Sprout Health Solutions presented new insights on the use of social media listening (SML) for understanding patient experience in chronic disease at Virtual ISPOR EU, the leading European conference for Health Economics and Outcomes Research (HEOR).
| LONDON, Nov. 23, 2021 /PRNewswire/ -- Sprout Health Solutions presented new insights on the use of social media listening (SML) for understanding patient experience in chronic disease at Virtual ISPOR EU, the leading European conference for Health Economics and Outcomes Research (HEOR). Fernanda Trevisan, MSc, Scientist at Sprout, shared findings from a scoping review in the session, “Is Social Media Information Useful to Understand Patient Experiences and the Burden of Disease?” Her on-demand podium presentation is available starting today, in advance of the conference (November 30 – December 3).
“As social media is increasingly used in healthcare research, we wanted to assess the tools available, including their limitations, benefits and ethical questions,” said Trevisan. “The evidence suggests SML provides an inclusive, unfiltered and less burdensome method of capturing patient experiences that is both time and cost efficient. However, because it is a young field, there’s more work to do in organizing methods, frameworks and guidelines.” Evolution of Social Media Listening Originally tapped for branded consumer market research, SML is now utilized across healthcare to map a more authentic picture of patient journeys, including the impact of illness, symptoms, treatment beliefs, side effects and unmet needs. According to Trevisan, SML can be a key pillar of patient insights work to develop relevant educational resources, and to inform clinical trial development. It’s especially beneficial in populations less represented in typical research or where evidence is scarce. “For example, individuals with rare disease often rely on social media to learn about new treatments or share personal stories with those who face similar challenges. Even though the data is anonymized, you get a very clear sense of personal experiences over time and conversations peer-to-peer.” Trevisan noted the studies identified ethical issues and limitations, including user selection bias. And, because data mining algorithms tend to prioritize the most frequent mentions, it can be harder to identify all emerging themes. To view the presentation, visit Sprout Health Solutions Industry Insights. About Sprout Health Solutions
SOURCE Sprout Health Solutions |
View original content to download multimedia:
