In the final article, we will look at Measurement and Peer Comparisons through the prism of the exposure driven approach. We’ll examine the need for user “tunabilty” of both exposure thresholds and the toolsets available to the liability decision support system.  We will then close the series with a recap and overview of how a liability decision support system, with advanced exposure modeling capabilities, will benefit the claim organization at both the adjuster and organizational level.

We are pleased to announce the development of our new electronic brochures and flyers, describing our services and products.  We would also like to take this opportunity to briefly provide you with some background regarding our company.  VMG is a relatively new face in liability decision support systems, with a unique methodology that truly captures best practices and brings consistency to your organization.  We are a client-centric company with a simple approach; understand what is unique about our client’s environment and tailor a solution to fit their needs.

Our product Exposure manager XM combines all of the key informational aspects of the liability claims process.  The XM platform consists of modularized liability components that allow you to blend any number of your third party vended and in-house tools into a holistic single point access tool for your liability claim representatives.   Our technology staff, service center and customer service staff are the best in the industry.

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As always, we encourage our readers to contact us with questions, comments on our articles, or on other topics of interest to the insurance community in general. It is through the free flow of ideas that knowledge and insight flourishes. Please feel free to share your comments, suggestions or observations with our readership – which is made up of leading insurance professionals nationwide. To post your comments, click on the “Leave a Response” link located at the end of the article.

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.

Negotiation Factors

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).

Tools/Platform Elements

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.

Accident Reconstruction

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.

Causation Analysis

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.

Negotiation training/coaching

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.

Conclusion

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.

Bibliography

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
This article may be copied and distributed freely provided that you keep this copyright notice intact and is provided for free and without charge.  We have to the best of our knowledge abided by all copyrights, trademarks and quoted material.  Any comments, omissions, misuse concerns etc. regarding the use of trademarks and copyrights should be directed to info@vatti-manhattangroup.com.

In Part 1 of our series, “An Exposure Driven Approach,” we examined the key role that the liability claim exposure model plays in the management of a claim throughout its lifecycle. In this article we will look at: how the liability claim exposure model complements the workload quantification model; how it can be used by the organization to quantify and distribute individual workloads in order to maximize adjuster efficiency through effective triage; and finally, how it can also be used to develop the most effective staffing profile for the organization as a whole.

Utilizing the liability claim predictive exposure model in workload quantification requires an organization to have a thorough understanding of its claim servicing model, and how that model drives the allocation of available resources. For the purposes of this series of articles, the term “claim servicing model” can be thought of as the management defined prioritization of resource allocation based upon how the organization has defined its liability claims organizational structure. We will see that the claim servicing model chosen by the organization will significantly define the organization’s focus, structure, workflow, and staffing model.

Claim Servicing Model

Claim liability can be characterized in part by the structure of the claim servicing model around which the organization has been designed. For example, a liability organization can be designed around a geographic based claim servicing model. In such a model, the organizational thought is that the workforce of liability adjusters who are highly specialized in the local laws, customs and norms within given geographical areas can accurately assess exposure potential and guide claims through the most advantageous settlement process, given the idiosyncrasies of the jurisdiction governing the claim. (Consider for instance jury damage awards likely to be decided by a jury in the Bronx, New York, versus a jury in rural Texas.)

A liability organization structured around a geographic claim servicing model will require a workflow model that triages claims to adjusters based upon the adjuster’s familiarity with the locale of the claim. If claims are assigned to adjusters outside of their geographic area of expertise, the efficiency of both the individual adjuster and of the claims handling process as a whole would be expected to have less positive financial outcomes for these assignments; hence triage would first focus on geographic area.

Geographic based claim servicing models represent just one of the possible structures of the claim liability organization, and is used in this article to emphasize the point that whatever foundational structure is implemented (from specific geographic offices to one of centralized service centers), that structure will act as the organizational base of the liability group. An exposure driven claim servicing model is a complementary framework around which the organization triage can be enhanced.

Exposure Driven Claim Servicing Model

In an exposure driven claim servicing model the adjuster workforce is designed based upon exposure potential of the types of claims handled by the organization. For example, if an organizational analysis of claim patterns reveals that the greatest claim frequency potential lies in soft tissue injuries, the organization would structure its workforce so that its liability claim adjusters have an exposure delineation with soft-tissue injury expertise predominant within the claim process, complemented with adjusters with expertise within other injury types. Likewise, it would structure its workflow so that the exposure delineation of soft tissue injuries would be directed to those adjusters with the most experience, or those adjusters with expertise in the particular type of injury reflected in the claim.

Claim servicing models based on exposure can take other base or complementary forms. For example, the litigation/attorney representative driven model can function in a complementary role to the exposure driven model. In this model the organization structures its workforce with adjusters skilled in the negotiation techniques and strategies that might be required during any portion of the lifecycle of the claim. For example, an adjuster will use different negotiation styles depending upon whether the adjuster is negotiating directly with a claimant or with a claimant’s attorney. Claims workflow in this model is characterized by triaging of claims to the adjuster best suited to the particular type and style of negotiations most likely to result in a satisfactory resolution of the claim.

The claim servicing models mentioned above are general examples that highlight functional structures within a liability organization. The model adopted by any organization will be dependent upon the requirements of the specific organization, and will be determined by senior  management of the organization. Notwithstanding, exposure and more importantly predicting exposure and triaging, are the key elements within an organization’s functional structure.

Organizational Skills

The ability of any organization to develop and maintain a workforce with skill levels sufficient to meet the demands of the workflow handled by the organization is paramount to its success. Matching workforce skill levels with work requirements is particularly important within a claims organization. It is especially significant within the liability function because of the range of skills required to handle claims of varying complexity and because of the difficulty in both recruiting new adjusters and retaining experienced adjusters.

For these reasons, it is important that management has the ability to both quantify the skill levels of their adjuster workforce, and to track those skill levels on an ongoing basis. This ensures the availability of an adequate pool of adjusters in the workforce, with skills matched to both current and predicted claim inventories.

A recent article in Best’s Review highlights the current adjuster shortage in the industry, and the need for maximizing the productivity of experienced adjusters:

Experienced claims people are an increasingly scarce resource. In fact, in early 2006 Deloitte Consulting predicted a shortage of 84,000 adjusters by 2014.
Prior to embarking upon huge hiring efforts, carriers should first ensure that they are maximizing the value of the claims adjusting talent they have by evaluating where, when and how they use their current claims resources.

Highly experienced resources must be reserved not only for the claims (or pieces of the claim, such as individual coverages) that truly require their expertise, but also for the knowledge transfer they can pass along to less-experienced claims professionals. (May 2011, p33)

Claims Inventory and the Staffing Model

In addition to understanding the dynamics of the claim servicing model under which the liability group functions as a whole, the organization must also analyze its claims inventory flow and assess its workforce needs under all possible variables within that flow. Is the claims inventory of the organization stable across time, is there seasonality?  Other factors that can influence the claim service model such as mix changes, given business model/strategy changes, or organizational acquisitions must also be assessed for their effects on the model.

The organization must have a clear understanding of the baseline norm of its claims inventory, and when there is likely to be a deviation from that norm (either high or low) as well as the probable degree of that deviation. With this understanding the organization can structure its most effective workforce size to deal with its average claim flow yet retain the flexibility to deal with anticipated peaks in claims flow.

To achieve maximum efficiency, the staffing model of the organization must be a reflection of both the claim servicing model developed by the organization, and the inventory flow of the claims serviced by that organization. To put it another way, the skills possessed by the adjuster staff must match as accurately as possible the demands made of that staff for the type and number of claims being handled by the organization. Furthermore, claims should be assigned to adjusters based upon all factors, not just one – the adjuster’s skills, inventory, and the claim servicing model of the organization. The claim servicing model should be the guide in determining staffing levels, including both the number of adjusters and their skill levels.

