Why can't insurance underwriters just trust my doctor's records?

It's a question that seems almost paradoxical in our data-driven world: if you've had regular check-ups and your medical history is documented, why can't an insurance underwriter simply review those records to approve your application? The reality is that while your doctor's notes are a crucial piece of the puzzle, they are rarely sufficient on their own. The reasons have less to do with a lack of trust and more to do with the fundamental nature of clinical data itself, its structure, completeness, and suitability for the specific risk calculations that underwriting requires. For insurers, navigating the gap between clinical records and underwriting reality is a persistent operational challenge.

A 2021 study assessing Electronic Health Record (EHR) data completeness found a mean capture proportion of just 16%-27% in a single EHR system across two large provider networks. (Weber, et al., 2021)

The data dilemma: why insurers trust doctor records for underwriting, but can't rely on them exclusively

The core challenge for insurers who need to trust doctor records for underwriting is that clinical medical records and underwriting risk assessment are designed for different purposes. A doctor's record is created at the point of care to guide ongoing treatment for a specific patient. It's a running log of diagnoses, medications, and observations. An underwriting file, by contrast, is a risk assessment tool designed to predict future mortality and morbidity for a large group of people with similar characteristics. This fundamental difference in purpose creates several practical problems when relying solely on a physician's electronic health records (EHRs).

The data is often unstructured and inconsistent. A significant portion of a medical record consists of a physician's narrative notes, which are difficult for automated systems to parse and analyze systematically. The same condition might be described with different terminology by different doctors, making standardization nearly impossible without significant manual intervention. Furthermore, records are often fragmented, existing in disparate, non-connected systems. An applicant may see a primary care physician, a specialist, and a hospital-based clinician, none of whose EHR systems talk to each other. This results in a scattered, incomplete picture of an applicant's health. Research from Weber, Avillach, and Palmer (2021) published in the Journal of the American Medical Informatics Association highlighted this fragmentation, showing that even within large networks, a single EHR system captures a surprisingly small fraction of a patient's total encounters.

This leads to several key issues for underwriting:

• Missing Information: EHRs are built to record diagnoses and treatments, not necessarily the absence of risk factors. Lifestyle information like exercise habits, which are highly predictive for underwriting, are rarely captured in a structured way.
• Data Gaps: When an applicant receives care from multiple, non-affiliated providers, no single record contains the complete history. This creates blind spots for an underwriter.
• Lack of Forward-Looking Data: Clinical records are retrospective. Underwriting, however, is prospective, seeking to price a policy based on future risk. A clean bill of health today doesn't provide the full context an underwriter needs to assess risk over a 20 or 30-year policy term.

These factors force insurers to use other methods to collect the necessary data, not because they don't trust the doctor's record, but because they can't build a complete risk profile from it alone.

Data Source	Process	Data Quality	Applicant Experience
Attending Physician Statement (APS)	Manual request to doctor's office; paper or PDF records returned	Highly variable; often unstructured, incomplete, or illegible. Can take weeks or months.	Passive; applicant waits for their doctor's office to respond. High potential for delays.
Third-Party Database Checks	Automated check of public records, MIB, and prescription history.	Structured and fast, but provides a limited, indirect view of health status.	Invisible to the applicant; happens in the background. Raises data privacy questions.
Paramedical Exam	A nurse visits the applicant's home to collect vitals, blood, and urine.	Standardized and comprehensive, but expensive and invasive. High friction.	Inconvenient; requires scheduling, time off work, and a physical encounter. High dropout rates.
Digital Health Assessment	Applicant completes a self-guided assessment via a mobile app, often using the phone's camera.	Standardized, structured, and instant. Captures current vitals and risk factors.	Convenient and fast (typically under 2 minutes). Completed from anywhere, anytime.

Industry applications of modernized data collection

The shift away from a total reliance on traditional doctor's records is impacting how various insurance products are underwritten.

Term life insurance

For term life, speed is critical. The long cycle times associated with retrieving and reviewing medical records are a major source of friction. Digital health assessments allow carriers to triage applicants, accelerating low-risk individuals into an automated approval path while flagging higher-risk cases for a more thorough review.

Final expense insurance

The final expense market is characterized by older applicants and smaller face amounts. The cost of a full medical exam or even an APS review is often prohibitive. Here, mobile-based health assessments provide a cost-effective way to gather essential health information without the high overhead of traditional methods.

Disability Insurance

Underwriting for disability insurance requires a nuanced understanding of both current health and potential future health risks. While a physician's record is important, it often lacks the specific functional data needed. Digital tools can supplement this by capturing data points related to lifestyle and wellness that are strong indicators of long-term health.

Current research and evidence

The limitations of EHRs for secondary data analysis, including insurance underwriting, are well-documented. A key study by Weber, Avillach, and Palmer (2021) investigated EHR data completeness and found that across different insurance cohorts (Medicare, Medicaid), the mean proportion of a patient's encounters captured by a single EHR system ranged from 18% to 30%. This confirms that relying on a single source of clinical data provides a severely limited view.

The researchers concluded that "data from a single EHR system represents a minority of the care a patient receives," underscoring the challenge for insurers who need a comprehensive health history. This fragmentation is a primary driver behind the industry's search for more reliable and complete data sources to augment what can be gleaned from a doctor's chart.

The future of underwriting data

The future does not lie in abandoning clinical data, but in supplementing it with more immediate, applicant-provided information. The trend is toward a hybrid approach where insurers use automated third-party data checks and applicant-completed digital health assessments to create a comprehensive risk profile in minutes, not weeks. This approach respects the applicant's time and privacy while providing underwriters with the structured, validated data they need to make fast, accurate decisions. By combining the breadth of historical data with the immediacy of a real-time digital snapshot, insurers can solve the problem of incomplete records.

Frequently asked questions

Q: If I give an insurer permission, can they see all of my medical records? A: Not necessarily. Your authorization allows them to request specific information relevant to the insurance application from the doctors, clinics, and hospitals you disclose. However, the completeness and format of what they receive can vary widely, and it often doesn't include your entire lifetime medical history across all providers.

Q: Why do I have to answer health questions if the insurer is getting my doctor's records? A: Your answers to health questions provide crucial context and fill in gaps. Medical records may not contain lifestyle information like exercise, smoking, or family history in a structured way. Your application answers help the underwriter build a more complete and accurate risk profile.

Q: Is a digital health scan as accurate as information from my doctor? A: These two sources measure different things. A doctor's record provides a historical view of diagnoses and treatments. A digital health assessment provides a real-time, standardized snapshot of your current vital signs and risk factors. Both are valuable, and insurers use them to create a holistic view of your health.

The insurance industry is actively working to solve the challenge of obtaining fast, reliable health data for underwriting. As technology evolves, companies like Circadify are developing tools that empower applicants to securely share their health information directly, streamlining the process for everyone involved. To learn more about how digital, applicant-driven data is transforming the underwriting landscape, explore our resources for insurance leaders at circadify.com/industries/payers-insurance.