Part of our Underwriter-to-Underwriter blog series

My meetings with member carriers spark interesting conversations where I often learn a new thing or two. We generally talk about application activity, any challenges they are having with EHR adoption and how I can help, or we chat about integrating data into workflows. However, occasionally something comes up that spurs a new way of thinking about how we use electronic data or, in this case, how we measure success relative to hit rates.

Last week, I had a call with a member carrier that has been using MIB’s electronic medical record data for approximately 18 months. In reviewing their search and release rate activity for the prior month, I noticed their release rate had dropped dramatically to 24% versus prior months’ results that were consistently north of 30%. Initially I was a bit surprised, but then I dove into analytical mode to find out ‘why’. Interestingly, the metrics showed that in a single month search activity increased threefold, yet the release rate declined. While this could possibly happen with a round of bad luck, it was inconsistent with MIB’s nationwide release rate of >30%. There had to be something new contributing the decline.

I questioned several possible causes for the activity spike - including asking if there was as a recent change to underwriting requirements or if new teams or units had started using the system. None was the cause. Then it occurred to me – was there a new use case? Bingo! The carrier had recently introduced a new product/program that uses a hybrid of a DtC (direct to consumer) and an agent support model. There was an obligation to perform a post issue medical record review for a small sample of the applications issued and they were using MIB’s Electronic Medical Data platform to accomplish this.

A new use case – one where NOT finding a record is not necessarily a BAD thing. The MIB Electronic Medical Data Service was a perfect customer ‘friction-less’ solution for this scenario. With no search fee and a low likelihood for a special authorization requirement, when compared to an APS, the member could meet the obligation of the treaty and avoid post-issue interaction with the customer. For me, this was an ‘ah ha’ moment.

As an industry, we have a somewhat myopic view of release rate activity. Higher always being better. For most use cases, this is true and MIB remains hyper-focused on release rate growth and new data sources and solutions to support this strategy. However, there are some use cases where a low release rate may be a positive thing. Such as, post-issue random audits and other forensic type of disclosure investigations. In these cases, low release rate data can prove to pricing actuaries and reinsurance partners that accelerated program requirements are actually working to place good risks on the books and eliminate the poor risks! Policy reinstatements and policy change management may be additional use cases where a lower release rate is a win. Operational units can use electronic medical data searches to verify that a customer has disclosed all pertinent medical information on abbreviated applications and expedite approvals. This is especially important for companies concerned with retaining existing customers vs. incurring the high cost of new customer acquisitions.

With these new use cases emerging, it will be important to understand the context of how electronic medical data is being used as we review and react to release rates. Because a high percentage of ‘hits’ is, in fact, NOT always a good thing.