Using Claims Intelligence in Healthcare

Below is 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.

Hi everyone, thank you for joining today's webinar. This session is about using claims intelligence in healthcare. By healthcare I mean life sciences, pharmaceutical companies, medical device companies, or biotechnology firms. And there are four customer segments one of which is healthcare providers. That might be hospitals and health systems or even some of those smaller more independent provider practices.

Then you have providers of data and intelligence on health care providers across the entire continuum that really includes hospital physicians and every other provider in between. The InetSoft data intelligence product suite ties these all together to give you great detailed intelligence on each one of those providers with the ability to really search and filter and get a targeted list. But then you can also take a look at very specific profiles that really show all of the intelligence that you might need to know in order to work with any of the providers.

In the database they track about 8,800 hospitals and IDNs. That includes providers that are operating in that ambulatory space such as clinics, surgery centers and imaging centers. About 85,000 long term care facilities that range from skilled nursing to home health to hospice are included.

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Commercial Claims Data Assets

Then there is a lot of great intelligence on physician groups and physicians operating in market. That includes 150,000 or so physician group profiles and intelligence on over 1.6 million healthcare professionals and physicians. Some of the key data that is tracked on all of these different types of healthcare providers really ranges from affiliations and the relationships that they have with other providers and market, plus some of the key executives and their contact information of staff each one of these providers. There is also great information on different opportunities that help you develop business with an entity such as for responding to RFPs.

There is technology implementation data, key financial, clinical, and quality metrics that help you understand what the operations of that provider business might look like. But what we'd like to do today is really kind of focus on the procedural and the diagnosis information that you can analyze in order to understand from the claims information how to best work targets and segment the data for effective strategies within your own business. With that we'll go ahead and dig into more information about the commercial claims data assets.

Now I'm going to tell you a little bit about the commercial claims data asset to describe some of the top line numbers that make this particular data really useful to end users. If you are in a relationship with multiple claims clearing houses that are operating in market, you need to access a pretty large commercial claims data asset that significantly covers the US market. Here are some of the top line stats that are important for each of you to know.

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About one billion medical claims are tracked annually, so there is great coverage not only on about 6,700 hospitals in the market, but we also have claims data from the medical side on about 1.3 million healthcare professionals. So that is really strong coverage. Beyond that there is also prescription claims data, and there are about 900 million prescription drug claims that get processed annually within the data set. This large RX specific data set actually brings a lot of great insight into the prescribing habits for well over a million physicians that are operating in market today.

On the other side of things let's talk a little bit about the number of lives that are commercial claims cover. About 210 million lives in total are covered, and with that there is data that is going to back three years all the way through to the present. In terms of those lives that's about a 150 million lives that are actually covered annually, and that represents about two thirds of the US population.

Now that everyone has a little bit more background on the claims data itself, I'd love to go ahead and talk about how you can actually integrate this type of intelligence into our BI platform and how it works to really put the data into context with a lot of great other account and physician level intelligence.

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Data Cleansing of Healthcare Claims

If you have experience working with claims data, you know how dirty and messy these data sets can be especially given how large they are with billions of records on all different types of attributes. What we really focus on is taking the claims data that we now have and putting it within our product platform to accomplish a couple of things for end users.

The first key to discovering insights in this healthcare data is really to create that easy to use and easy to navigation interface that makes this data a lot more accessible than it is otherwise. Our access is straight forward. Our filtering capabilities are easy to use, and it really brings down the barrier to entry for what can be considered a pretty complex data set.

The next step is the processing, manipulation, and mashup of this data on a regular basis to get that into the interface so that you have the most up to the minute intelligence available. That might be claims data from hospitals. That might be claims data, or alternatively it could be claims data tracked on providers that are operating in that ambulatory market like a physician group or a surgery center.

Finally, what we've done is we've actually put standardized reporting around the claims data so that you can spend less time trying to figure out how to make use of it and more time really finding some of those hidden insights that are really related to how you think about targeting and strategic initiatives going forward. As a result here, by putting the data into our analytic reporting platform, we have created a much more powerful way for users to get insight out of this type of healthcare insurance information.

Next: Insurance Claims Analytic Views