In a January / February 2009 article, the journal Risk Management noted that a staffing model which brought the right adjuster to the right claim at the right time would result in lower operating costs for the organization:

Risk managers should implement a new approach to claims management that drives down open claim inventory levels while driving up speed and efficiency. They should go back to the drawing board and implement a claims staffing model that will allow them to maintain this lower cost operating model. If the right expert is brought to the table, the risk manager will most likely find a lower cost claims administration program with far greater efficiencies than they had before. (p56)

Claim Workload Quantification

Workload Elements

All claims are not created equal. Regardless of their severity or complexity, they require that adjusters perform certain key operations. These operations will vary in the amount of time and effort required for their completion, depending upon the specific factors involved in each individual claim. The operations that are common to all claims can be thought of as basic claim workload elements. The specific factors that affect the time spent on completing the basic claim workload elements can be thought of as workload multipliers.

Basic workload elements common to all claims include such items as:

Contact with both claimant and insured throughout the claim lifecycle.

Data input on the specifics and details of the claim.

Investigation of the specific element of the claim.

Analysis of the claim and settlement offer or proposal.

Negotiation of final settlement of the claim.

Each of these basic claim workload elements (and any others which might be specific to the business process for any given organization) can be quantified by the time required to complete them. That quantification can be defined by the term work units. Obviously claims that are more complex or that have greater exposure potential will require that an adjuster devote more time to completing any or all of the basic workload elements required to handle the claim. As the complexity or exposure potential increases, the work units required to complete the basic workload elements for the claim increases as well.

Workload Multipliers

Workload multipliers are any elements of the claim that increase the work units required to complete the handling of the claim. These can be present at the beginning of a claim or they can occur at any point during the lifecycle of the claim. Following are examples of various categories of workload multipliers.

Claim age. Most routine claims require the most effort by adjusters (work units) during the 30 day period after initial filing. In effect, work effort is front loaded into the claim cycle. During that time adjusters conduct initial interviews, gather routine information, enter that information into claim management systems, make assessments, recommendations, etc. As the claim progresses through its lifecycle, it generally requires less effort by the adjuster.

Reported date lag on claims. This can play a significant factor as workload multipliers. Often a lag in claim unit reporting will require substantial extra effort by the adjuster to complete the routine tasks associated in handling the claim. For example, it may be harder to locate involved parties; interviews may require more time and effort because memories have faded, etc.

Exposure class changes. If the exposure potential of a claim increases significantly during its lifecycle, greater resources will need to be devoted to handling that claim. An increase in a claim’s exposure potential from its expected or predicted exposure level will act as a workload multiplier, increasing the work units needed to close that claim.

Attorney representation and/or litigation. If, during the lifecycle of a claim, a claimant should move from direct interaction or negotiation with the adjuster, to attorney represented negotiation, that change will act as a workload multiplier for that claim. Such a change will require that the adjuster devote more time to extra contact with the attorney, increase clerical requirements, and maximize negotiation efforts. Should the claim proceed to litigation, the workload multiplier effect will increase even further.

Indemnity payment effects. Claims that can be closed without indemnity payments to the claimant will obviously require fewer work units and the inventory effect of these claims in the overall mix is a needed factor to take into consideration.

Quantifying Workload

Once the claims organization is able to define both the basic and multiplier elements that comprise the workload of its core claim handling functions, it will be able to quantify those elements and assign work unit values for each of them. In addition, management will possess a tool that will give it the ability to classify claims by both estimated time and work unit requirements.

Timeframe. As noted above, most routine claims will fall into a frontloaded work unit structure. Assuming the claim is filed in a timely manner and that there are no substantial workload multiplier elements, the average routine claim will exhibit an initial surge in required work units (as the claim enters the processing system). As the claim progresses through its lifecycle the amount of work units devoted to it will steadily decrease, except for a brief spike as the claim reaches final settlement and closure.

Work unit quantification. The timeline required to settle a routine claim can serve as a useful benchmark for the organization. The time it takes for each basic workload element to be completed can be quantified and averaged across the range of skill levels of the organization’s adjuster workforce. Once this is done, the organization will have a metric that can be used in conjunction with the liability claim exposure model to give a numeric indication of the work units required (as defined by the organization) for the completion of each basic workload element. From that baseline measurement, the same process can be applied for each potential workload multiplier and its effect on the work units required across the varying skill levels of the adjuster pool.

By objectively quantifying the workload elements involved in claim handling, the organization will be able to triage their claims inventory by workload type and assign adjusters based on ability and inventory. Using the exposure model to triage claims into work unit categories at the beginning of the claim lifecycle will provide the organization the flexibility to triage claims in the most efficient manner, matching adjuster skill levels with claim requirements. In addition, effective claim triage will permit management to balance employee workloads during both routine operations and during periods of increased or decreased claim flow.

Monitoring

Effective management of any liability group requires the ability to efficiently and accurately model all of the elements involved in the claims handling process. In order to maximize adjuster productivity, measure strategy and effectiveness, and better understand trends as they evolve, management must monitor and adjust both the workload and workflow within the organization. Workload analysis using a liability claim exposure model can provide the organization the ability to analyze adjuster performance across the entire range of claims operations.

By applying a work unit metric to individual claims handling elements, management will be able to measure adjuster performance in handling not only individual claim functions, but also across claims of varying types and ages. This will in turn, provide management both greater flexibility and greater precision in claims assignment, and will result in the most efficient utilization of the adjuster workforce.

While the liability claim exposure model can play a key role in helping assess individual and organizational performance as well as determining optimal workload and workflow, it is not limited to these functions alone. By applying the data derived from workload quantification against normal claim flow fluctuation, management can develop a staffing model template that is both efficient and responsive to workflow changes.

Closing Thoughts

In the first installment in this series, we illustrated how the liability claim exposure model can provide a foundation that an organization can use for both claim management and workflow/workload distribution. In this article, we went on to describe how the liability claim exposure model can also be the basis for quantifying both organizational and individual workloads, and how that quantification can be used to triage the claims inventory and produce a staffing model designed to service that inventory.

In part 3 of our series, we will look at the dynamic interaction between the liability claim exposure model and the liability decision support system.  We will examine the concept of the liability decision support system as platform rather than product, and how that concept can ensure that adjusters are provided the right tools at the right time for optimal claim resolution.

Bishop, Mike, and Mahoney, Mike. “Filling a void: property/casualty insurers need to hire and train the next generation of adjusters.”  Best’s Review. Retrieved 9/1/2011 from Gale Power Search (Infotrac): Subscription or Library membership required.

Pelto, Corby. “Three ways to cut claim costs now.” Risk Management. Retrieved 9/4/2011 from: http://www.rmmag.com/Magazine/PrintTemplate.cfm?AID=3841

(CC) September 2011 Vatti-Manhattan Group
This article may be copied and distributed freely provided that you keep this copyright notice intact and is provided for free and without charge.  We have to the best of our knowledge abided by all copyrights, trademarks and quoted material.  Any comments, omissions, misuse concerns etc. regarding the use of trademarks and copyrights should be directed to info@vatti-manhattangroup.com.

In this series of articles we will examine how a liability decision support system that is structured around an exposure driven approach philosophy can result in more effective claim handling and increase the efficiency and effectiveness of the organization as a whole. The series consists of four articles, each of which will cover in depth one element of the claims management process and how that element can be enhanced through the application of an exposure driven approach philosophy.

The first article in the series will cover what we refer to as Triage and Investigation, and how the exposure model for a claim should be the driving factor in the management of that claim throughout its lifecycle. We will also examine how an exposure driven approach can affect organizational dynamics and staffing models.

