Delivering smarter, faster insights for better health outcomes

Konovo is a global healthcare intelligence company, with access to validated HCP and patient audiences. It also leads patient recruitment services through Rare Patient Voice’s innovative tools that power the full research workflow end to end.

In a recent webinar – ‘Discover a new era of healthcare panel engagement: Grounded in people, accelerated by AI’ – Konovo experts addressed some of the critical topics impacting today’s healthcare market research. Becky Harris, senior vice president, head of product, Konovo provided the product viewpoint; Wes Michael, president and founder, Rare Patient Voice (a Konovo company), provided the patient and caregiver viewpoint; and Danielle Schroth, vice president, panel operations, Konovo, provided the HCP engagement viewpoint.

From effective panellist recruitment and robust validation, to precision targeting and enhanced engagement, the webinar dove into how a human-powered, tech-accelerated approach delivers smarter, faster insights for better health outcomes. After all, at a time when AI dominates the conversation, the most powerful insights in healthcare research still come from genuine human connection.

What life sciences and healthcare researchers should ask panel providers

From a panel perspective, Schroth noted that, while the numbers are important – Konovo has 200,000 verified patients and family caregivers, and millions of healthcare professionals verified globally – it also comes down to individual human participation.

Considering the questions from the product and technology angle, Harris commented that many partners claim to be AI-powered, but that this is rather an expectation now.

“It should be in their tech development, should be in their product strategy, should be in their general ways of working […] What I would encourage you to […] actually start asking them [is] what their AI policy is,” said Harris. “There’s a real difference between being AI driven – where there's the […] algorithm and the technology doing the work – and actually having a human involved [… where] people are verifying what's actually happening.”

Equally critical is transparency.

“Are we being transparent when it's [AI] being used, how it's being used? Do they know, do they consent to it?” Harris said. “Some of the best partners that I have seen out there, they're incredibly transparent when the technology is doing the work versus when the human is doing that work.”

From the Rare Patient Voice viewpoint that transparency is important, also.

“That helps us evaluate,” Michael agreed. “How are they also getting their participants to be good market research contributors? […] What are they doing to empower and educate those individuals so that they make good decisions? […] What are in the T&Cs and how does that interact, the potential use of AI in research and educating those respondents?”

Turning technology into insight, not just noise

There is an expected pace that surrounds AI deployment and use at the moment, but the panellists agreed that an intentionality needs to be in place, also.

“In truth, if you haven't actually been intentional around the problem that you're solving for […] then it's going to be really hard to utilise the output from that,” said Harris. “You end up with noise […] It's the same thing that came up with data democratisation a number of years ago: what is the context and how is the data being used? It's the same concept here: what's the research objective?”

“We can speed up one element, but actually we should be really challenging ourselves to [wonder] how do we ask better questions or how do we use AI to be a thought partner so that we remove the noise and we can be a lot more intentional about how and when we're using it, not just put AI in front of everything as that badge,” Harris continued.

For Schroth, it’s important to consider intentionality from the respondent point of view, also. Meanwhile, for Michael, even though traditional methods shouldn’t necessarily be forgotten, AI does circumvent some of the ‘grunt work’, so to speak.

“If you look at the old days – that's what, two years ago? – you'd have a book of tabs and you'd give it to a junior researcher and they create all these charts and graphs, but that was an insight […] that's where the senior researcher, knowing the client, knowing their needs, would […] tease out, well, how do we tell the story to give them the insight?” explained Michael. “And we're in a very parallel place here. Instead of the junior researcher doing all the crunching, AI can do that, but it still needs to be turned into that insight, and AI can help us do that.”

Fraud prevention and transparency

Pursuant to everything so far discussed in the webinar, fraud prevention followed naturally as the next topic of discussion.

“What is your policy if it's determined that a respondent has used AI in their participation frequency?” asked Harris. “And the tools surrounding quality checks and validation, what are those tools? How are they integrated? At what point does a human weigh in? And are they making use of automated data quality checks […] to confirm consistently this is a human and they're using a human brain to participate in research?”

‘Fraud’ in this sense covers both fraudulent participation from a professional standpoint, though, as well as AI usage. And any tool used for detection must be able to differentiate between the two.

“They are individuals, they are human beings that are spending their time engaging with us,” continued Harris. “And there is an element of […] respect, which I think we often forget more broadly across the industry […] Respect for [their] time and making sure that we're getting them to the right survey that makes sense for them that they're going to have value in responding to is really key.”

Schroth agreed with this critical element of respect, and “not just sort of rushing to get an outcome.” For Michael, there are complexities.

“I think it's even more difficult with patients than with HCPs because at least you have any numbers to start with,” said Michael. “[A] patient, you know, the self-stated diagnosis, you've got to really be sure. Is it some bot in some foreign country? And so, the first thing I would ask any provider is, what is the source of your panels? Where do you get them? Are you scraping the Internet?”

“What we like to do is meet people in person; talk about old school, right?” he continued. “Talk about non-AI. Go to the patient events or referral partners, patients, know other patients, the advocacy groups, know folks […] If you get the right people to begin with, that solves most of your fraud problems right there.”

Balancing speed with quality, the human way

Clients themselves are always pushing for faster turnaround, however, and those old-fashioned approaches don't perhaps permit that accelerated speed required today. The question is: at what point, though, does speed become a genuine threat to quality?

In Harris’ opinion, it shouldn't be at the expense of either quality or intuition.

“We shouldn't move faster in the things that really make the data trustworthy,” she said. “We want to consistently expand our access, build more tools, but that can't happen at the expense of verifying the validity of the access. And so we want to make that investment in technology to create the right tools to get the most out of the intervention and resource.”

“It reminds me of that old cartoon where somebody's staring at their microwave and yelling ‘Faster, faster!’” added Michael. “I did the first online physician study in the year 2000 and what a surprise to get the data back in a day because we're used to having it come back [a month later] and using a month to plan the data analysis […] Industry had to figure out how [to] take advantage of that speed.”

Nonetheless, everything considered, human expertise remains essential to making AI truly effective in healthcare research.

“It’s not just the human expertise, but also considering the human experience,” said Harris. “We want to make use of AI technology to provide meaningful experience that combines quality data and […] a positive member experience […] It's that concept of having two customers […] Without our HCPs and our patients feeling the same way, we're not going to have a happy customer because they're not going to want to participate with regularity.”

For Michael, the live human kick-off call is still crucial: “There's nothing better because AI can transfer the information. Here's what the client wants, here's what we can do. You need to add that human touch on top of the wonderful stuff that AI does.”

From intuition to gut instinct, at the end of the day, healthcare is human care, but what keeps HCPs and patients participating in surveys meaningfully over time, again returning?

“We need to listen to our respondents,” said Schroth. “We're here to provide a platform for them to elevate their voice and get a seat at the table.”