Cost-Benefit Analysis of Underwriting Screening for Opioid Risks

Recently, the insurance laboratories have started to offer expanded screening protocols for opioids. There is one screening protocol for the natural opioids: Morphine, Codeine and Heroin. However, since the synthetic and semi-synthetic opioids have different chemical structures, additional screening protocols had to be developed to detect them. Additional screening is now available for methadone, hydrocodone, oxycodone and fentanyl.

With new screening options available, it is up to underwriting departments to determine how to implement them into their underwriting guidelines. From a financial point of view, it would be beneficial to implement the new screening protocol only for ages and risk classes where the expected savings from claims costs are more than the cost of the test itself. The cost of the full opioid panel is approximately $12 per application, but how do we calculate the expected claims savings?

As a starting point, we used CDC population mortality data² to estimate the implied claims savings under a best case scenario where the new underwriting protocol was 100% effective at declining risks associated with opioid overdose.³ Chart 1 shows the expected savings over 10 policy years⁴ for a $100,000⁵ life insurance policy. 

Based on these results we might conclude that it is worthwhile to screen all applicants for opioids. However, this would be an overstatement of the benefit as it has been shown that substance abuse mortality rates from life insurance populations are much lower than rates among the general population.⁶

Fully Underwritten Market

To calculate the impact on the insurance population, we used Munich Re’s own insured mortality experience⁷ which included over 1,400 claims due to overdose in order to estimate the claims savings in a best case scenario where the new underwriting protocol was 100% effective at declining risks associated with opioid overdose in the first year. Chart 2 shows the expected savings over 10 policy years for a $100,000 life insurance policy. 

As can be seen, the expected savings is considerably lower than that of the example based on general population statistics and somewhat less than the cost of the drug screening itself. However, we cannot immediately conclude that there are no uses for these screenings.

Smokers

Although there might not be a cost savings for including opioid screening across the entire portfolio, that does not mean that there aren’t pockets where screening could be beneficial. If we look at this same data split by smoking status, we see a significant difference in the cost savings for smokers verses non-smokers. At most ages affected by the epidemic, the expected claims savings for smokers is higher than the cost of the screening protocol (approximately $12).

Charts 3-4 show the same scenario as before, only now we see the results on a smoker distinct basis. 

Based on these results, one recommendation might be to implement a reflexive opioid screening on all applicants who have a positive cotinine test.

Middle Market

We have seen the significant difference in the set of results based on general population statistics compared to the set based on life insurance claims experience. Part of this difference is explained by the socio-economic makeup of the insured population. 

When we subdivide the general population into socio-economic strata (using education as a proxy), both mortality and cost savings decreases as you move up the socio-economic ladder.⁶

This can be seen in Charts 5-6 where the college educated population is compared to the general population and to the insurance population. The college educated subgroup of the general population exhibits mortality levels similar to the insured population, but not quite at the level of the insured population in early policy durations. The remainder of the difference can partially be explained by the benefit that is being derived by traditional underwriting during the initial years of the policy. 

However, as the industry tries to capture the middle market and move away from fluid underwriting towards accelerated or automated underwriting processes, these conclusions may not continue to be valid. Under these programs, new target markets may exhibit a different mortality level due to both the socio-economic effect and the change in the selection benefit from the more streamlined underwriting process.

Another consideration is that even if these screening protocols are 100% effective at determining if someone has used opioids recently, it will not automatically follow that the person is at risk of addiction or death. Thus the effectiveness of the implementation of the underwriting protocol will be less than 100%.