The second article in the series will focus on Workload Quantification and how an understanding of the exposure model allows for the most efficient assignment of claims, (i.e., the right adjuster for the right claim), and how that exposure model also determines the amount of work required to resolve the claim.

The third article will look at the liability decision support system and how it needs to be Adaptive to the exposure prediction model on a continuing basis throughout the claim lifecycle. We will examine the concept of the liability decision support system being a platform rather than a product, and how, depending upon the exposure model, it can bring to bear the proper tools at the proper time in the claim cycle so that the claim can be resolved in the most optimal manner possible.

Finally we will look at Measurement and Peer Comparisons through the prism of the exposure driven approach. We’ll examine the need for user “tunabilty” of both exposure thresholds and the toolsets available to the liability decision support system. And we will close the series with a recap and overview of how a liability decision support system with advanced exposure modeling capabilities will benefit the claim organization at both the adjuster and organizational level.

Triage and Investigation – Day One Prediction, Claim Assignment, Claim Management, Organizational Dynamics, and Staffing Models

An accurate exposure prediction for each and every claim, throughout the lifecycle of that claim, (from first notice of loss through final settlement), is the cornerstone of any successful claims organization. Having a reliable exposure model allows the claims organization to triage claims and assign adjusters and resources to maximize productivity and efficiency, and minimize the cost of the claim handling process.

In medicine triage is the process of determining the priority of treatment by sorting casualties based upon the severity of their injuries. In claims the concept of triage can be thought of as assigning adjusters and resources to manage a claim based upon the exposure prediction for that claim. Obviously the sooner that a claims organization can make an accurate exposure prediction for a claim, the more efficiently and cost-effectively that claim can be resolved. A liability decision support system that has both an effective exposure prediction model and the ability to allocate tools that are appropriate for the types and exposure levels of the claims assigned to the adjuster is an invaluable asset for any claims organization.

Exposure Driven Claim Assignment

One of the key elements in developing the most effective and efficient claims organization is assigning the right person, with the right skill set, to the appropriate level claim. The importance of initial claim assignment based upon potential exposure was noted in an article in Claims Magazine by Rebecca C. Amoroso:

A claims talent crisis is looming with a projected shortage of more than 85,000 adjusters by 2012. With the number of expert adjusters dwindling, initial assignment of claims to the right resource is more important than ever. By better understanding a claim’s true exposure, explosive cases are quickly directed to the most qualified adjusters while low-exposure claims are channeled to less experienced resources or auto-adjudication. (August 2008, p1)

While the need for proper initial claim assignment may seem obvious, the complexity of accomplishing that seemingly simple task becomes readily apparent when you consider an organization with hundreds, or even thousands of adjusters, each at a different competency level, handling hundreds or thousands of new claims daily.

By utilizing the exposure prediction model of a trusted liability decision support system as the basis for assigning claims to adjusters, the claims organization has a built in mechanism for enforcing consistency of assignment that most efficiently utilizes the talents and skills of its adjusters, no matter what their level of expertise.

By having the ability to assign the right adjuster as early as possible in the claim handling process, the claims organization can also minimize adjuster reassignments during the life of the claim. Reassignments are costly to insurers on multiple levels – they increase the time period needed to settle a claim (making it more likely a claim will enter litigation), they involve duplication of effort (increasing labor costs), and they generally are a major source of consumer complaints involving insurer claim practices. Author Rod Travis, an executive vice president for a management consulting firm specializing in the insurance industry, noted in the Consultants Corner blog of Insurance Networking News, the role that information technology (of which the liability decision support system is a key element) can play in assigning adjusters:

IT can improve financial results by partnering with claims departments to deliver stronger claims automation and better analytics from claims data. This can help identify cases with potentially higher losses, enabling early and appropriate intervention. One simple example is flagging low-severity soft tissue injuries. Such claims warrant a more senior adjuster be assigned. (April 12, 2011, p1)

Exposure Driven Claim Management

Claims are dynamic, with their classification and complexity frequently changing during the life of the claim. These changes must be continuously monitored by a liability decision support system that dynamically reacts to each change with an updated and current exposure prediction model. That model in turn should be the basis for assigning adjusters to a claim based upon their strengths and skills as well as providing a framework and tool set that will best allow the assigned adjuster to most efficiently handle the claim.

Changing elements within a claim represent a dynamic environment in which a liability decision support system can play two important roles. First, the system should be able to assess the effects of any changes on the exposure prediction value for the claim. A 2005 Business Insurance article in which author Rupal Parekh interviewed claims technology expert Donald Light of Celent Communications, touched upon the importance of this liability decision support system function:

To help determine what is fair and accurate for both claimants and the insurance company, some online systems now provide suggested settlement amounts, using a rules engine, Mr. Light noted. For example, in the case of a bodily injury such as a broken leg, systems are available that can provide the adjuster with the average settlement amounts based upon geographic-specific medical costs. (May 1, 2005, p12)

Parekh quoted Mr. Light as saying of these systems, “For newer adjusters, especially, that takes away the likelihood of making a human error.” (May 1, 2005, p12)

The other important role of the liability decision support system is to assist the adjuster in the investigation of the claim by suggesting and making available investigative tools and resources that are tied to the initial or changing circumstances of the claim. The tools best suited for the investigation of a claim are almost wholly dependent on the exposure potential of the claim. If exposure potentials are initially high, or if they should change significantly during the life of the claim, a sophisticated liability decision support system should be able to suggest to the adjuster the most appropriate investigative resource.

For example a sudden and significant change in medical specials midway through the investigation of a claim, could trigger the liability decision support system to suggest to the adjuster that a specialized impact analysis be performed. Tools that predict the probability and severity of injuries based upon an impact study of the underlying accident, could be helpful in determining if the change in medical specials is warranted.

Staffing Models and Organizational Dynamics

A liability decision support system that is focused on exposure can also be the lead element in determining the most efficient staffing model for the claims organization. The data that the liability decision support system uses in creating exposure prediction models for individual claims can also be used on a macro level across the claims organization as a whole, to create an optimal staffing model by providing a basis for the quantification of different exposure events.

Developing a staffing model that matches adjuster skill sets and event quantification and that also provides a means of modeling actual claim workloads (and the exposure level across those workloads), is a formidable but absolutely essential task. On his insurance-related blog, The Claims SPOT, Marc Lanzkowsky addresses the issue of developing a staffing model. “Having a staffing model will allow you to objectively look at your operation and help determine if it’s a good time to hire more staff” (May 3, 2010, p1).  He lists 3 suggestions for creating a staffing model. First says Lanzkowsky, determine:

What kind of organization are you?….Understanding the strategic position of your claims organization is critical to understanding what kind of staffing model is relevant.

Decide on a metric to develop your model: The metric you choose will help to determine the model, but will be wholly based upon the types of claims organization you are….Maybe your claims settle quickly, as in some property matters, so the number of new claims a handler receives in a month is a more critical metric…

You now have the metric – test the staff and come up with the model: Once you settle on a metric, check your top performers against the new metric you have selected. How many files are they handling and still managing files within best practices? At what point does their ability to manage those files well breakdown? Take an average of the top performer’s metrics and you will have a staffing model to give you a benchmark.  (May 3, 2010, p1)

Using exposure models as the metric which Mr. Lanzkowsky refers to in his second point in the above quote can allow the claims organization to match the skill sets of its staff to the actual types and exposure levels of its claims inventory. Matching adjuster staff skill levels against the claims inventory exposure levels is an effective method of developing a staffing model that is made possible through the exposure driven approach philosophy.

