At Pulse Infoframe, we have a sneaking suspicion about Dr. Femida Gwadry-Sridhar, our founder and CEO. We believe her favorite childhood game was Connect the Dots. Why? Because of her skill at connecting the dots in healthcare data. Of course, the world of healthcare data is disorderly, not numbered and easy to connect. To make sense of it all, you have to love data and live it.
“I have over 25 years’ experience in pharmacy, clinical epidemiology, and methodology,” says Gwadry-Sridhar. “That translates to over 25 years of working with data to find answers. I’m definitely passionate about data and using it to help patients. Whether it’s about building an experiment in a test tube or designing a study, data that we already have and need to create are at the center of all discovery.”
For example, analyzing data led her and her fellow researchers to discover that heart patients who delayed filling their first prescription for statin medication had a much higher chance of not continuing to take these lifesaving drugs.
While conducting clinical trials, Gwadry-Sridhar came across one major hurdle: the data from doctors, researchers and clinicians was stored in different systems and collected in different ways. In the technology industry, the name for these disconnected systems is data silos. Imagine barn silos, where grain from one silo doesn’t mix with grain in any of the others. Data is often stored the same way.
“Data silos made it difficult to find candidates for clinical trials,” says Gwadry-Sridhar, “because I didn’t have access to all their data and especially relevant data.”
If Gwadry-Sridhar didn’t have access to the data she needed, then thousands of researchers around the world were experiencing the same problem.
That led to another discovery: these data silos hindered research in rare diseases and cancer, where there are either few patients globally or require very precise data that are hard to come by.
Rare Diseases and the Need for High-Quality Data
Over 7,000 documented rare diseases exist. However, any rare disease may have only a few tens, hundreds or thousands of people living with a condition in the world. Neither disease nor data recognize any boundaries.
Different countries define “rare disease” in different ways. In the United States, a rare disease is a disease that occurs in fewer than 200,000 people. That number may seem large. After all, it’s the population of many small cities. However, the National Cancer Institute in the United States estimates that in 2020, about 1,806,590 people will receive a cancer diagnosis. Or how about ailments of the heart? The CDC reports that about 18.2 million adults age 20+ live with coronary artery disease.
Each condition has its own challenges, no matter how common or rare, and adversely affects people’s quality of life. The only way to help is to discover and combine the data that can help solve each problem.
Like a puzzle, each missing piece creates a challenge, and our job collectively is to find the missing pieces and connect the dots. But first we need to assemble what we do know that will point us to what we need to find out. Improving outcomes requires an understanding of the causes, chronicling the patient journey and then mapping out what we need to navigate success.
Cancer and Data
Although the NCI estimates that almost 2 million people will be diagnosed with cancer in 2020, there are over 100 types of cancer.
“Cancer refers to cells that divide out of control, but the factors that lead to this uncontrollable division are numerous,” says Gwadry-Sridhar. “By collecting complete data, we can track not only what different cancers have in common but also study each cancer’s uniqueness. It all comes down to the data—how we leverage what we do know by codifying the data into what we know to be common across diseases so that we can also apply our learning across diseases.”
Sharing Knowledge to Build Knowledge
In science, it’s called the eureka moment. In modern pop culture, the aha moment. Whatever you’d like to call it, that moment led Gwadry-Sridhar to create the first knowledge translation health informatics lab in North America, in 2006. In other words, she created a facility focused on sharing data across health disciplines.
“Collaboration” isn’t a trendy word in healthcare; it’s how healthcare operates. Imagine an evening where your child begins complaining about pain in their ear. Your GP’s office is closed, so the two of you go to your local hospital. There, you will meet with a triage nurse, a doctor, and possibly a lab technician. Their knowledge about your child’s condition came from research carried out around the world to help diagnose your child’s earache quickly and provide the proper treatment.
Healthcare research can only work via collaboration. Without it, researchers risk duplicating efforts, wasting time and money. Ultimately, patients then suffer. With effective collaboration, researchers can more easily access the data that can give them better context. With this increased understanding, they have a better chance of finding effective treatments and cures. What good is diagnosing an earache without understanding the possible bacteria and viruses behind it?
Medical knowledge grows at an incredible rate. This requires researchers and doctors to dig deeper into their specialties for answers. They miss opportunities for discovery, because they research within the silo of their own disciplines. The lab Gwadry-Sridhar created allowed researchers to share data among different fields to find answers that might simply be in front of someone else’s nose.
Data Protection and Governance
All this talk about sharing data may raise some concerns, and it should. Healthcare information is extremely personal, and those sharing their information must trust it’s being used and protected properly. In tech terms, this is called governance.
The knowledge translation health informatics lab Gwadry-Sridhar created also developed an appropriate and effective governance structure. Therefore, those providing the data, whether researchers or patients, could trust that research could continue to find answers to improve patients’ lives without carelessly sharing their personal health data.
Taking Data One Step Further: Gwadry-Sridhar Founds Pulse Infoframe
“When data are shared across boundaries,” says Gwadry-Sridhar, “medical advances are made. That means patients, clinicians, researchers, and pharma and biotech companies can share their data and collaborate with each other.”
Gwadry-Sridhar founded Pulse Infoframe in 2011 to combine her love of data and desire to help patients improve their lives. Since then, the company has helped patient advocacy groups, pharma and biotech companies, healthcare researchers and doctors collect and share data to bring about answers.
From 2011 to 2013, Gwadry-Sridhar, along with a team that consists of researchers from different health sciences centers, a cancer center, a university and a pharmaceutical company, used Pulse Infoframe’s platform, healthie™, to collect data on metastatic melanoma in Canada.
Why?
Because the data were missing. Without detailed data on the distribution, causes and risk factors of metastatic melanoma, how can researchers find a cure?
Dr. Gwadry-Sridhar is known in Pulse Infoframe offices as hardly stopping. In 2019, when travel was still possible, she visited over 20 conferences, presenting on patient registries, data governance and the three C’s—connect, collaborate and create, all necessary to find answers.
But we suspect that—on occasion—she’s taking a breather somewhere, enjoying a coffee and a snack, her pencil following each number in order in a connect-the-dots activity book. Life isn’t only about work, as we all discovered in 2020. In keeping with her passion for following the dots, Gwadry-Sridhar spends her spare time playing tennis. She’s learning to keep her eye more on the dot, or rather the ball, and focusing less on rejoicing in her last shot.
What her lived experience so far has taught her, though, is to never lose sight of where the dots are going and where they can be joined to create a pattern that provides knowledge and a better understanding of how these patterns can help us win against the diseases that affect those we care about.
