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The NetMinder Blog

Five Best Practices to Find the Right Provider Network for Your Customers

Posted by Laura McMullen on Thu, Jul 24, 2014

In a recent blog post entitled, Five Best Practices to Use Network Data and To Grow Your Business, we wrote about the ways carriers and network leasing companies can improve their position in network comparisons by better cleaning their data. Another point of view is from the brokers and consultants who use network analyses to help their customers choose the right benefit plans.

health insurance plansShopping for employee benefits is complicated and time consuming. Employers and other plan sponsors typically rely on a broker or consultant to help them through it. Brokers and consultants know that network issues can turn a satisfied customer into one that goes out to bid in the blink of an eye. Even if everything else is right: price, benefits, service, and timely and accurate claims payments can’t outweigh a network that doesn’t fit the employee population.

As we pointed out in our other post, the best networks:

  • Offer a wide range of choices: multiple general and specialty providers are included in the network
  • Are convenient to use: providers are located near home or work
  • Include popular providers and facilities: providers are the ones that members and their families want to use
  • Save employers and employees money: in-network providers offer meaningful discounts that reduce out-of-pocket expenses and claim costs

Depending on the number of employees your customers have, different types of network analyses are probably available from your carrier partners. Generally, we see four types of network analysis:

  • Network Counting – measure the quantity of providers in each network (available for groups of all sizes)
  • Accessibility Analysis – correlate network provider locations to employee home and work locations (available for groups of all sizes)
  • Disruption Reporting – match historical provider utilization and claims experience for a group to the providers in a different network (available for groups with at least 200 employees)
  • Repricing – compare cost of claims for all providers (in- and out-of-network) if a different network were in place to the cost experienced in the current network (available for very large or self-funded groups)

Download our whitepaper, The Network Analysis Pyramid, to learn more about each method.

As the primary users of network analyses, brokers and consultants are in a unique position to influence the requirements of each type of analysis. Keep these five best practices in mind as you work with carriers on your customers’ behalf:

  1. Insist on clean, accurate data so you get clean, accurate reports.
  2. Clearly identify required fields and formats in all file requests.
  3. Obtain claim data from the incumbent carrier whenever possible.
  4. Choose a consistent counting method for all reports to ensure that you are comparing apples to apples.
  5. Evaluate key specialties separately from the overall network based on your client’s needs.

With all of the changes from the Affordable Care Act, employers and other plan sponsors are relying on brokers and consultants more than ever.

How do you evaluate networks today?


 

Tags: compare networks, data management, market comparison, network metrics, dental network, network providers, health insurance, Affordable Care Act, network comparison tool, disruption reporting, data analysis, network change, Healthcare, healthcare reform, health reform, ACA, healthcare exchanges, provider networks, health insurers

When Is a City Not a City?

Posted by Laura McMullen on Wed, Mar 26, 2014

One of the most common questions we get from NetMinder users when they run reports comparing provider networks in specific cities is why aren’t there any providers in ______________? (Fill in city name here.)

Often the reason is that the client’s definition of a city is different than the preferred US Postal Service definition. That’s why, to ensure you always get apples-to-apples comparisons, we base the city designations in NetMinder on the USPS preferred city designation. 

  • Cleveland is a good example. There are a number of ZIP codes in Cleveland that have both preferred and acceptable city names. See list below:

Cleveland zips resized 600

  • Here’s a screen capture from www.usps.com for zip code 44118 for an example of preferred and acceptable city names.

Cleveland preferred

So, what can you do when you’re running a NetMinder report to avoid this problem? The best thing to do is to run your report at the ZIP code or MSA level. Those geographic areas are more firmly agreed upon than city names. MSA, or Metropolitan Statistical Area, reports can be helpful in this situation because city names are included in the name of the MSA, i.e. CLEVELAND-ELYRIA, OH. If you choose to run a county report, I recommend including city and 5-digit ZIP subtotals to make sure that you include all of the areas you need since county names might not be as familiar as city names.

Try this tip out when you log into NetMinder next time and let us know how it goes in the NetMinder User Group on LinkedIn.

 

Tags: compare networks, data management, business intelligence, data analysis, provider counts, ZIP codes and cities

Overwhelmed by big data?

Posted by Aaron Groffman on Tue, Jan 22, 2013

Netminder powerfuldataBig data was a hot topic for businesses in 2012, and according to a recent Forbes article, it will be even hotter this year when consumers really start to see its impact in everything from retail to healthcare.

The already vast volumes of information that exist online continue to grow every day, presenting enormous opportunities for businesses. Collecting and analyzing these large data sets, aka big data, can help companies make better decisions, predict probable outcomes, cut costs, identify new business opportunities, close more deals and retain more clients.

But how can businesses access the immense amount of information that is available and harness it for effective business intelligence?

Businesses, especially smaller companies, encounter three main challenges when trying to tackle big data, according to a recent article in Inc. First, many don’t have access to big data. Second, they may not have the technology and relational databases needed to easily pull the data. Third, many businesses don’t have the expertise on staff to analyze the data (e.g. a data scientist and a team of analysts).

David Selinger, a founder, CEO and data scientist at RichRelevance who formerly managed data mining and site optimization at Amazon.com, offered some tips for handling big data in a recent article. He suggests that businesses find experts to help them manage and analyze data, take advantage of the cloud, protect privacy, and of course, execute, test and measure.

Do you have experts lined up to take advantage of your big data opportunities?

Tags: data management, business intelligence, big data, data analysis

 

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