How digitization of physician data is changing the way pharma selects and manages KOLs

The digitization of physician career information has dramatically improved the Key Opinion Leader (KOL) data landscape, allowing KOL data providers to provide their clients with improved quality, while also increasing the value they receive from data-driven products. The resulting increase in quality will ultimately facilitate better data-based decisions.

The current state of digital data sources

The publication in 2014 of OpenPayments — CMS’ compilation of the financial arrangements between healthcare providers and life sciences companies — was the most recent in a wave of digitized, consolidated physician data. Included among global, publicly-available data sets that could potentially be incorporated into a KOL Profile are Publications (PubMed), Clinical Trials (ClinicalTrials.gov, the ISRCTN registry, etc.) and Patents (USPTO and WIPO). Beyond OpenPayments, US-centric databases include NIH’s RePORTER, CMS’ NPI database and ABMS’ Certification Matters.

Along with NPI and ABMS, OpenPayments and RePORTER have taken even greater steps towards facilitating data accuracy: they’ve created a unique identifier for every medical professional who has received industry payments or grant funding, respectively. This means that, once you’ve properly associated a Physician ID (OpenPayments) or a PI ID (RePORTER) to a KOL record, you can search these data using just the identifier. This is extremely useful because it mostly eliminates the prospect of name ambiguity, which is a leading cause of Profile data error. In contrast, the challenge of name ambiguity still exists for publication, clinical trials and patent data, leaving open the potential for such errors.

The impact of digital data on KOL programs

So why is it so important that this digital information is so readily available? Two words: accuracy and completeness — the two major dimensions of KOL data quality. They are both equally important since accuracy prevents false positives and completeness prevents false negatives. Neither of these errors is desirable because both can skew any decision that is based on this data. It’s the classic ‘garbage in, garbage out’ scenario.

Say, for example, you are performing a network analysis to determine if a sought-after physician — one you are not able to reach directly — is professionally connected to one of your existing KOLs; someone who could then make a warm introduction for you. Arguably, one of the strongest connections between two medical professionals is that they are co-PIs on an NIH grant. In the pre-digitization era, you would pore over their individual CVs (assuming you could even get access to both) and determine that your KOL and the physician you are trying to reach both list an NIH grant with the same title (but, for the sake of discussion, with no associated grant numbers). This may initially lead you to believe that they are co-PIs, but grant titles are not exactly unique and this could just be a coincidence. With digitized data, you can examine the RePORTER record for the grant in question and determine, with certainty, if the two really are co-PIs. This is why digitization is so important: if this data was not digitized, you could be misled into making the wrong decision.

How this benefits everyone in the KOL value chain

As a long-time provider of KOL data, we can tell you that the digitization of physician data has not only helped us create a significantly better product, it has improved the value we can provide to our pharma, biotech and medical device clients. Much of the data described above is available for download, which means we can aggregate it and then query a list of names or unique identifiers against the database. This not only allows us to deliver more accurate and complete data, it saves us considerable time in doing so as compared to querying the same data using editorial search methods. Since time is money, this increased efficiency gives us the opportunity to provide the highest quality product at competitive prices, which translates into the best possible value for our clients. And tell me, what client wouldn’t want that?

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