This is the second in a series of papers covering findings from Munich Re’s studies on the protective and operational value of electronic health records (EHRs) in underwriting workflows. 

A reminder of our study premise: EHRs are becoming more common as a growing number of carriers integrate them into their underwriting processes. At the same time, EHRs have improved the amount and quality of information they capture.

To understand these enhancements and how they can be utilized, Munich Re completed a series of unique retrospective studies to find the protective and operational value of EHRs in multiple underwriting scenarios. The study included a sample of over 800 underwriting files consisting of business from multiple carriers that target middle to high-net-worth markets.¹ Broker, general agency, and direct-to-consumer distribution channels were included, as were traditional and fluidless underwriting paths.

The use cases studied included:

• Adding EHRs to accelerated underwritten cases, i.e., no labs or attending physician statement (APS)
• Using EHRs to replace fluids for fully underwritten business without APS (this paper)
• Assessing the impact of replacing traditional APS with EHRs

For this second study, 387 cases out of the 800 were identified as fully underwritten (insurance exam + labs). For the purposes of this paper, cases with decisions based on insurance exams and labs, along with application disclosures, will be referred to as the “Fluids” underwriting scenario. 

To conduct the study, underwriters first reviewed cases with fluids and an exam present but no EHR. They then reviewed the same case with an EHR but no fluids or exam. The difference in underwriter assessment of the risk of these two scenarios is the basis of the study. Cases with no EHR hit could not be used for this comparison.

Face amounts were limited to the $100,000 to $5,000,000 range. Issue ages were floored at 18 and capped at 70. These filters brought the study case count down to 350. The sample included middle and high-net-worth markets with distribution representing brokers, general agents, and direct-to-consumer channels. 

To ensure an independent review, we engaged external and internal underwriters to help complete the risk assessments. For consistency, they utilized the Munich Re EDGE underwriting manual to assess each risk in the scenarios indicated.  

Use case: Value of EHRs when replacing insurance exams and labs

Mortality savings and cost-benefit analysis:

The study captures 1) the underwriting risk class assessment for each policy when exams and labs are used in the presence of an application and MIB that do not require “for cause” underwriting evidence, and 2) when an EHR is used to assess those same cases instead of Fluids. Munich Re calculated the expected mortality based on the underwriting risk class decisions in both scenarios and assessed the protective value from EHRs overall compared to Fluids. A cost-benefit analysis was conducted to quantify the net financial impact in dollars per policy.

Methodology

• Table 1 shows the relative mortality assumptions by risk class that were used in the analysis.

• A count-based average expected mortality was calculated for both the Fluids scenario and the EHR scenario, based on the relative mortality factors outlined above. There were policies for which an assessment could not be made given the available underwriting evidence in the Fluids scenario and/or the EHR scenario. These undetermined underwriting risks were excluded from the mortality calculation, and therefore, the average expected mortality includes all policies that received an assessment in that scenario.    

• Assessments could have been considered undetermined for any reason the underwriter did not feel they had enough data to make a decision, such as cases with incomplete or old data. During the application process, an undetermined assessment would usually be followed by a request for more information, medical or otherwise.

• The mortality saving for using EHRs over Fluids was calculated as follows:
  Mortality saving % = Average expected mortality for EHR / Average expected mortality for Fluids - 1

• The mortality saving was further quantified in dollars per policy by projecting a present value of future death benefits (PVDB), which was used as a surrogate for the present value of premiums. The 2015 Society of Actuaries (SOA) Valuation Basic Table (VBT) with no mortality improvement was used as the underlying mortality basis. Lapse and interest rates were set to best estimate assumptions. Projection length was set to a 10-year time horizon.

• The net saving per policy for using EHRs over Fluids was calculated as follows:
  Net saving per policy = Mortality saving per policy (PVDB basis) - EHR cost per policy + Fluids cost per policy.

Broken out by age and face bands, we see that the mortality saving rate in this study is slightly higher for younger ages and lower face amounts. We do not break out issue ages greater than 60 due to low policy counts, unlike in our first paper evaluating adding EHRs to AUW programs.

