In parts 1 and 2 of our series, “An Exposure Driven Approach we examined how the liability claim exposure model is the foundation for both claims management, organizational efficiency and structure. In this article we look at how the claim exposure model can also be used as the driving element of the liability decision support system, and how that system can utilize the exposure model to provide an organization’s claim representatives with the right tools at the right time to maximize claims handling effectiveness.
To understand the concept of the liability decision support system as a platform rather than a product, it is helpful to view the liability decision support system not so much as a simple claims handling mechanism but rather as a system that is designed to collect and organize claim information on a continuing basis. This type of information can then be used to develop ongoing claim exposure models. On the basis of those exposure models the proper analytical tools (resource profile) can be provided to the claim representative for the most expeditious and advantageous settlement of the claim.
Elements of Exposure
To accurately model exposure prediction levels on a continuing basis throughout the lifecycle of a claim, the liability decision support system needs to be able to assess all of the individual factors which contribute to the overall exposure level of the claim. These factors can change over time, and changes to any of them can affect the predicted exposure level. The liability decision support system must continuously assess and respond to any changes with updated claim exposure predictions and toolbox resource requirements. Exposure factors fall within four general areas – general claim, injury specific, medical information and negotiation factors (not all claims will have factors / information within all areas).
General Claim Information
There are a number of factors and variables that are considered in the prediction of exposure and can dictate the resource profile for the claim, for example:
Age of the claim – Older higher exposure claims may require more resources, for example, they may require the claims representative to do additional investigation as well as include expert analysis. Additionally, they are more likely to be attorney represented / litigated.
Location of the claim – Exposure potential is affected by the locality of the claim, for example the likelihood of large jury awards. Medical costs are also affected by the location of a claim.
Mitigating and/or contributing factors – These are important to the claims representative’ evaluation of the claim for both the insured and the claimant.
Claimant specifics – For example occupation, age, earning level / potential, health status, credibility and reliability, history, etc. can affect the exposure and ultimate outcome of the claim.
Nature of claim / components – Nature of loss, injury, injury factors, medical specials, pain and suffering, self-represented, attorney represented, etc. from a historic perspective are key elements of exposure prediction.
Injury Specific Information
As we look at the dimensionality of a claim and the going exposure prediction, injury information developments become a primary predictor of overall exposure for example:
Initial injury assessment – Ambulance, hospital, diagnostic and treatment records at time of injury.
Injury and medical record evaluation – Subsequent treatment and diagnostic records and component evaluations exposure key predictors for claim exposure development.
Mechanism of injury – Assessment to insure treatment is consistent with diagnosis and no preexisting conditions, degeneration etc., are present or receiving treatment.
Treatment utilization – Progress assessment versus authorized medical specials to insure treatment numbers and payments within normal range.
When looking at a claim from a multidimensional perspective, exposure deviations, severe factors, injuries diagnosis or sudden changes in medical specials during the life of claim can be used and change the profile of a claim in the liability decision support system / platform. Claims with severe injuries at initial filing, or claims where medical specials suddenly spike or otherwise exceed the normal predicted exposure level will trigger the liability decision support system to deploy a detailed mechanism of injury investigative tools.
Medical History and Treatment Information
Injury causation and the qualification of treatment are key elements of liability claim handling and a liability decision support system / platform. Correlation of injuries, diagnosis, and the treatment (ICD9/10 and CPT codes and their correlation to the physical injury mechanisms) are important elements of the medical handling process. Additionally, these elements establish a baseline for the analytical processes that are the basis for establishing injury causation and financial predictors.
Other areas that have direct adjudication elements such as usual and customary rate analysis for over-billing via geographical area, specialty, etc. can help give a relative measurement for claim representatives. Physician fee schedule (Centers for Medicare – Medicaid Services) analysis, comparison for service charges and other ancillary services for medical cost containment all contribute to the establishment of a baseline for normalized medical units that provide a consistent exposure base. The medical dimension of the exposure model is a key predictor to the overall financial elements of a claim. The liability decision support system / platform must allow claim representatives to not only adjudicate medical, but must also utilize the results in the overall exposure model that drives the settlement process and resource profile for the claim.
Ongoing exposure prediction, as well as prediction of the key negotiation factors allows the claim to be presented to the claim representative in proper context. Additionally, the prediction driven process allows the determination of the resource profile for the claim (Turner and Zizzamia, July 2008). Below are examples of prediction of the key negotiation factors and modifiers of the negotiation platform:
- Contributory negligence and comparative fault analysis and documentable application to settlement offer ranges.
- Use of insurers’ historical data and industry standards for advanced profiling and case correlation.
- Quantification of the effect of attorney representation on probable settlement outcomes.
- Individual analysis of attorney records and venue specifics.
- Pre-existing conditions effects on negotiations and settlement outcomes.
- Strength of case prediction to provide claim representative settlement guidelines.