The above methodology also gives the claims organization the operational flexibility to monitor changes in claim types, volumes, and exposure levels and adjust its staffing requirements in a timely manner to reflect those changes.

Conclusion

A liability decision support system that provides advanced exposure modeling capabilities will benefit the claims organization on multiple levels. At the adjuster level it will increase the efficiency and consistency of the claims handling process. At the organizational level it will assist in developing staffing models that accurately reflect the true operational needs of the organization.

Amoroso, Rebecca C. (August, 2008). Science Project – Tech Decisions. Claims Magazine Retrieved 6/2/2011 from: http://www.propertycasualty360.com/2008/08/01/science-project

Lanzkowsky, Marc. (May 3, 2010) “Does Hiring More Staff Improve Claims? How To Know When The Time Is Right.” The Claims SPOT – SPOT on Ops Retreived 6/2/2011 from: http://theclaimsspot.com/2010/05/03/does-hiring-more-staff-improve-claims-how-to-know-when-the-time-is-right/

Parekh, Rupal. (May 5, 2005, p12) “All Systems Go; Automating claims processing systems can speed up processing and boost the bottom line.” (Cover Focus: Information Technology). Business Insurance. Retrieved 6/1/2011 from: Expanded Academic ASAP (Infotrac): Subscription or Library membership required.

Travers, Rod. (April 12, 2011) “5 Steps for Insurers to Maximize Profitability. Insurance Networking News Claims Blog. Retrieved 6/6/2011 from: http://www.insurancenetworking.com/blogs/insurance_technology_IT_projects_profitability_growth-27652-1.html

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In this article we will show how an advanced liability decision support system can augment the inherent skills of the claim representative and allow that representative to make comparative negligence evaluations that are multidimensional, viewing the claim as a whole rather than as isolated elements. This multidimensional approach allows the claim representative to structure their evaluations of the key elements of the investigation to make comparative negligence assessments. In addition, these assessments reflect both the factual elements of the claim as well as the more intangible elements such as credibility, quality, and reliability of information sources, elements which can have major impacts on the outcome of negotiations or litigation.

Brief History of the Development of Comparative Negligence vs. Contributory Negligence

Over the past half century the doctrine of comparative negligence has gradually replaced that of contributory negligence in American tort law and has now become the standard in state automobile insurance regulations across the country. In a 2001 Harvard Law School – John M. Olin Center discussion paper, author Oren Bar-Gill noted:

The comparative negligence rule, and more generally the principle of comparative fault, is sweeping through the law of torts, and beyond. Through statutory intervention or judicial innovation, the traditional common law doctrine of contributory negligence has been gradually pushed aside. And the march of comparative fault continues. (Paper 346, 12/2001, p4)

The contributory negligence doctrine had been the governing standard for automobile insurance law for the first half of the twentieth century throughout most of the United States (it remains so in four states and the District of Columbia – see Appendix A). Under the contributory negligence system, third party lawsuits for injuries sustained in automobile accidents were not permitted if the plaintiff in that lawsuit was judged to be even partially at fault in the accident. It did not matter how minor the fault, if it existed at all, recovery of damages was prohibited.

Acceptance of the contributory negligence standard slowly began to decline as dissatisfaction with its relatively harsh results grew among the general public. Pressure from the motoring public and lobbying from trial attorneys resulted in a shift away from the contributory negligence standard. State legislatures across the country began to substitute the new standard of comparative negligence into their automobile insurance regulations. Comparative negligence in its simplest form is a legal doctrine that enables claimants to recover a portion of their damages even when they are judged to be partially at fault for an accident. Each driver’s degree of negligence is compared to that of the others and a claimant’s recovery is reduced by the percentage of his or her negligence.

Depending upon state statutes, comparative negligence takes one of three forms: pure comparative negligence, modified comparative negligence – 50% rule, or modified comparative negligence – 51% rule.

• Pure comparative negligence – Thirteen states use the pure comparative negligence rule which allows any person suffering damages to recover even if that person was 99% at fault. Any damages awarded however, are reduced, by the damaged party’s degree of fault. In a noted 1975 decision (Li v. Yellow Cab Company), the California Supreme Court, moved the state of California from a contributory negligence system to one of pure comparative negligence. In its decision the court mandated that:

Therefore, in all actions for negligence resulting in injury to person or property, the contributory negligence of the person injured in person or property shall not bar recovery, but the damages awarded shall be diminished in proportion to the amount of negligence attributable to the person recovering. (1975, p10)

• Modified comparative negligence – 50% rule. In the twelve states utilizing this variation of modified comparative negligence an injured third party can only recover damages if his or her fault does not reach 50%. If a driver is judged to be 50% or more responsible for an accident that driver is prohibited from recovering damages. As with pure comparative negligence, damage awards are apportioned according to the degree of responsibility.
• Modified comparative negligence – 51% rule. Twenty one states use the 51% rule. Under this version of modified comparative negligence an injured third party may recover damages if his or her responsibility is 50% or less. In other words damages can be awarded to a driver who was 50% responsible for the accident, but not if he or she was 51% or more responsible. As with pure comparative negligence, damage awards are apportioned according to the degree of responsibility.

Note – for a listing of the damage award system in use by each state, see appendix A at the end of this article.

A Structured Approach to Evaluating the Components of a Claim Investigation

All claim investigations are built around three key foundational pillars: investigative reports, physical evidence, and statements. Investigative reports can take the form of police reports, accident scene photos, skid mark analysis etc. Physical evidence is the evidence resulting from an accident – damage to vehicles and injuries to those involved. Statements include statements by the involved parties or witnesses, made to the police at the scene or to the adjuster during his or her investigation, as well as statements provided by expert witnesses brought in to analyze specific elements of the claim.

During the initial portion of a claim investigation the goal of the adjuster is to ascertain the facts of the accident and to determine the liability of each of the involved parties – the claimant (or claimants) and the insured. A key element in determining liability is assessing the comparative negligence for each party involved in the accident.

In assessing comparative negligence, the adjuster uses the investigative reports, physical evidence, and statements to evaluate their content as well as their reliability, quality, and credibility. This evaluation in essence determines if there was a breach of duty by any of the involved parties and if so, what part those breaches of duty played in the accident. This linkage is important given the fact that the concepts of duty owed and duty breached are tort concepts that would be used in a judicial context. Below is a summary of the main elements inherent in the concept of  negligence and breach of duty as outlined by author David J. Shestokas in his article, “The Law of  Negligence”:

Doctrine of Breach of Duty in Motor Vehicle Accidents

A claim investigation can establish that an insured either had no duty or did not breach a duty they did have, or it can establish that a claimant contributed to an accident by breaching a duty the claimant had.

In order to recover damages based on negligence a claimant must prove that all of the elements that comprise negligence are present. These elements are:

• Existence of a duty by the insured
• Breach of that duty by the insured
• Actual harm or damages caused to the claimant
• The breach of duty by the insured was the proximate cause of the actual harm or damages suffered by the claimant. (Mar 25, 2009, p1)

The operation of a motor vehicle on a public roadway imposes duties upon the operator. There are duties that are common among all states and jurisdictions and there are other duties that are state specific. Common duties include:

• Duty to look out – you must pay attention and be aware while driving.
• Duty to operate safely
• Duty to Avoid – you must do all that is reasonable to avoid a collision or contact with another vehicle or pedestrian.
• Duty to obey traffic laws
• Duties created under the “reasonable man” theory. – You must operate your vehicle as would a “reasonable man” in similar circumstances.

