Life insurance underwriting is a notoriously difficult and historically non-standardized process, heavily impacted by the quality of the health records used to make decisions. For On The Risk, The Journal of the Academy of Life Underwriting, Dr. Paulo Pinho, Discern Health’s chief medical and strategy officer, and Andy Kramer, vice president of underwriting risk and innovation at M Financial, explored the past, present and future of electronic health records (EHRs) in life underwriting, the need for interdisciplinary collaboration between underwriters, informaticists and technologists, and how data standards will revolutionize the future of the industry. A summary of the four-part series is below.

Part One: A Look Back

Historically, the life insurance industry has been slow to adopt technological innovations and has relied on antiquated systems. When the COVID-19 pandemic hit, traditional underwriting sources became difficult to obtain, forcing the industry to adapt in real-time and utilize EHR data in order to continue writing new business. However, it has not been the glass slipper that the industry needed. The data, which represents a longitudinal view of a patient’s visits to hospitals, clinics and doctors’ offices, helps to provide an end-to-end view of the patient journey. Paired with AI, these data sources have the potential to reshape the life insurance underwriting industry, but data source variability can complicate the creation of a cohesive patient view for life underwriters. In the first On The Risk article in the series, Electronic Health Records – Enablers of the Next Major Leap in Life Underwriting, the authors explore the strengths and weaknesses of EHR records compared with traditional systems and why implementation and data standard setting are needed for the future of underwriting algorithms and workflows.

Part Two: Developing Standards for Life Underwriting

Dr. Pinho and Kramer were joined by Nicolas France, data and integration architect at ACORD, for the second article in the series, Why Are Electronic Health Record Data Standards an Imperative? The latest Association for Cooperative Operations Research and Development (ACORD) data standard support the input and use of EHR data for life underwriting and highlight why data consistency and accuracy is critical. Specifically, the ACORD data standard increases efficiency, helping stakeholders make important decisions at faster speeds, improves effectiveness, helping organizations to reach goals, and remains flexible to adapt to constant and unpredictable changes within the industry. Adopting these standards will ultimately lead to savings due to less programming time, freeing constrained technology resources to focus on growth-driven projects. Armed with the ACORD Electronic Health Records Data Standards, the life underwriting industry is poised for a great technological leap, akin to the 1990s transformation from paper to digital image.

Part Three: Technology’s Influence on the Future of Life Underwriting

In the third article of the series, Electronic Health Records – Current State of Adoption in Life Underwriting, Tony Moreland, director of clinical and life insurance account management at Availity joined Kramer and Dr. Pinho to discuss the nuances of structured and unstructured data and how each can be leveraged to make underwriting more efficient. Defining an industry strategy for seamlessly integrating the changing and increasing data set is critical for its use in the underwriting industry. The authors defined a clear path forward to be cost- and time-effective, including the use of technology to enhance monitoring for and correcting bias within systems to improve the underwriting process.

Part Four: The Future of the Industry

Kramer and Dr. Pinho concluded the four-part series highlighting the next phase of EHR data standards and the underwriting optimization they will enable in On The Risk with Electronic Health Records – What Does the Future Look Like While access to EHR data has revolutionized the underwriting industry, to date, it has been led by large carriers with teams of data scientists dedicated to improving automation, excluding smaller carriers or those without the capital to invest heavily in automation. Data standards would provide uniformity and drive efficiency, effectiveness and flexibility throughout the entire life insurance value chain for all parties.

The creation of the Electronic Health Record Data Standards for underwriting will revolutionize the life insurance industry, creating significant automation and efficiency gains. These gains will benefit all, leading to more efficient communication among parties and enable automation of routine cases, allowing underwriters to focus on more complex cases. Standards will allow for cost-conscious technology connections and will enable reinsurers to receive files in the correct data format, helping to substantially improve underwriting efficiency.

How Discern Can Help

Data interoperability is a recurrent concept that has impacted all clinical data end users.  Challenges posed by the sheer quantity of data, comprehensiveness, variability, inconsistency, and quality make decision-making for those looking to glean insights and ascribe patient or population risk a barrier to entry for many clinical and nonclinical organizations looking to adopt a clinical data philosophy.  The life insurance industry has faced multiple forks in the road as technology has evolved; the shift from voluminous paper charts to PDFs, the adoption of a risk model premised on Rx data and now, the choice between digital automation vs. human abstraction are all examples.  These articles present the rubric for adoption and thoughtful implementation for clinical data into workflows and identify the challenges, opportunities, skillsets and patience required to use this asset in workflow for optimal results.  Discern gleans insights and automates morbidity risk determination for clinical use cases in high-risk populations – our thoughtful curation and feature selection could be the model for the appropriate use of clinical data in the life insurance space.


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