Use Case of Maximizing Drug Launches with Analytics

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.

The second use case that we're going to explore is really focused around drug launches and being able to maximize what that launch experience looks like. The key question that we're going to go ahead and shine a light on is how a pharmaceutical company might really be able to understand some of the early adoption related to their drug in the effort of being able to maximize their sales and being able to maximize their marketing launch as well.

As many of you know, being able to understand the early adoption of a drug that you just launched to market is extremely important and critical to being able to understand the long term success of that particular launch. Now, there are a couple of different ways that you can actually think about how a drug is being adopted.

But it's really important to understand the settings in which that drug is actually being used and prescribed. That might be understanding which hospitals have started to use your drug. That might be understanding which physicians have started to prescribe your drug. It's really kind of a starting point to understand the success of a launch.

Use Drug Expense Claims Data

Now what you can do is you can actually use drug expense claims data to see whether or not that drug is actually being ordered. When a drug is ordered then you have more intelligence on whether or not claims are being submitted for reimbursement. Then you can also from there understand how many patients are actually being impacted, and you can track that over time.

Now, when new drugs come to market initially what is most valuable is actually having that real time access to understanding how often the drug is actually being prescribed. Being able to see that on a monthly basis gives you a good tracking mechanism for understanding how those counts are changing over time. Are they accelerating at the right rate? Are the providers and physicians actually prescribing your drug? Does that change anything related to your strategy itself?

Let's go ahead and dive into the analytics again and take a look at how you can think about this for an injectable drug that is delivered in the hospital setting. Real time data is the most important thing in being able to maximize what your lunch efforts really look like. That's based on the example that I just showed you to be able to influence what your strategy is.

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There are a couple of things that are important for consideration here, especially as you consider how important it is to track intelligence over time. The first is the notion that drug patents do expire, and sometimes those product pipelines can narrow pretty quickly. Being able to get to actionable intelligence that informs you on what that uptake looks like, what those prescribing trends are, and the physician practices or individuals that are really kind of writing those scripts is really becoming more critical.

In addition to that, with the lag time of generally between four to eight months before a J code is actually assigned, it's important to actually keep your finger on the pulse and make sure you understand where that code is being built for before it becomes ubiquitous over time. Then finally, being able to understand that sales distribution is not only the only thing that you actually need to know. What you really need to have is that that visibility into who is doing the prescribing, what levels and reimbursement are actually taking place to inform what any kind of actionable next steps might look like to maximize that launch.

Okay, so let's go ahead and drill into an example here related to a drug uptake analysis. What I want to do is look at a new code or an injectable that got released for the purpose of being able to be used in the hospital inpatient setting. We're going to take a look at code J0702, which is meant to be an anti-inflammatory for the purpose of being able to help with any sort of inflammation on the skin after for example, a surgical procedure. Newer codes want to use this to be able to assess how we can use claims data to actually think about the success of this uptake and how it might inform what our next steps might look like as the brand team or the commercial team.

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I've gone ahead and inputted the code that I care about. I'm going to go ahead and update the results to start to understand who are the hospitals that have started to bill for this particular injectable in calendar year 2018. What we see is that there are 339 hospitals across the US that have started to bill for this code. We've got Harrisburg Medical Center at the top of the list, and it bills for this injectable 301 times. We've got Lee Memorial Hospital out of Fort Myers, Florida who's billed for this code 188 times, so on and so forth. But gives you some good high level intelligence on who the hospitals are that have managed to make this injectable a part of their potential surgical follow up.

Now, one thing that we can start to think about here is that we can go ahead and work with and partner with these 339 hospitals to understand the instances in which they've been successful in using this particular injectable. When they haven't been successful, we can inform and really drive what our future and subsequent work would look like to get the adoption increased across the board to the other hospitals that are operating across the US landscape.