Prescriptions for Points of Pain in the Claims Process

For these top five issues, consensus was reached among all groups. Some differences did exist among the groups on other less highly rated concerns:

• Carriers saw fewer problems with the quality of claim personnel than risk managers (3.1 compared to 4.6).
• Smaller and mid-sized carriers had more concern about privacy laws than Tier 1 carriers (4.9 compared to 3.5).
• Smaller and mid-sized carriers also had more concern that their systems did not measure what was important (6.1 compared to 4.5).

Later in the survey, respondents were asked to rate the approaches used to deal with the points of pain. The following indicates rank order and average score of respondents (on zero-to-10 scale) for the various approaches seen as needed in order to deal with the key issues and concerns:

1. Reduce frequency and severity of losses (8.66)
2. Improve reserve accuracy (8.66)
3. Improve customer satisfaction (8.56)
4. Reduce loss costs (8.43)
5. Improve return-to-work results (8.4)
6. Monitor accuracy of medical provider payments (8.24)
7. Improve timeliness of incident reporting (8.19)
8. Improve accuracy of claim information (8.08)
9. Improve reporting of reserve changes (8.04)
10. Monitor timeliness of payments to medical providers (7.65)

Of particular interest was how technology was used to address these various issues. In the case of rising medical costs, several technology capabilities seemed to be employed. In the case of establishing reserve accuracies, technology seemed to be less utilized despite its perceived value.

These 10 items, and others, would be considered in determining what information should be captured and at what point in the process.

Improving the Information Lens

Two of the five biggest pain points related to data are lack of data standards and lack of metrics generated by the system that actually improve performance on key issues. The lack of effective metrics can be traced back to a specific root cause: failing to consider, at the time of capture and deployment, how data will be used to produce information that can support fact-based operations decision-making. Without that strategic approach from the outset, managers will be flooded with data but lack useful, actionable information that can help them accomplish their goals. To overcome this challenge, changes in technology need to be coupled with both process and organizational change.

In addition, there also should be an "information lens" applied, which is different than focusing solely on technology or process capabilities. The information lens specifically addresses the data standards and metrics of pain points.

For example, when a firm purchases new technology and then appropriately redesigns processes to improve performance, it still may fall short of its goals. The problem is likely that the information lens was not first applied to determine what data should be captured and at what process point in order to create the possibility for detailed granular analysis of claim-process efficiency and effectiveness. Effective information management requires well-designed processes that capture data flags upon entry and exit of activity in each process step (first notice of loss, claim assignment, inspection, estimation, etc.) and allow detailed coding of what is occurring throughout the life of the claim.

Applying an information lens provides companies with a more detailed view of claim life-cycle times. With a step-by-step, detailed analysis, managers can make targeted improvements to decrease life-cycle time in each process step. That has proven to be far more effective than just looking at the overall claim life-cycle.

One increasingly popular solution is the use of automated adjuster scorecards that supervisors can use to monitor and benchmark claim-process components such as cycle time, lack of activity, reserve adequacy, age of claim, status of investigation, subrogation status, and three-point contact.

Technology's Usefulness vs. Actual Utilization

The Katie School national survey probed and compared the perceived usefulness of 30 different claim technologies, as well as their actual utilizations. Exhibit 3 lists the claim technologies that participants were asked to consider.

Even with all of the influences on claim expenses, only a few technologies seemed to account for a statistically reliable improvement in results. Automated adjuster scorecards showed a correlation to reduced claim administrative expenses. One TPA firm executive interviewed for the study stated that his firm had reduced claim age by 10 percent and unnecessary claim adjuster time by 20 percent through use of an automated adjuster scorecard.

Some claim experts we spoke with have found that a best practice in claim handling is splitting responsibility for claim file activities to allow for parallel processing across different claim specialists. For example, collecting police reports or handling claim medical are given to separate groups. These experts believe that this approach can improve effectiveness and cycle time. In addition, greater understanding of the benchmarks within the claim-cycle components can enable effective specialization.

The caveat is that if the proper focus isn't placed on data management, scorecards can create less trust in the data.

Linking Data to Performance

To ensure the proper focus on the most valuable improvements, there must be explicit accountability and targeting by senior executives from both the business and technology areas. Of course, calculating the value of improvements requires that firms measure the outcome of their efforts. The following lists the kind of results that are measured and the percentage of firms capturing the information.