Exposure Model: Analytical Approach and Tools
Exposure modeling should be seen as a dynamic and continuous process throughout the lifecycle of a claim. At any given time, the exposure model generated by the liability decision support system provides a snapshot of the predicted exposure given all of the available information at that moment. However, truly sophisticated exposure modeling is much more like a movie than a snapshot or series of snapshots. It is both continuous and reactive to changes in predicted exposure as they occur.
Changes in any of the elements of exposure during the claim life-cycle will cause corresponding changes in the exposure prediction model. A sophisticated liability decision support system will react to those changes by automatically providing the analytical tools to the claim representative that are best suited to investigating and resolving the claim given the level of exposure prediction. The tools available to the claim representative will vary on a continuing basis as the predicted exposure level of the claim varies (Ayuso and Santolino, 2008/07).
The tools available to the claim representative can be thought of as resource profile / platform elements. The availability of the platform elements varies with the exposure prediction level of the claim. High exposure level claims that require in-depth investigation by the claim representative will see a greater number of platform elements presented to the claim representative than will relatively simple low-exposure claims.
Data and information generated by the claim representative through the use of each platform element is used by the liability decision support system to continuously refine the exposure prediction level of the claim. As exposure prediction levels change, the liability decision support system continuously responds to those changes by providing the claim representative the platform elements best suited to analyzing the changes and minimizing exposure levels.
Platform Elements/Exposure Analysis Tools – examples
Understanding each of these tools and how they incorporate new data into the exposure model is critical for heuristic process exposure evaluation. Each of the products incorporated into an exposure driven platform allows for the utilization of appropriate tools given the overall exposure of the individual claim.
Medical Bill Review
Medical cost contentment is a critical function of a liability platform. The elements of the adjudication process are also a large adjustment expense. A platform that can differentiate exposure can select the elements of adjudication. These elements can be incorporated and triggered by; different medical bill processes (including medical utilization prediction), usual and customary rate data, expert analysis requests, provider sequencing flags etc.
Medical Profile Review
Nurses, specialists, experts etc., understanding the aspects of the medical review that includes medical history and reports specific services can be incorporated into the claim evaluation process given the triggers of these factors within the development of the case.
Expert Witnesses and Reports
Integration into legal services for attorney representation and the evaluation of the strength of case based on the progression of the evaluation process case analysis using quantification of expert reports and other specialists can add additional dimensionality to the exposure model.
Medical Records Review
For a certain case the specific medical record subject to review can provide date of service sequencing that can be added into the exposure model and change the exposure base for the predicted engines for general damages.
Police report retrieval and review
Services such as police report retrieval and review can also be incorporated based on factual information in the development of the case. In many organizations such services are used as a matter of fact. When straight through processing based of key predictive nodes each service has a defined role in the claim process.
An investigation may also include sophisticated techniques such as accident reconstruction. These types of techniques can be warranted given questionable factors surrounding the accident and the injuries that are being claimed. Most importantly if the exposure prediction mechanisms are accurate these techniques can be used effectively establish injury causation.
There are a number of techniques that can establish mechanisms of injury. These techniques can be incorporated to show causation within the process of evaluating the injuries and the circumstances surrounding the individual case.
The ability for a liability support platform to communicate factual and predicted aspects of a claim to the representative so that the full context of the case is apparent during the negotiation phase of a claim is critical. Unobvious concepts related to strength of case and fraud indicators can be extremely important. Additionally, given the circumstances of the case support modules that discuss the injuries that are being claims and the causation factors can help the claim representative.
Tools – Note
Each of the exposure factors and tools can be taken in any specific order; however, the order and number can be designed by the organization to address key strategic goals and individually incorporated into the exposure platform. The point about tools is that they should be incorporated based on exposure of the claim and that all claims should not be forced through tools – tools are based on exposure there by utilizing services, maximizing efficiency and minimizing loss adjustment expense.
There are three major drivers to the evaluation of a liability decision support system / platform, (1) assisting the claim representative to understand the key elements of the claim information as it develops, (2) providing predictive elements of key financial nodes within the liability handling process and (3) the utilization of claim organizations tools / resources that will aid in providing the best outcomes of the claim process, thereby, minimizing the overall loss cost expense for the organization.
In this segment we continued to provide food for thought and encourage the thought process that can inspire the reader to examine their existing claim processes with a renewed perspective.
Ayuso, Mercedes and Santolino, Miguel (Working Papers 2008/07): p1-24: Forecasting the maximum compensation offer in the automobile BI claims negotiation process. Research Institute of Applied Economics 2008
Turner, Kevin A and Zizzamia Frank (July 2008): Predicting Better Claims Management. Risk and Insurance Management Society. Retrieved 9/1/2012 from: http://www.rmmagazine.com/MGTemplate.cfm?Section=MagArchive&NavMenuID=304&template=/Magazine/DisplayMagazines.cfm&Archive=1&IssueID=324&AID=3706&Volume=55&ShowArticle=1
(CC) September 2012 Vatti-Manhattan Group
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