research initiatives. My team and I strive to unlock the potential of all these data to inform a range of different activities that can benefit the hospital, the research community, and patients.
The data we help hospitals collect can be used for quality and performance initiatives, research patient experience with different diseases and conditions, and understand the effectiveness of therapies. In many ways, this is the next step for the healthcare community in realizing our mission to continually improve the quality of care for all.
Q: Why do hospitals and research departments need to care about real world data?
Victor: Using these clinical data drives efficiency and reduces redundancies across the organization by aligning quality, research, and operational needs. Building the comprehensive data structure needed to do this gives every stakeholder access to high-quality data whenever they need it to influence decisions. For example, Carle Cancer Institute leadership is already applying real world data to inform important hiring and program management decisions.
Furthermore, the value of high-quality clinical data can have real financial implications for research programs. These data can be used to support researchers against demands to answer research questions, optimize clinical trials, and match patients to studies more quickly than ever.
Q: What research data challenges do you help hospitals and health systems solve?
Victor: Our conversations primarily fall into one of three buckets.
#1 – Help with producing datasets.
There is a big bottleneck in hospitals around producing data for research. People know they have valuable data, but it is hard to produce consistent datasets with the current staff. Q-Centrix works with these teams to help build the right datasets.
#2 – Leveraging their data to inform research.
Hospitals want to do more research but have difficulty starting because of the data silos across departments. It is also challenging to query electronic medical records directly; data elements needed for research are often missing from the EMR.
Building the processes and frameworks necessary to mine data from all the diverse sources that record information during a patient’s various touchpoints with the hospital is extraordinarily challenging. Our team’s expertise helps our partners overcome these challenges and start using their data.
#3 – Broader connectivity within the research community.
Hospitals frequently seek partnerships with other institutions to reach the patients they are trying to better understand. They themselves may not have the volume of patients needed to drive insightful research. Importantly, data from separate places must have the same data refinement processes to yield a usable dataset.
Our network of over 1,200 hospital partners, all abstracting data according to the same best practices, is uniquely equipped to handle both needs, giving facilities access to the patients and the consistent data they need to conduct effective research quickly.
Similarly, hospitals are often looking for sponsors for their research. We are now starting to connect hospitals with other complementary organizations, whether other hospitals or sponsors.
Q: EMR information was not meant for research – what does it take to get this type of data “research-ready”?
EMRs are often missing a lot of information needed to complete registry submissions, build research datasets, and drive confident decision-making. Instead, that information is buried in unstructured forms like physician notes and other documents.
To produce high-quality data at scale is an arduous task. It is highly reliant on human experts, technology, quality assurance or data integrity, training, and database design. Q-Centrix has built an impressive capability involving thousands of US-based clinical data experts, custom-built data capture software, training systems, data engineering capabilities, and more to do this at scale and at the highest quality. We rely on every piece of this process to help produce research-ready data.
Q: What motivates you to work with hospitals on their real world data needs?
Most people who work within the broader healthcare ecosystem got into it because of an innate desire to do something good for the world. Like everyone else on the planet, people in my orbit have been impacted by heart disease, cancer, and other common health challenges. I feel grateful that my career has coalesced around roles that capture these individual experiences into larger datasets that can shine a light on disease and play a role in improving care.
Q: What has been the biggest surprise in working with clinical data management for research?
Having historically worked on the drug discovery side of the healthcare equation, I was not fully aware of how much data potential the average hospital has. Most hospitals are investing quite a bit into their various data reporting needs but are not aware of what a few small additional steps could do to help them leverage what they already have, break down data silos, and get more value from their data. There’s real power in aggregating these individual patient experiences into larger data programs that can help inform research and drive better care.
About the expert:
Victor oversees the Q-Centrix real world data strategy, aligning the data, infrastructure, and capabilities to deliver high-quality research datasets across the healthcare ecosystem. He joined Q-Centrix with a strong track record in managing cross-functional teams of data scientists, engineers, and clinical experts to measure the patient experience. He is driven by a deep belief in the power and potential of merging disparate disciplines to unlock datasets and merge data silos. Prior to Q-Centrix, Victor worked on oncology-focused real world data assets, partnering with top pharma companies to understand their data needs and deliver high-value datasets.