The Value of Analyzing Physician Drug Adoption Rates

Below is the continuation of the transcript of a Webinar hosted by InetSoft on the topic of Using Claims Intelligence in Healthcare. The presenter is Abhishek Gupta, Chief Data Scientist at InetSoft.

Beyond the value of analyzing physician drug adoption rates, you can think about the kind of the affiliation structures that we've talked a little bit about that really helped to inform what your drug launch strategies should be based on, and how loosely or tightly aligned a doctor may be within our particular system. You also have the contact information for physicians whether that'd be the emails that we have on hand, the addresses where they're practicing for their primary practice location, or even direct dials. That really helps to inform and allow you to have that efficient and targeted outreach strategy.

Then finally you are able to incorporate all of their prescribing data into your workflows. Being able to think about that prescribing data within the context of the therapy areas or the indications that are important to you allows you to have a new dimension to think about that affects the success of a launch before you actually go to market.

Throughout this presentation, I've been able to show you a couple of different examples of pharmaceutical launch analytics and how you can actually get great access to commercial claims data and use that to support your strategic business initiatives. The in product integration makes this data easy to use, but sometimes it's important to really accelerate what your analytics journey.
#1 Ranking: Read how InetSoft was rated #1 for user adoption in G2's user survey-based index Read More

Analytic Capabilities from Healthcare Claims

This expands what some of those analytic capabilities are. You can go ahead and define and develop what are some complicated analyses that might bring you additional insight and intelligence within the commercial healthcare claims landscape. With that we're going to head into our Q&A portion of the webinar.

Great, thanks. First question here: Can you tell me more about the sources of claims data used in the analyses?

This claim data comes from multiple different clearing houses that actually operate in the market today. We combine that data with other sources, including claims data from the Medicare program to come up with a robust all payer claims data solution. When we take a look at that data asset, we understand that there's no kind of significant bias in that data, meaning there is great representation across all geographies and across different periods of time. Beyond that, data goes back to January 1st through the present time, which enables us to really deliver those real time views, but also to analyze and trend that data over the past three calendar years.

Great, another question here. You shared insight on being able to drill into referral patterns. Can you tell us more about that part of the offering?

Absolutely, we use our claims data to run a really data-driven referral analysis that helps our customers understand how patients are moving between healthcare organizations and healthcare professionals. This analysis not only helps to demonstrate the real relationships that are in place based on claims experience, but what it also does is really help to demonstrate the strength of those relationships by quantifying and counting referrals over a couple of various windows of time.

That really starts with a 60 day window and can escalate up to 120 days from that analysis. Through the data, we can really kind of slice and dice these referrals by a number of different factors, which would be kind of by time, by direction, by type of provider, to really help inform what your targeting strategy might be.

Read what InetSoft customers and partners have said about their selection of Style Scope for their solution for dashboard reporting.

Example Based On Pharmaceutical Benefits Claims Analytics

All right, we'll take one last question here. You shared an example based on pharmaceutical benefits claims analytics. What are other analytic scenarios can people use the claims data for?

Yes, so we've selected a few of the most common use cases. But the reality is, is there's a tremendous amount that you can do with this type of data in conjunction with the other intelligence that can be tracked within the platform. A few other ideas that you might consider would include running patient journey analytics, running a payer mix analysis, or even thinking about trending opportunities to really launch and bring new products into market over time.

I think with that that concludes the Q&A portion of the webinar and wraps us up for this afternoon. I want to thank everyone for dialing in this afternoon to learn more about how using claims intelligence can really help you win at your business. Thanks so much, everyone. Have a great afternoon.

Previous: An Example of Analyzing Drug Prescription Patterns