Segmentation of KOLs and other thought leaders

Let’s say you want to select someone from your pool of Key Opinion Leaders for a specific function. It could be as a speaker, advisory board member, author of a journal article or study chair for a clinical trial but, either way, there are a thousand data points that could be used to select that individual. I don’t mean ‘a thousand’ figuratively. There literally are a thousand pieces of information in an average KOL profile; even more for higher-ranking KOLs. Segmentation of medical experts — as would be performed in order to make the above selections — is predicated on accurate and complete KOL profile data. It’s the classic garbage in, garbage out scenario; as is the case I suppose for pretty much any decision.

What’s been missing to date?

What’s been incomplete so far in KOL profile data is any real metric of KOL efficiency or, to put a business spin on it, return on investment. By this, I mean how much will it cost for a drug company to involve a KOL or medical expert as a trial investigator? How does this compare to the cost of funding the entire trial, with all of its associated overhead costs? How many journal articles (the first line of awareness among colleagues) will they get out of it? Just as importantly, how do these values compare to benchmarks for their peers? Even though this particular data set revolves around trials and publications, this kind of benchmarking can provide broader insight into how wisely each recipient utilizes resources; your company’s resources, by the way.

Here’s a glimpse of the data. Of the $2.4B in research payments made by industry which could be definitively linked to a trial identifier, clinical investigators received an average of approximately $51,000 per trial over the four year period from 2013 to 2016. The median per-trial payments were around $12,000, indicating that this data follows the same exponential decay curve for distribution as does most other information in a KOL profile. The maximum industry payment to a single investigator was just shy of $50M per trial. Interestingly, this is about the same as the maximum 2013–2016 cost of a government-funded, investigator-initiated trial, although government-funded averages and medians were, not unexpectedly, much higher. Of course these amounts vary by trial scope, including phase, number of enrollees, etc., but the concept remains the same; it’s now possible to benchmark a KOL’s expected efficiency in relation to that of their peers.

Why has ROI not been used extensively in the past?

The reason these kinds of calculations have not been used extensively in the past is a bit of a mystery; industry data has been available for four years now. It could be that Medical Affairs groups — the primary consumers of KOL profile information — are not quite as numbers-centric as are their Marketing counterparts. It could also be that the resources devoted by the drug companies to these activities in the past were viewed more like an expense than as an investment, which would negate the entire concept of ROI altogether.

Regardless, we have this information now and it can be used for these or similar calculations. There are a myriad of criteria that can go into the selection of KOLs for any role, so we don’t expect this data to be the sole, driving factor in KOL selection. We certainly do see it as something that should be considered if you want to maximize the productivity you get out of your annual budget.

This article was originally published by Michael Broad (Principal at Act Healthcare Solutions) on LinkedIn.

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