Using data to assist in claims decisions

For auto casualty insurers, a focus on fraud detection requires differentiating medically necessary clinical treatment that is causally related to an auto crash. The solution lies with recognition of injury risk in the collision as well as linkage to health conditions that may influence the injured party’s evaluation and treatment. The combined assessment of specific injury risk and relevant clinical treatment in the unique circumstances of the vehicular trauma—at scale—demands technology.

Factors affecting claims costs

Increasing casualty claims severity continues to challenge P&C insurers, with costs outpacing the consumer products inflation and U.S. medical inflation rates. According to an April 2018 report by the Insurance Research Council, Countrywide Patterns in Auto Injury Claims, annualized claimed economic losses for bodily injury (BI) liability insurance closed claims increased 10% in 2017 compared to findings in 2012, while the average U.S. medical inflation rate was only 3%. The casualty claims inflation trend is notable given the types of auto related bodily injury diagnoses most frequently seen in the last three years have remained relatively unchanged and are predominately by nature soft tissue neck and back injuries.

For the period of CY 2014 to CY 2017, the top diagnoses for bodily injury claims in terms of overall dollars charged have remained unchanged, with neck pain or cervicalgia and neck sprain/strain among the top one or two positions for the last four years. From a frequency standpoint, we know that property damage losses occur nearly four times more often than a bodily injury claim; however, the claim payout trends are more than four times costlier for bodily injury claims.

Multiple healthcare developments are influencing casualty claims severity, including:

• changes in medical documentation practices with greater penetration of electronic medical records;
• wider acceptance of emerging evidence-based medicine guidelines relating to triage activation, diagnostic imaging in hospital emergency departments, and medical protocols for certain diagnoses; and
• new clinical procedure technologies and locations, including ambulatory surgery centers.

Another external factor influencing casualty claim severity is that the average claimant age continues to increase in bodily injury claims. Growth in this metric over the longer-term points to higher medical costs per patient as the treatment of older patients, all things considered equal, can become more medically-intense and with higher associated costs relative to the experience of younger counterparts.

Given advanced age, individuals may present during crash triage with inter-current health conditions, more use of medications, and physical or psycho-social vulnerabilities in the setting of acute trauma, complicating their initial clinical evaluation and management (E&M), and requiring more initial medical, surgical or diagnostic procedures.

Additionally, many of the top bodily injury treatment procedures, by their nature, have ranges to be considered when being billed. These ranges include the level of service selected or the number of units employed. The percent of claims that include these types of medical services has grown. Furthermore, with the increase of electronic technologies applicable to patient management, new capabilities in analytics and artificial intelligence in healthcare clinical decision-making can be used to inform treatment protocols, leading to further differences in local or regional medication and procedure prescribing.

Data analytics identifies trends

For many carriers concerned about rising casualty costs, data intelligence now plays a key role in qualifying injury causation and managing the outcome of a medical auto claim. Casualty claims comprise multiple layers of cause-and-effect physical metrics, many related to the vehicle, including its speed, immediate environment at the time of the crash (such as roadway conditions), and the type and severity of the crash.

Significantly, the impact-induced change in velocity (Delta V or g force), which can be recorded at the time of the impact, can serve as an excellent gauge of the severity of the forces experienced by the vehicle’s occupants.

Delta V is the gold standard metric for measuring collision severity and is highly correlated with injury potential. This information can inform adjuster decision-making as the extent of the injuries sustained by the claimant(s), possibly appreciated from the first notice of loss, may shift, or as evaluation and treatment unfold over time.

Many claims organizations have yet to take full advantage of the value of all the data they routinely generate and store daily. Too often, the data is left untouched, negating its value.

Research suggests that the fundamental to linking auto physical damage (APD) data to casualty data is recognizing and capturing the key common denominators. This capability has eluded the claims industry for decades, but the technology is now available.

As a result, smart analytics can assist claim decisions and processes in a simple and non-disruptive way. A casualty adjuster can retain awareness of the collision features related to the claimant’s injury throughout the life of the claim, using this information to differentiate medically necessary and causally-related medical procedures. Moreover, this information can be included in the insurer’s ongoing medical and general damage assessments, improving the consistency and accuracy of the claim’s final resolution.

By using acceleration and impact direction data across a carrier’s portfolio in addition to aggregated summaries and benchmarks of claims, resolution can be understood based on the same types of events in terms of impact direction and severity. This approach is an important distinction from previous reporting capabilities.

In the past, the industry could review the average cost of a neck sprain/strain in a given jurisdiction. In the current state, it is now possible, for example, to analyze the average cost of a neck sprain/strain in a given jurisdiction for the same type and severity of impact.

Creating consistent benchmarks, freeing up the adjuster’s time, reducing loss adjustment expense, increasing loss cost management accuracy and avoiding fraud are just some of the benefits to data analytics and artificial intelligence advancements.

From first notice of loss to estimating auto physical damage cost severity and potential severity of injuries, insurers that embrace these advancements will become the leaders in reducing claims costs, increasing customer satisfaction and improving business outcomes.

Chris Brew (cbrew@cccis.com) is senior vice president of casualty at CCC Information Services Inc.