Combing Through Claims.

Sophisticated software can help insurers dig deep into financial and clinical claims data to tailor programs that help employers cut workers' comp costs.

Working more efficiently is the driving force behind the development of new technology and services in the business world. The workers' compensation industry also could use a healthy dose of the "work smarter, not harder" philosophy.

While many enhancements have been made to reduce costs, enable safe and sustained returns to work and improve overall outcomes, the workers' comp industry has the opportunity to take advantage of one of its most abundant resources: data. Comprehensive data analysis can yield the information necessary to pinpoint cost drivers within an organization and direct targeted managed-care programs.

One of the biggest challenges in the industry is accessing data scattered among insurers, third-party administrators, consulting organizations, risk managers, health-care providers and others. To move from this fragmented environment to one that is more consolidated, carriers and their vendor partners must educate employers about the benefit of outcomes measurements and work together to provide tailored processes to improve efficiency and overall results.

Data analysis is the key to creating customized programs that get to the heart of an employer's "pain." Sophisticated data-mining software provides insurance carriers, employers and third-party administrators with a variety of methods for identifying and analyzing high-risk workers' comp cases. Using data-mining techniques, carriers can detect patterns, relationships and trends that might not be obvious to even the most expert observer.

Looking to the Past

Insurance carriers have collected a wealth of data over the years in the claims-management arena. Now data can be organized in a way that allows the examination of past claims experience to help determine how to handle future cases. But more than claims data is needed to see the whole picture; it is important to incorporate an employer's clinical data into the analysis.

To begin, consider what can be measured when claims and managed-care data--including case management, utilization review and bill review--are combined. Factors such as disability duration are further explained when severity is introduced through medical-management data; cost drivers aren't limited to the data available only in claims; and benchmarking becomes more accurate and specific to an organization's overall experience. By combining claims data with managed-care data to evaluate an employer's experience, it is possible to pinpoint other cost drivers, such as highly litigious areas; high-cost job types; diagnoses and specific procedures that are most pervasive; and the abundance of a particular diagnosis in specific locations. Furthermore, the combined analysis can help show whether providers are returning employees to work in a timely manner, whether charges for provider services are consistent with that of their peers and whether services are being used efficiently. It also can help carriers compare s imilar claims and uncover discrepancies.

Consistent and aggressive workers' comp data-analysis strategies also can help identify high-risk claims, improve the quality of care for injured workers, resolve injuries and decrease lost time from work and overall claims costs. By looking at outcomes and determining what's happening with a particular book of business, insurance carriers can help employers identify what's going on with their claims and help reduce costs.

The first step in analyzing outcomes is to look carefully at an insured's claims history What type of injuries are occurring? Where and when are injuries most likely to occur? How long do employees remain out of work? What measures are taken to rehabilitate them and return them to work?

Joining Claims and Medical Data

Unfortunately, in today's workers' comp system, there is still a significant lack of data integration. A successful data-analysis strategy requires a joint effort among insurers, employers and providers of disability-management services. By combining their clinical-encounter and financial-claims data, it then becomes possible to measure and evaluate outcomes on several dimensions.

The key to optimal managed care is to identify claims that are at risk for being more expensive and longer lasting. Organizations that properly use determined outcomes measures can make sure the managed-care program that's in place is functioning--driving down costs while providing optimal care and reducing disability duration to well below industry benchmarks.

One of the first steps to achieving accurate outcomes measures is to gather primary claims and managed-care data. This includes information pertaining to lost-time duration, the impact of managed care, returns on investment and provider profiling. In addition, the analysis could include data from vocational rehabilitation and education, prevention programs and return-to-work measures. Pulling all of this data together can help determine where problems exist and allow for more accurate injury comparisons and more meaningful decision-making.

Once the appropriate data has been gathered, it's important to tie it all together. Different sources of data will involve different definitions, coding and categorizations of data sets. Without aligning all of these definitions, codes and categories, it's impossible to create credible benchmarks. While aligning the data, any gaps in information, such as inconsistent or missing dates, and injury codes, etc., will need to be identified and addressed. Any discrepancies can skew data sets and corrupt the analysis and any conclusions.

The data gathered can then be analyzed using a team approach, including claims and risk management, health-care providers and program administrators. Additional analytical tools might be needed to drill into the data to provide insight into an employer's specific claims and managed-care experience. After the data has been analyzed, the results must be acted upon.

The use of data analysis can help identify which claims will benefit most from case-management intervention, how soon claims should be referred to case managers and which claims should offer the best return on investment and cost savings.

Profiling Claims

Once the appropriate claims have been identified, the next step is to profile the descriptive characteristics of these claims in business terms and measure their cost and duration. These statistics will provide a baseline understanding of the targeted claims population to which more sophisticated analytic methods may then be applied to probe for patterns, trends or groupings of claims. In this manner, you can systematically recognize similar claims characteristics earlier in the life of a claim, using historical, closed claim data.

Accurate data analysis can help make the claims-management process much more objective and help employers implement targeted managed-care programs that focus on the most costly and complex cases.

Frederick B. Scardellette is vice president with Intracorp, a national health-care disability-management company.