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  #21  
Old 05-28-2018, 07:16 AM
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This reminds me of when my company wanted to 'innovate' but im pretty sure their strategy was just to see how many times they could say 'innovate'.
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  #22  
Old 05-29-2018, 01:24 PM
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While there are a couple of important exceptions (e.g. gaming risk scores), in general predictive analytics isn't remotely as useful in health insurance as it's made out to be.

And what's left to do can often be purchased or outsourced.
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  #23  
Old 05-29-2018, 01:31 PM
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It's been my experience that most of the problems associated with predictive modeling starts with the data.
Data you get are the end process of paying claims. And the goal of paying claims is doing it right and fast. Not necessarily to provide actuaries with all the data they need in a perfect format.
Also, changing of time periods (month-to-month, even) requires a lot more thought and will generally muddy the results.
And, now your data are two years old and might not be relevant to today's decisions.
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  #24  
Old 05-29-2018, 07:40 PM
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Originally Posted by Locrian View Post
While there are a couple of important exceptions (e.g. gaming risk scores), in general predictive analytics isn't remotely as useful in health insurance as it's made out to be.

And what's left to do can often be purchased or outsourced.
List of clients that implemented new "health product" - say some diabetes program, etc. etc.

Given the experience of those clients and the claims of their individuals, can we use the claims of individuals from another client to more accurately gauge the value of each of these programs to them? Are we able to make detailed predictions about product offerings that don't rely on mean statistics of that client, but instead individual/claim level data?

Also, hospital networking decisions seem to be ripe for optimization. What I've seen in that space is super lackluster...

If we're limited to traditional actuarial outputs, then I agree that health has few opportunities. If you expand it to the company as a whole, there should be plenty of creative ways to use that information.

Can't talk about them all though cause how will I sell my consulting services later on? :P

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  #25  
Old 05-29-2018, 07:43 PM
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I’d be less concerned with predictive analytics and more concerned with data management from what you’re saying. You can’t compete in most healthcare payer spaces without knowing that part of the game. Given their answers on analytics and using outside vendors for certain core functions, I see some potential red flags, but I’m not sure how to dig into that while interviewing for a job.

In general though? Regional health plan is a risky proposition imo. Not necessarily a bad idea to work there, but the game is more skewed towards the big players than ever.
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  #26  
Old 05-29-2018, 07:46 PM
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List of clients that implemented new "health product" - say some diabetes program, etc. etc.

Given the experience of those clients and the claims of their individuals, can we use the claims of individuals from another client to more accurately gauge the value of each of these programs to them? Are we able to make detailed predictions about product offerings that don't rely on mean statistics of that client, but instead individual/claim level data?

Also, hospital networking decisions seem to be ripe for optimization. What I've seen in that space is super lackluster...

If we're limited to traditional actuarial outputs, then I agree that health has few opportunities. If you expand it to the company as a whole, there should be plenty of creative ways to use that information.

Can't talk about them all though cause how will I sell my consulting services later on? :P

-Riley
Your examples are elementary enough that Iím confident labeling you a charlatan in the health field. Health actuaries arenít restricted to traditional work, and I can vouch that they have been working on this type of work for years. Results are mixed.
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  #27  
Old 05-29-2018, 07:58 PM
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Many health insurers outsource their predictive modeling needs to consultants (I do a fair amount of this for carriers).

And yes, data management is a huge problem in health insurance. Or a huge opportunity, if you prefer.
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  #28  
Old 05-29-2018, 08:22 PM
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Your examples are elementary enough that Iím confident labeling you a charlatan
Them's fightin' words
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  #29  
Old 05-29-2018, 10:28 PM
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Interviewed with a regional health insurance company this week.

Asked the VP about their predictive analytics capabilities and how such techniques are used in the company.

Other than some off the shelf risk adjustment software used in the quality and care management departments, and a few tasks outsourced to vendors (e.g. fraud, waste, abuse department), they don't use these techniques anywhere, and have no staff dedicated to building/improving models. Actuarial teams focus on reporting and traditional actuarial work (report loss ratios, claim triangles, trend reporting, rate filings, etc.). IT has a BI group building reports/dashboards in tableau, but it's entirely reporting the news/explaining the past, not forward looking.

"We are not competing on analytics" was an exact quote.

Would this be a red flag to you in a job hunt?
Look at the bright side: you won't hear the word "analytics" that often.
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  #30  
Old 05-29-2018, 10:29 PM
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Your examples are elementary enough that Iím confident labeling you a charlatan in the health field. Health actuaries arenít restricted to traditional work, and I can vouch that they have been working on this type of work for years. Results are mixed.
Normally the "etc.etc" gives it away...
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