Electronic health records are currently undergoing widespread adoption in the United States.
The use of EHRs by health care providers more than doubled in the United States, from 42% to 87%, from 2008 to 2015, and currently at least 84% of U.S. hospitals now use them, according to the Office of the National Coordinator for Health Information Technology's Health IT Dashboard.
As physicians and consumers grow increasingly comfortable with the technology, EHRs are creating a new reality for life insurers. Still, the question remains, how will life insurers use EHRs?
The life insurance industry is breaking new ground in its efforts to correlate clinical data, health claims data, and patient-generated data in order to derive the complete story of an insured's health or risk status. However, challenges remain in a number of areas, including how best to develop a system that allows all essential data to be delivered to the right places and provides information that is easy to access and use.
Why is understanding and interpreting digital health data such a challenge?
First, the sheer amount of data included in EHRs is overwhelming. Digital health data (DHD), a reference to both clinical data and medical claims data, is complex and has many layers. Because of this, understanding DHD is like learning a new language, with all the nuance of communication—context, conjugation, dialect, etc.
Structured EHR data is represented by several medical coding vocabularies, each of which consists of thousands of codes, including diagnoses codes, procedure codes, drug codes and lab codes. For example, there are nearly 95,000 ICD-10-CM codes alone, and ICD-10 is just one of many standardized code systems used in health care. In addition, these codes can vary based on whether they are being used in a clinical or claims/reimbursement setting.
The result: Carriers trying to use DHD can be overwhelmed, and too much data makes the process slow and ineffective.
New ways of aggregating and distributing EHR data are emerging. In much the same way that the industry went through a transformation with prescription history data, a new landscape around the use and application of EHRs in insurance is taking shape. By transforming raw data, we can make sense of the various data sources and efficiently digest health data for use in underwriting.
Each interaction with a physician, medical system or pharmacy is a piece of an individual's health care story. From conditions and tests to therapies, prescriptions, and use of medical equipment—all of this is important information for insureds, and companies can benefit from expert interpretation of this data.
By interpreting, analyzing, cross-referencing and organizing data, it is possible to score data from all of these sources, transforming the raw data into an assessment, or score, which is provided to the insurer. In much the same way insurers can receive a prescription score, the DHD score can streamline the underwriting process.
The industry has been working for some time to bring EHRs to life insurance, and that work is paying off. We are breaking new ground in efforts to correlate clinical data, health claims data, and patient-generated data in order to derive the complete story of an insured's health or risk status.
EHRs are already transforming underwriting. How will you make them work for you?
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