Optimizing medical claims: the case for structured information

Optimizing medical claims: The need for structured information

Published: Jul-15-10

In a March 2010 article for Claims Magazine, I talked about the challenges in optimizing medical claims. Last month, I discussed the need for key performance indicators. This week, I will talk about the need for structured information.

Methodology and results

The research for the article was conducted from interviews conducted in July and August of 2009. Accenture worked with an independent firm and spoke with 30 senior claim executives at major US property and casualty insurer.

The majority (79 percent) of insurers believe that their medical records processing is not fully optimized.
One out of three executives mentioned difficulty in accessing medical information.
Nearly half (47 percent) of those surveyed cited illegible handwriting as being a problem.

Given that US property and casual insurers pay out an estimated $50 billion in claims annually, these findings are significant.

Structured data

Medical records contain extremely important information for claims processing, and also for data analytics. However, as this study showed, insurers have difficulty accessing the information in medical records. Accenture believes that investment in information technology in this area, with a shift to a structured data approach, is necessary.

By implementing structured data, insurers can standardize the way that they access, analyze and report medical information. Further, by streamlining the process, more complicated claims can be allocated to senior claims adjusters. The overall effect is an increase in efficiency and a decrease in cycle times. Further, by standardizing data, adjusters can access all the information they need, when they need it, so that claims are processed more accurately.

Data analysis and advanced analytics

Moving to a structured data approach will also allow insurers to perform data analytics. By building a database of consumer attributes, needs and preferences, insurers can implement a market segmentation strategy. Predictive modeling can also provide insight as to what customer needs might be in future.

Advanced analytics would also have immediate and direct benefits, especially in improving indemnity accuracy, recovery identification and capture, and fraud detection and prevention.

What challenges do you foresee in moving to a structured data approach?

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May-08-12

I think insurance companies will face internal opposition when trying to shift to a more structured data approach, as people working in the organizations have become used to the set ways of doing things and processing information and may be unwilling to move beyond their comfort zone.

Apr-26-12

One reason for the rise in cost for insurance is perhaps the lack of a streamlined process and lack of structured information. There is a lot of inefficiencies, that with proper data analytics and the the cooperation of other insurers, can help improve the system.