The breach of duty concept is fundamental in assessing degrees of comparative negligence for both claimants and insureds. Anyone who is determined to have a breach of duty in an accident is negligent. In any accident, one or both parties can be found to have committed a breach of duty resulting in negligence which contributed to the accident. A sophisticated liability decision support system can assist the adjuster in determining comparative negligence by allowing the adjuster to rate the reliability, quality, and credibility of each the three investigative pillars: the investigative reports, physical evidence, and statements. These ratings, based on the expertise and experience of the adjuster, are used by the liability decision support system in determining the probable shared responsibility of the claimant for the accident.

Given the fact that this assessment of duty owed duty breached is critical to a comparative negligence determination, a system that provides investigation survey templates that are populated with the factors that are relevant in determining the comparative negligence of both the claimant and the insured is paramount. The factors within the templates will assist in determining which driver breached which duty, and the degree those breaches played in the comparative negligence of the claimant and the insured. Because those factors vary greatly with the specific type of accident, the liability decision support system must be adaptive and flexible enough to provide the adjuster with only those query sets that are relevant to the specifics of the particular accident. In addition, a truly advanced liability decision support system will allow an adjuster to use their experience in rating the reliability, quality, and credibility of the reports, physical evidence, and statements themselves. These ratings will be used in generating both comparative negligence assessments and in more advanced systems, an overall strength of case evaluation which can assist the adjuster in deciding the best strategy to adopt in settling the claim. This will insure consistency across claims and within the organization, and provide defensibility should the analytical process itself be challenged.

The results of the analysis provided by the liability decision support system should produce a liability and comparative negligence assessment that provides a useful guideline that the adjuster can use for negotiations and settlement of the claim. We have found that providing the adjuster a visual scaled representation of the probability of the claimant’s shared responsibility for the accident, is an effective method of alerting the adjuster that there is a comparative negligence element that should be pursued.

Summary

When considering the processes involved in the investigation and evaluation of claims some of the fundamentals that an organization should keep in mind include:

• The liability decision support system should allow the adjuster to focus on the key elements of the claim, and produce a liability and comparative negligence assessment that provides a guideline for negotiations and settlement of the claim.
• The adjuster must have the flexibility in their investigation to pursue whatever avenues of information are relevant to the claim. The liability decision support system must not become an impediment to that flexibility by forcing the adjuster to adhere to a pre-determined, one-size-fits-all investigative template.
• The liability decision support system must provide a support structure that allows the adjuster to apply their investigative skills in the most productive and efficient manner.
• In assessing liability and comparative negligence the adjuster must be able to document objective and consistent standards that are applied across all claims. The liability decision support system should provide a mechanism that is defensible and demonstrably unbiased.
• Ideally, the liability decision support system will also provide an objective assessment of the strength of case in the event the claim was to proceed to litigation.
• The liability decision support system should provide a mechanism that allows the adjuster to enter both the factual and subjective elements of the claim for evaluation. The evaluation returned should provide both a strength of case rating, and negotiation points that can be used by the adjuster in determining whether a case should be defended or settled.

The liability decision support system should augment and support the adjuster’s investigation and evaluation of the claim. It should not be thought of as a sort of “electronic adjuster” that is able to replace the judgment, skill, and analytical expertise of the adjuster. Rather, it should serve to aid the adjuster’s evaluation of the claim by structuring the process of the evaluation itself. Providing a structural framework upon which the adjuster can build an evaluation gives consistency to the evaluation process across claims and throughout the organization.

Bar-Gill, Oren. (12/2001, p4). “Does Uncertainty Call for Comparative Negligence?” (Paper 346). Harvard Law School John M. Olin Center for Law, Economics and Business Discussion Paper Series. Retrieved 2/10/2011 from: http://lsr.nellco.org/cgi/viewcontent.cgi?article=1134&context=harvard_olin

Case Reference:

Li v. Yellow Cab Co. (1975 p10) 13 C3d 804 [L.A. 30277 Cal Sup Ct Mar., 31, 1975] Opinion – Sullivan, J. – III [6]. Retrieved 3/11/2011 from: http://online.ceb.com/calcases/C3/13C3d804.htm

Shestokas, David J. (Mar 25, 2009, p1). The Law of Negligence: Duty, Breach of Duty, Injury and Causation. Suite 101.com. Retrieved 3/8/10 from: http://www.suite101.com/content/the-law-of-negligence-a105023

Appendix A – Damage Award Systems Used by the Various States

Contributory Negligence States: Alabama, Maryland, North Carolina, Virginia, (Washington D.C.)

Pure Comparative Negligence States: Alaska, Arizona, California, Florida, Kentucky, Louisiana, Mississippi, Missouri, New Mexico, New York, Rhode Island, South Dakota, Washington

Modified Comparative Negligence States – 50% Rule: Arkansas, Colorado, Georgia, Idaho, Kansas, Maine, Nebraska, North Dakota, Oklahoma, Tennessee, Utah, West Virginia

Modified Comparative Negligence States – 51% Rule: Connecticut, Delaware, Hawaii, Illinois, Indiana, Iowa, Massachusetts, Michigan, Minnesota, Montana, Nevada, New Hampshire, New Jersey, Ohio, Oregon, Pennsylvania, South Carolina, Texas, Vermont, Wisconsin, Wyoming

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In this article we will examine the application, rules and limitations of UCR with respect to third party liability, first party liability, personal injury protection (PIP) and MedPay applications. Our goal is to look at the operational practicality and to understand the role of this concept within the claims organization.

Definitions of Payment Methodologies.

Insurers pay medical bills in one of two ways, either through fee schedules, or through a repricing concept that has come to be known as usual, customary and reasonable, or simply as UCR.

Fee schedules can either be voluntary as with HMOs or PPOs, or governmentally mandated. Medical service providers who participate in Medicare-Medicaid for example receive a fixed fee for the services they provide that is set by the federal government. In the same manner, providers treating patients covered by State worker’s compensation and disability programs, or patients covered under a State No-Fault, PIP (Personal Injury Protection) mandate, also have their reimbursements limited to amounts authorized by State-mandated fee schedules. In addition when a medical service provider joins a PPO (preferred provider organization) or HMO (health maintenance organization) that provider agrees to accept the fee schedule set by the PPO or HMO.

UCR payments to medical service providers are used by insurers as a method of controlling and standardizing medical costs. In their simplest form, UCR payment schedules are determined from statistical analysis of prevailing charges among all providers within a given geographical area for a given service or procedure. An article by Michael Hood and Lane Wood in the Dallas Bar Association’s publication Headnotes, describes UCR pricing this way:

Few states define the terms “usual, customary and reasonable,” and even fewer have regulations on the methodology used to determine UCR charges. Typically, a UCR charge is defined as the general prevailing cost of that service by a majority of health providers of the same discipline within the same geographic area.

To determine UCR charges, insurers use health care billing information collected from privately owned databases….(Headnotes, March 2009, p8)

UCR History and Litigation

The development of the UCR concept was pioneered by the health insurance industry.

One of the initial steps in the evolution of physician payment in the United States was the development of usual, customary, and reasonable (UCR) fee schedules. The Blue Shield plans, which then provided the largest portion of physician insurance and operated with the support of local medical societies, collected information on what each physician charged for each service in a local area during the previous year. When a physician submitted a bill, it was checked to determine whether it was above his or her median charge for the same service the previous year (usual), above the 75^th percentile of charges by all doctors in the area (customary), or justifiably higher because of a patient’s complicating secondary illness or another acceptable reason (reasonable). When Medicare was implemented in 1966, it adopted the Blue Shield UCR method of paying physicians. (Getzen, 2010, p.136)

After Medicare adopted the UCR pricing system other payers followed suit and UCR became the standard method used by the insurance industry in repricing medical bills. Because of increasing costs however, Medicare in the early 1990’s began a move away from the UCR based fee system and began reimbursing physicians using what is called a resource-based relative value scale (RBRVS). RBRVS was developed by a Harvard research group and basically relates the value of medical procedures to each other (based on time, skills required and other factors), assigns a dollar conversion factor along with a geographic factor to derive a formula which computes payments for specific services and procedures. (For more on the development and methodologies of the Medicare fee schedule system, see “The Medicare Fee Schedules – History, Development and Role” section of this article.)

