But researchers must expand their focus beyond incidence rates.
Credit: Geralt, Pixabay.com
When Simron Singh, MD, MPH, and his team began conducting population health research regarding neuroendocrine tumor (NET) cancers in Ontario, Canada, their work spurred several different kinds of results.
Singh, a medical oncologist at Odette Cancer Center at Sunnybrook Health Sciences Center in the University of Toronto, discussed the benefits that population health studies can yield at the NANETS Symposium last week in Philadelphia. He also encouraged researchers to tackle other questions outside incidence rates, outlining best practices to help them get there.
“Don’t just repeat what we already know,” he told attendees, urging them to strive for what’s useful. “Don’t reproduce the same population data.”
When things go right, here are some of the key areas that population health research can affect.
Awareness: While studying pancreatic NETs in Ontario, Singh and his colleagues raised awareness among patients and members of the general population. That in itself can aid in combatting the disease.
Policy, funding, and interest: In Canada, Singh helped prove that NETs were more common than first thought. In turn, that swayed the government to dole out more funding and patients to seek treatment, he said. “It wasn’t very long ago,” he said, referencing his country, “when awareness of NETs was very low.” Such a campaign can also stimulate interest in the scientific community, sparking partnerships and data-sharing infrastructure.
Real-life outcomes: A gap exists between actual outcome data and the results of clinical trials, a point echoed by other NANETS speakers. That sort of disconnect suggests the trial might not be reproducible, or it hasn’t been translated correctly. But population health has the power to spotlight such problems. That is the first step toward a solution, which can save energy and money, Singh said.
Research priorities: Population health studies allow researchers to pinpoint gaps in care or holes in the body of knowledge. That can guide future studies.
Finding disparities: Not everyone receives ideal care, Singh noted, and that’s especially true of NET patients. But population health can reveal who’s missing out.
Encouraging data collection: Although Singh discouraged collecting data for the sole sake of collecting data, he said these kinds of studies might prove valuable in prodding healthcare groups to focus more on informatics.
For population health researchers—and the public—to reap these fruits, they must follow reliable, clear paths to the data.
For starters, that requires a straight-forward direction. “It’s really important to think about your research question, but also think of your population of interest,” Singh said. “That’s probably the most important step.” That area is critical, he said, due to the aforementioned gap between clinical trials and real-world outcomes.
To get strong data, investigators must then define what they’re looking for: outcomes, incidence, funding levels, or something else? The numbers will be skewed by that perspective, Singh said. Then, at regular intervals, researchers must review the data they intake to ensure quality.
Before any of this, however, Singh suggests analyzing what you’re seeking and why it’s important. Will people care? Will it improve outcomes?
Not long ago, Singh and his colleagues undertook a study of the disparities in NET incidence and outcomes between rural and urban areas in his province. They analyzed 6271 cases and found a pronounced disparity between geographic areas and that it typically took a “very long” time before a recurrence.
Their population health study helped inform new guidelines governing NETs that came out last year in Canada, Singh said. Their efforts had impacted clinical management. “So it was data to really drive change,” he said.