Percentage of Organizations Measuring Desired Results:

1. Improve timeliness of incident reporting (83.9 percent)
2. Reduce loss costs (73 percent)
3. Reduce frequency and severity of losses (72.5 percent)
4. Improve reserve accuracy (72.3 percent)
5. Improve reporting of reserve changes (71.2 percent)
6. Improve customer satisfaction (66.7 percent)
7. Accuracy of medical provider payments (62 percent)
8. Timeliness in payments to medical providers (66.1 percent)
9. Improve return-to-work results (56 percent)

One reason key metrics are not captured is because data standards are typically left to the IT organization. Because of their limited perspectives, they often miss the critical link between data standards and metrics, which is what creates the value in the information. Furthermore, there is often an accountability issue with data standards, as IT groups managing data standards interact with the business units (such as claims) who are creating new requirements for front-end applications to improve service and accommodate process exceptions.

To further complicate things, a business unit requesting the front-end changes may not be the group that truly cares about measurement and metrics. For example, one user of claim data is the actuarial department; they use claim data for pricing and reserving. They typically aren't involved in claim application changes even though pricing and reserving are critical to overall organizational success.

In summary, business and technology must jointly focus with an information lens to discover the clear links between operations, data, and the metrics needed for actionable insight if they hope to improve information management and address the pain of insufficient data standardization and ineffective metrics.

Dealing with Challenges

Claim professionals should know the challenges of operations, which have consolidated and now require them to deal with multi-faceted and complex issues in different geographic areas. The venue factor alone presents numerous challenges. Consider, for example, the Workers' Compensation Research Institute report on variation of cost drivers by state:

• Texas — utilization, especially of chiropractic care.
• Florida — hospital costs and the use of hospitals in primary care.
• Illinois — ancillary medical services and diagnostics.
• Tennessee — surgery rates.
• Missouri — higher rates of attorney involvement.

Utilization treatment fees also vary by venue and this also affects claims. Illinois and Tennessee (where there are no fee schedules) pay much more for similar treatments than employers in similar states that have fee schedules (like Kentucky). Differences in the way permanent partial disability (PPD) claims are evaluated and resolved are dramatic, especially when comparing states that have medical panels to those that do not.

Technology certainly has an important role in dealing with this challenge. Because of the variability in cost drivers by state, it is critical to perform rigorous analyses of drivers of loss and administrative expenses prior to embarking on broad technology development or substitution.

The standard or ad-hoc reporting methods provided in many claim managerial reports frequently are not designed to account for these state-by-state differences. Getting real insight requires doing complex statistical analysis by integrating available datasets to determine how operation factors, claims characteristics, claimant demographics, and other independent variables impact dependent variables of performance (frequency, severity, satisfaction, etc.). Doing this type of analysis helps provide greater insight on the root cause of issues prior to making misguided technology investments.

One common example is the variation in data that can be viewed by state. Frequently, fraud analysts are constrained in the data they can view through canned queries. They require more flexible support from IT in allowing them to use more ad-hoc data in order to effectively identify and deal with fraud without running into regulatory compliance problems.

The Technology Paradox

Despite the positive perceptions and correlations of technologies to workers' compensation results, the study showed no overall correlation between technological sophistication and results. Firms were given a score of between zero and 300 based on the number of technologies they had and their level of utilization of these technologies. A firm that completely utilized all 30 technologies listed in this survey would have a sophistication score of 300. The highest score in this group of respondents was only 250.

Some technologically sophisticated organizations reported excellent returns while others at the same level did not. On average, there was a positive correlation between results of technological sophistication, up to a mid-range of sophistication (120 out of a score of 300). Beyond that point, the results of technological sophistication became more uncertain and even negative overall for all groups. The results became less "generalizable" and instead depended more on the particular ability of the individual company to integrate and leverage its technology.

Several explanations have been offered to explain this phenomenon. One possibility is that as companies have added more technology, they have failed to properly integrate their systems and redesign processes. The number of vendors used also might be a consideration. Another possibility is that the companies with high levels of technological sophistication have already maximized returns on mature technologies. This would explain why the smaller, less sophisticated Tier 4 insurers are just now seeing results in loss costs. Adjuster turnover also is a potentially complicating variable. Some practitioners suggested that some companies should do a better job of getting new adjusters up to speed on how to most effectively use technology. Because adjuster turnover was rated as a higher concern for the Tier 1 companies, and because these were the most technologically sophisticated, it could be due to turnover. Many of the smaller regional carriers (and often less-sophisticated ones) have less concern over adjuster turnover.

What accounts for performance differences? Many companies say they use technology; however, experts have found it is the effective use of the technology that creates true sophistication and improved performance. Systems must be integrated with other systems in a cost-effective way to minimize design and development time, maintenance costs, and overall environment complexity. Experts suggest that this is one of the single biggest drivers of IT performance.

Jim Jones is the Director for the Katie School of Insurance at Illinois State University. Michael Williams is Professor of Marketing at Illinois State University. Paul Blase is a partner in the insurance industry practice at management consulting firm Diamond Cluster International.