While some insurance companies followed Medicare’s lead most continue to use a UCR – based reimbursement system. UCR has never been popular with medical providers or patients. Providers say that the methodology used to calculate UCR schedules is skewed in favor of payers and does not provide fair compensation for their services. Patients complain that when they go out of network, reimbursement rates are lower than in-network rates, and that they are left to pay the difference between what the insurer pays and the actual charges.

Those arguments got a big boost in 2009 when then NY Attorney General Andrew Cuomo announced a $50 million settlement with the nation’s second largest health insurer, UnitedHealthcare, regarding their ownership and operation of the Ingenix UCR database. Two days later Cuomo announced a $20 million settlement with Aetna, the nation’s third largest insurer, over their use of the Ingenix database. This was followed almost immediately by UnitedHealthcare agreeing to settle a class action lawsuit for $350 million, which had been brought by the American Medical Association, health plan members, health care providers and state medical societies.

The settlement of the lawsuit involving Ingenix, the United Healthcare unit that provides data used to set “usual and customary” charges for medical services, is at least on the surface a big step toward reducing uncertainty on the part of healthcare providers and patients about how charges are set, and who will be paying them….

The investigation by New York State Attorney General Andrew Cuomo revealed that the Ingenix database intentionally skewed usual and customary rates downward through faulty data collection, poor pooling procedures, and the lack of audits…

The investigation also revealed that having a health insurer determine the usual and customary rate, a large portion of which the insurer then reimburses, creates an incentive for the insurer to manipulate the rate downward…

Under the terms of the settlement, United Healthcare will fund the establishment of a new, independent database run by a nonprofit organization, which will develop data collection protocols and other methodologies used in connection with the database.

The nonprofit will also develop a Web site where consumers around the country can find out in advance how much they may be reimbursed for common out-of-network medical services in their area… (CBS Moneywatch, March 2009, p1)

A company called FAIR Health Inc. is the nonprofit organization that will develop the new UCR databases which will replace the UnitedHealthcare – Ingenix databases. FAIR Health was established in October 2009 and will serve as an independent, objective, and transparent source of healthcare reimbursement data for consumers, insurers, healthcare providers, researchers and policymakers. On the FAIR Health website the organization defines its mission as:

FAIR Health was established in response to New York State Attorney General Andrew Cuomo’s investigation into the insurance industry’s methods for determining reimbursement rates for patients who seek care from out-of-network providers. The investigation determined that such reimbursement policies were conflict-laden, potentially flawed, and opaque to patients seeking cost information… 

In implementing its mission, FAIR Health is developing two types of data products. The first, the FAIR Health Consumer Cost Lookup, will be targeted to consumers and consists of a free, user-friendly website whereby patients can estimate the out-of-pocket expenses they will incur if they seek out-of-network care. FAIR Health’s second set of products will be targeted to payers, and will consist of licensed benchmarking tools that can be used to assist in their establishment of out-of-network reimbursement rates.   

The foundation for all of FAIR Health’s products will be its national database of millions of de-identified healthcare claims. These claims are submitted directly to FAIR Health by insurers and other healthcare payers. In recognition of the groundbreaking contribution that FAIR Health’s claims database can make to research on the nation’s healthcare system, we intend to offer our data at modest cost to qualified researchers and policymakers studying health costs and care delivery…

For all of our data products, FAIR Health’s paramount goal is transparency and integrity. Stated simply, our aim is for our data to become a gold standard in reimbursement data. (FAIR Health Mission Statement as presented on the FAIR Health website – Jan, 2011)

As part of the agreement with New York, Ingenix has stopped marketing its UCR database products to new customers but will continue to issue normally schedule updates to its existing customers. Once FAIR Heath begins marketing its replacement UCR database modules, Ingenix will end its involvement with UCR database products entirely.

For the insurance industry the Ingenix settlement means that insurers may have to re-evaluate how they calculate UCR rates. Some insurers may simply switch to one of the competing UCR database products such as the Wasserman Physician Fee Reference, PFR, or they may choose to use the FAIR Health database when it becomes available. However some experts think that the Ingenix episode could lead to more fundamental changes. Doreen Corwin, director of network affairs for StrataCare Inc. notes that, “This may well cause payers and review companies to consider other options for defining reasonableness in payments based not on charge data but rather some percentage of a widely accepted payment methodology such as Medicare.” CBS Moneywatch – (March, 2009 p3)

UCR Use Within Mandated Coverage Systems (No Fault, Workers Comp)

State mandated insurance programs such as worker’s compensation and No-Fault Auto Insurance personal injury protection (PIP), will often employ medical reimbursement fee schedules that are based on the UCR concept. The fee schedules used by these programs are developed from various UCR databases – commercial, governmental and hybrids of both. States will mandate how fee schedules are developed, and from what sources they may be derived, within the applicable law governing the specific program to which they are to be applied. Just as with commercial insurers, states use UCR fee schedules to control medical costs and insure that providers adhere to treatment guidelines and billing practices consistent with the mandates of the program in which they are participating.

The Medicare Fee Schedules – History, Development and Role

Since its establishment in 1965 Medicare has become the largest single healthcare payer in the United States covering some 45.2 million people according to the 2009 Medicare Trustees Report. A 2009 Congressional Budget Office report noted that:

Federal spending for Medicare made up 21 percent of total health care expenditures in 2007, and federal and state spending for Medicaid, 16 percent. A variety of other public programs accounted for 10 percent of total spending. Such programs included those run by state and local governments’ health departments, the Department of Veterans Affairs, and the Department of Defense; workers’ compensation programs; and the Children’s Health Insurance Program.  (CBO – The Long Term Budget Outlook, 2009)

When Medicare was first instituted it paid providers based upon their usual and customary charges as long as those charges were reasonable. It basically adopted the Blue Shield developed UCR fee schedules which were at the time, the standard method of payment for service providers. Medicare also allowed providers to bill Medicare enrollees directly and for any difference between their charges and Medicare reimbursement rates, (a practice known as balance billing.) In testimony before a House subcommittee in 2004, the head of the CBO noted the effects of this method of reimbursement:

The charge-based reimbursement system gave physicians the incentive to raise their charges from year to year to boost their revenues, and those increases led to a rate of growth in spending that averaged 13 percent annually from 1967 through 1974.

As concerns grew about the program’s rising costs, policymakers focused on restraining fees. In 1972, they mandated that the annual update to physicians’ fees be limited to the increase in the MEI, a provision that was implemented in 1975. (Douglas Holtz-Eakin, CBO Director, Testimony before the House subcommittee on Health, May 5, 2004, p2)

The Medicare Economic Index, MEI, adopted in 1975 was an attempt to limit the growth in fees for physician’s services. The MEI is essentially a measure of the prices for the resources needed to provide physician services. It was designed to provide a basis upon which to estimate the total costs required for an average physician to operate a medical practice.

