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Minimize Disruption by Maximizing Overlap

Posted by Susan Donegan on Thu, Aug 10, 2017

In order to minimize disruption for potential new clients, a dental plan needs to maximize its overlap with competitors' networks. In other words, they need to have as many of the same dentists as possible. What might be a manageable task when aiming to match up with a single competitor, this gets quite challenging for a plan with 8-10 significant competitors.network overlap.jpg

In the chart above, the blue circle represents Network A, a middle-of-the-pack network among the Top 15 dental PPO plans, while the gold circle represents the average of all of the Top 15 dental PPO plans. Network A, though quite large, only overlaps with its peers at a rate of 57%. This means that while 6 out of 10 access points in Network A's network are likely also to be in any given competitor's network, 4 out of 10 are not, and will potentially cause disruption for a prospective client. The challenge for Network A, as it is for all dental plans looking to grow, is to maximize their overlap with key competitors so that potential clients will experience minimal disruption when switching to their plan.  

Download our whitepaper, Recruit Smarter, Not Harder to learn how NetMinder data can help you target and recruit dentists more successfully and efficiently. 

Tags: market comparison, health insurance, disruption reporting, network overlap, network disruption

Estimating Network Disruption

Posted by Laura McMullen on Fri, Mar 18, 2016

Network disruption is an important consideration to an employer group planning to change insurance plans. People are attached to their doctors. A 2014 Becker’s Hospital Review/Survey Monkey survey asked people “how much they would have to save on premiums to choose a plan that forces them to change their primary care physician. The median response was a savings of $100 a month, but some people would ask for a lot more, including 28% who would want to save at least $200 a month.” 

That’s why disruption reporting is an integral part of many negotiations. Part of the plan selection process for large groups or self-insured groups is to run a disruption report using past claims experience to estimate savings in the proposed plan. But what do you do when you don’t have the claims data for a formal disruption report?

Using the Network Overlap report to evaluate disruption is a great option for smaller groups where the decision timeline is short and claims data unavailable.

disruption_graph.pngWhat does the Network Overlap report show?

This report compares two networks side-by-side, providing total, overlapping, and non-overlapping counts for each of the two networks by geographic area and specialty. ZIP codes with high overlap percentages will have less disruption than ZIPs with high unique percentages.

How does it work?

Upload your file using the UPLOAD ZIP CENSUS option in the geographic scope selection box and make the rest of your choices as usual to get started.  Running this report with custom census geographies simplifies your analysis:

  • Understand disruption for all employees in the same report. All of the ZIP codes in the file will be included in your report – even if they are not all in the same state.
  • Clarify network access in and around home and work locations. The report will return for the networks and specialties you select in the counties that contain the ZIP codes in the census file. For example, if 33433 and 33313 are in your census, the report will show Florida as the state and results in Palm Beach and Broward counties. Be sure to subtotal your report by ZIP5 to see the results for each ZIP code separately.

There aren’t too many opportunities to sell health insurance to a company that isn’t currently offering it to their employees. Demonstrating minimal network disruption can be the difference between a successful takeaway and a lost bid.

How do you estimate network disruption for current and prospective customers?

Tags: health insurance, disruption reporting, network change, ZIP codes and cities, network overlap, network disruption

 

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