We quantified the dollar amount of the mortality savings to be $304 on average per policy.² For this study, the average cost of EHRs, accounting for multiple EHR data sources per life and summarization services, is assessed to be $55 per policy.³ The cost for labs and exams based on typical programs is assessed at $75 per policy.⁴

While the study demonstrates positive net savings on aggregate, we further analyzed how the net savings vary by different issue age and face amount combinations. Table 3 summarizes the net savings per policy split by issue age and face amount bands. 

Decision rate and customer experience

In addition to providing additional protective value on mortality over Fluids in this study, using EHRs resulted in a slight increase in the decision rate, allowing a decision to be made in 75% of applications compared to 72% using Fluids. Decisions include approval, decline, and postpone assessments without further information needed. Table 4 shows the decision rates between the two sources of evidence.

The small difference in decision rates at these sample sizes makes it difficult to conclude that the EHR decision advantage will persist across multiple programs and studies. With similar decision rates, EHRs may retain a potential advantage for improved customer experience, quicker turnaround times, lower cost, and improved mortality protection. Approximately 50% of EHRs are typically delivered within one hour, 80% within 24 hours, and 90% within 48 hours, resulting in a closer to frictionless experience than exams and labs generally allow.

The hit rate for our EHR pulls was approximately 55%. This study was only conducted on cases for which there was an EHR hit. The decision rate will be lower for cases without an EHR hit and additional evidence will likely be required in many of these cases. 

Common themes EHRs help uncover

The study captures the reasons and corresponding evidence sources for why a risk class decision was made (or not made). We were able to analyze the reasons for policies whose risk class decisions were different using EHRs compared to insurance exam and labs.

For cases that were undetermined in the Fluids scenario but received a decision with EHRs:

There were 44 cases, or 13% of the study sample, that did not receive an underwriting decision in the Fluids scenario but received a decision with EHRs.

The risk class distribution after incorporating EHRs is shown in Table 5. We see that about half of the cases with EHR decisions were standard or better, with the remainder substandard or worse.

As illustrated in Table 6, EHRs identify a variety of medical conditions and build and/or weight changes. They are particularly proficient at identifying diabetes, mental nervous disorders, as well as cardiovascular and respiratory disease history.

For cases that received a decision in both the Fluids and EHRs scenario:

Table 7 shows the distribution of risk class variance for the 217 cases (62% of the study sample) that received decisions both in the EHR scenario and the Fluids scenario.

Evidence from EHRs resulted in a more adverse decision than evidence from Fluids did in a total of 34 cases. Conversely, there were 30 cases where evidence from Fluids resulted in a more adverse decision. EHRs found evidence for tobacco misrepresentation in two cases where Fluids found no evidence, while Fluids found evidence for tobacco misrepresentation in three cases for which EHRs found no evidence.

Table 8 shows common impairments EHRs found that resulted in a more adverse decision than using Fluids evidence.

The results of this comprehensive EHR study highlight the effectiveness of EHRs as a core underwriting tool, showing their potential value in fully underwritten use cases without an attending physician’s statement. Based on these study results, we can see benefits both financially and operationally through mortality and underwriting improvements by requesting an EHR first.

Insurance exams and labs are a current snapshot of physical findings. All applicants are evaluated based on the same criteria and standards – no more, no less. The quality and quantity of data in an EHR is very dependent on the applicant. They can include the same basic data as insurance exams, or they can include very deep longitudinal histories. In total, we see obtaining EHRs as a great first step for the underwriter in the presence of a clean application and MIB. Obviously, records must be available, but when an applicant has been to the doctor in the not-too-distant time prior to application, an underwriter may often make a fully informed assessment without the need for invasive testing. And, when factoring in the cost of an EHR compared to an exam and labs, we still see the potential for real savings. In addition to overall savings, our study shows that EHRs can add operational value by driving a net increase to the number of risk class decisions that can be accelerated without Fluids. 

Each carrier’s market and each applicant are unique. Requesting an EHR first makes intuitive sense to underwriters without needing a large study. However, you can also complete your own analysis to determine the impact on your specific business. We are happy to support you with this and have the tools, such as Automated EHR Summarizer and alitheia, to help you effectively integrate EHRs into your underwriting programs.

We look forward to bringing you our next paper in this series, where we review the impact of EHRs compared to APS-based underwriting. If you would like to subscribe and receive notification of this and future EHR retro study papers via email, please subscribe here.