The effort to control Medicare costs by tying provider fees to the MEI soon proved insufficient and Congress responded through the 1980’s with legislative fee freezes and specified increases:

Tying increases in fees to growth in the MEI was not sufficient to keep total payments from rising, however, and lawmakers took further steps to limit spending from 1984 through 1991. The Congress froze fees from 1984 through 1986; from 1987 through 1991, it raised them by amounts specified in legislation. The effect of those actions was that spending grew at an average annual rate of 15 percent from 1975 to 1991. (Douglas Holtz-Eakin, CBO Director, Testimony before the House subcommittee on Health, May 5, 2004, p3)

In 1992 an effort was made to control Medicare expenditures through the redistribution of payments based upon physician services provided. Analysts believed that the prior payment systems over compensated procedural services such as surgeries, at the expense of what they termed cognitive services such as office visits and consultations. The result was the implementation of the current RBRVS, Resource Based Relative Value Scale, fee schedule reimbursement system.

RBRVS is a listing of physician services with Relative Value Units, RVUs, assigned for each service. (Services are defined by their CPT codes.) RVU’s encompass three elements, physician work, practice expenses, and malpractice insurance. Components within each of these elements are weighted to reflect different costs, levels of expertise, etc. For example the RVU element for practice expenses varies with where the service is provided. If a physician provides a service within a hospital facility the practice expense value is less than if that physician provides that service within their own office. This accounts for office expenses, supplies, etc. Similar valuation occurs for the physician work element – for example a simple office visit has a higher value for a new patient than an established patient which reflects the additional work needed for assessing the patient through consultation, medical history etc. RVU’s also are adjusted for geographic variations in each of the three component elements using what are called geographic practice cost indexes, GPCIs.

The dollar value of an RVU is called the conversion factor and it is updated annually by the Centers for Medicare and Medicaid Services (CMS), through its Medical Payment Advisory Commission, MedPAC. The conversion factor is multiplied by the RVU to calculate the payment for a given service. The following representative formula was provided by the American Medical Association (note the approved conversion factor of $33.9764 for calendar year 2011) – (AMA website – The Medicare Physician Payment Schedule):

Work RVU x Work (GPCI) 

+ Practice Expense (PE) RVU x PE GPCI

+ Malpractice (PLI) RVU x PLI GPCI

  = Total RVU

x CY 2011 Conversion Factor of $33.9764

  = Medicare Payment

Medicare, because of its sheer size has become a defacto baseline in the calculation of UCR rates for payers nationwide. In an article in the Spring 2002 issue of the Journal of Health Care Finance, author Paul L Grimaldi notes that, “Medicare’s conversion factor has served as the floor for other insurers physician fee schedules. The most notable exception is Medicaid, in which case Medicare’s conversion factor often serves as the ceiling.”

The fact that Medicare has become (as Grimaldi said) a “floor for other insurers physician fee schedules” means that two standards have emerged for calculating UCR rates. That fact, in combination with the payouts that many insurers were forced to make because of the Ingenix case, could conceivably cause more insurers to consider switching their UCR model to one based upon Medicare. Such a move could protect insurers against lawsuits similar to the one brought against Ingenix. It is not difficult to envision insurers using Medicare rates as a cap on UCR payments, for example capping UCR payment rates at 150% of the Medicare rate. By combining an insurer’s historical payment data with the Medicare physician fee schedule (such as is done by the unique methodology created by VMG), insurers can have both a consistent and defensible methodology that they can use in establishing their UCR rates.

Concept of Settlement and Medical Specials. – Third Party Liability Claim Process

It is true that cost containment of medical specials is vital to an insurer’s bottom line and that the proper use of a valid and defensible UCR based fee schedule is a key element of that cost containment strategy. However insurers must always keep in mind that reduction in medical special payments achieved through the application of UCR based fee schedules might not achieve the equivalent in overall settlement savings as are achieved in the medical specials portion of the settlement. In other words a reduction of 20% in medical specials might not result in a reduction of 20% in the total settlement.

Insurers need to be wary of the forest and trees scenario, whereby they focus solely on stringent UCR fee schedule application as a means of achieving savings yet ignore the possibility of even greater savings offered by sophisticated liability decision support systems and their ability to drill down into the details of the medical specials themselves. It is within these details where the real potential for savings lies. Duplicate bills, duplicate lines within bills, CPT and ICD9 code mismatches, billed treatments for CPT codes unrelated to the accident caused injury, etc. All of these are areas of potential savings that would remain unexploited if the focus was solely limited to UCR fee schedules.

Understanding Medical Specials – The Cost Containment Pyramid

Smart insurers will employ liability decision support systems that provide both sophisticated UCR fee schedule application and more importantly give adjusters the ability to drill into medical treatment patterns to assess the appropriateness and effectiveness of treatments for the diagnosed injuries.

In looking at medical cost containment strategies for medical specials a good analogy is that of a pyramid divided into thirds. The upper third of the pyramid can be thought of as representing the savings achieved by focusing on stringent UCR fee schedule application, while the middle and lower thirds of the pyramid can be thought of as representing the savings achievable by applying a systematic in-depth review to the entirety of each medical special. In thinking of this pyramid model it is readily apparent that the bulk of potential savings regarding medical specials lies in the comprehensive review of all elements of medical specials rather than a narrow focus on the single element of UCR application.

The key element of a comprehensive medical cost containment strategy is a liability decision support system that integrates all elements of the claim (including medical specials) into an integrated whole that provides adjusters instant and thorough access to all claims documentation materials. In the realm of medical specials this type of liability decision support system allows the adjuster to assess the mechanism of injury by accessing the accident report, compare that information to the injury diagnosis through ICD9 coding, and assess appropriateness of treatments provided by comparing the treatment CPT codes to a comprehensive ICD9-CPT database. The liability decision support system should have the capability of automatically flagging injury-treatment mismatches. It should also have the ability to catch duplicate bills and duplicate line items within bills. These areas represent substantial potential savings for insurers.

Once each line item of each medical special has been checked for duplicates and cleared as appropriate, the decision support system should allow the adjuster to assess the charges for each line item by comparing each charge against a standardized UCR database which is accepted as authoritative within both the payer and the provider communities. As we have seen earlier in this article, using a UCR database whose statistical accuracy is in question can cost substantially more than it saves. A UCR database consisting of both an insurer’s historical payment data and standardized government reimbursement guidelines such as the annual physician fee schedule, (PFS) published by the Centers for Medicaid and Medicare Services (CMS) can provide an insurer both a consistent and defensible baseline for reducing excessive service charges. (The Historical / Medicare UCR is a unique methodology created and supported by VMG).

Provider Negotiations vs. Claimant Negotiations

In examining the application of UCR to medical special charge reductions, insurers need to be aware of the pitfalls of using a one-size-fits all approach, particularly when it comes to negotiating with claimants versus providers. Negotiating tactics and strategy that is appropriate in the case of providers can easily become counterproductive if applied to claimants.

For example if an accident and injury occurs in a no-fault (PIP) state, then it is perfectly appropriate for the insurer to use the payment provisions and fee schedules that are mandated by law in that state. And there certainly is no problem with reducing payments to providers who have charged in excess of the specified fee schedule.

Likewise when negotiating with a provider directly there is little or no downside in rigorously applying a company’s UCR fee schedule.

However, when negotiating with a claimant directly, a dogmatic approach to UCR based reductions may save a few dollars – but at a much greater cost to the insurer’s reputation and perception. Most claimants who are injured and have paid out of pocket medical expenses simply want those expenses reimbursed in a timely manner without needing to argue about (to them) arcane concepts such as UCR reimbursement. Of course we are not talking about fraudulent claims here – such claims should be vigorously pursued by any insurer. But for the average claimant, dealing with an insurer that he or she perceives is trying to nickel and dime them over medical treatment payments, is one sure way to turn that claimant into a plaintiff. Such a result is to no one’s benefit. When negotiating with a claimant directly, particularly one with no ulterior motive, the insurer will be far better off showing flexibility and maintaining the good will of the claimant.

Pragmatic Understanding of a Good Medical Cost Containment Program and Tool

For an insurer, understanding where the bulk of savings can be found in medical specials is key to unlocking those savings. Focusing your efforts on fundamentals that lead to a consistent approach to treatment patterns, duplicate elimination, etc., as discussed in this article, rather than relying on mechanical, non-defensible UCR strategies, is a sound and pragmatic liability and medical cost containment strategy.

In order for a medical cost containment program to provide maximum savings it must be comprehensive. It must take into account and exploit all areas of potential savings within medical specials. This requires a fully integrated liability decision support system – one that provides real time access to all of the documentation that comprises the claim and does so in an easy to use, intuitive way.

Of equal importance is that the liability decision support system provides consistency of analysis across all varieties of claims. By establishing a consistent methodology in analyzing claims an insurer can go a long way in deflecting claims of bad faith. Databases used by the liability decision support system must be supportable and defensible, that is they must be accepted as authoritative by both payers and providers.

By combining a “big picture” view of medical cost containment with the right tools provided by a comprehensive liability decision support system, an insurer can have a consistent approach to medical cost containment.

Bibliography

AMA – The Medicare Physician Payment Schedule, p1. Retrieved 01/19/2011 from: http://www.ama-assn.org/ama/pub/physician-resources/solutions-managing-your-practice/coding-billing-insurance/medicare/the-medicare-physician-payment-schedule.shtml

CBS Moneywatch – (March, 2009), p1). Retrieved 12/22/2010 from: http://findarticles.com/p/articles/mi_m0BJK/is_3_20/ai_n31444750/?tag=content;col1

Congressional Budget Office. (June 2009, Ch2 p1 (Overview of the US Healthcare System)). The Long Term Budget Outlook: http://www.cbo.gov/ftpdocs/102xx/doc10297/Chapter2.5.1.shtml

FAIR Health Mission Statement – From the Fair Health website. Retrieved 1/11/2011 from: http://fairhealthus.org/about-us/mission

Getzen, Thomas E. (2010). Health Economics and Financing (4^th. Edition). Retrieved Dec. 20, 2010, from: http://books.google.com/books?id=nw9EtbMnRk8C&pg=PA136&lpg=PA136&dq=%22development+of+usual+customary+and+reasonable%22&source=bl&ots=Px54TKKMZP&sig=UYYonwiaCOTrFq7GISZ6fmVxaCE&hl=en&ei=DmoPTd6qIMWBlAfrtrm4DA&sa=X&oi=book_result&ct=result&resnum=1&ved=0CBgQ6AEwAA#v=onepage&q=%22development%20of%20usual%20customary%20and%20reasonable%22&f=false

Grimaldi Paul L.. “Medicare fees for physician services are resource-based.” Journal of Health Care Finance. 2002. Retrieved January 20, 2011 from accessmylibrary: http://www.accessmylibrary.com/article-1G1-110311953/medicare-fees-physician-services.html

Holtz-Eakin, Douglas – Director CBO. (May 5, 2004 p2) Testimony before the House subcommittee on Health: http://www.cbo.gov/doc.cfm?index=5416&type=0

Hood, M., & Wood, L. (March 2009, p8). Insurance Transparency: Usual, Customary & Reasonable Costs. Headnotes, (Vol. 33, No. 3.) Dallas Bar Association. Retrieved 12/17/2010 from: http://www.dallasbar.com/documents/HN_03012009.pdf

Medicare Trustees Report (12 May 2009, p2). http://www.cms.gov/ReportsTrustFunds/downloads/tr2009.pdf

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The Property Casualty Insurers Association of America, PCI, indicates that in eighty percent of the states that allow third-party bad faith claims, auto bodily injury liability cost trends exceeded the national average (Albright, 2009). Bad faith claims can also adversely impact an insurer’s reputation and its ability to draw new customers and retain existing ones.

Bad faith claims put an insurer’s entire claims liability structure on trial. In this article we will examine how a liability decision support system that enables best practices to be consistently used as well as fully documenting each element of the liability claim handling process,  can specifically provide essential protection for an insurer against bad faith claims.

Background

For insurers the liability claim handling process provides numerous opportunities for insureds and claimants to bring bad faith actions. There are any number of ways that an insurer can be held to have committed bad faith. An article by Robert J. Prahl, Director of Education for the American Association of Insurance Services summarizes the areas of claim handling that are potential sources of bad faith:

• Investigation – The investigation of a claim (both first and third party claims) must be complete and thorough concerning both the liability question and the damages aspect. (2010, p2)
• Settlement Negotiations – Another possible source of bad faith is the conduct of settlement negotiations, particularly with respect to third party liability claims. (2010, p2)
• Inadequate Defense – Occasionally insurers may be uncertain whether coverage applies until the outcome of the trial. If an insurer simply refuses to defend a claim involving a question of coverage, it may subject itself to a bad faith claim, including an award for punitive damages. (2010, p3)
• Unfair Claim Practices Acts – Unfair claim practices acts, in effect in all states, address many aspects of claim handling…Although the provisions of such acts generally do not permit a claimant to sue an insurer for the violation of the act, some states permit a claimant to bring a separate tort action for bad faith directly against an insurer. (2010, p3)
• Claim File Reporting – Claim adjusters can unwittingly make written or electronic remarks in a paper or electronic claim file which may come back to haunt them in the event the file is later subpoenaed in a bad file suit. (2010, p3)

Within each of the broad categories listed by Mr. Prahl, there are multiple elements, each of which could lead to a bad faith claim. For example, regarding the liability investigation element, Mr. Prahl notes that an incomplete liability claim file could in and of itself be demonstrable proof of an inadequate investigation providing an opportunity for bad faith claims both by the insured and the injured third party.

According to the American Insurance Association there are currently 6 states that have statutory third party bad faith causes of action – Florida, Kentucky, Louisiana, Massachusetts, Montana and New Mexico. In states without a statutory right to third party bad faith causes of action, third party claimants can frequently sue insurers via assignment of rights of the insured. Author and attorney William T. Barker notes:

Absent rights flowing from a statute, third-party claimants ordinarily have few rights of their own regarding insurer refusal to settle and must rely primarily on assignments of the rights of the insureds they have sued…When a third-party claimant has a statutory right to have the insurer attempt settlement when liability has become reasonably clear, the most obvious consequence is that the claimant can assert a breach of this duty even if the insured was never exposed to any excess or non-covered liability. (2010, p.3)

Bad Faith Cases – setting the stage

Clegg v. Butler and Utica Mutual Ins. Co. – Massachusetts

Summary:

Clegg v Butler established that a third party claimant can sue an insurer for bad faith in refusing to settle after the insured’s liability has become clear. The case also established that insurers can be sued for treble damages for knowing or willful violation of the Massachusetts good faith practices.

The trial judge found for the plaintiff for $250,000 and imposed treble damages plus attorney fees and costs finding that – “Plaintiff is entitled to treble damages for Utica’s knowing and willful failure to effectuate a prompt and equitable settlement of his claim.”

(Clegg v Butler – Middlesex Superior Court, Civil Action No 93-0640, Conclusions, 18)

Key Points of the Case

Plaintiff James Clegg was badly injured in an automobile accident that occurred solely as a result of the negligence of Jeffrey Butler, Utica Mutual’s insured. Clegg sued Butler and brought a bad faith suit against Utica Mutual for refusing to settle.

The trial judge found, and the Supreme Court affirmed, that Utica’s adjuster and his supervisor determined that the insured was completely liable and at “no time did Utica consider the case to be anything but a so-called 100% liability case against its insured.” (Clegg v Butler – Middlesex Superior Court, Civil Action No 93-0640, Findings of Fact, 6)

Both the trial judge and the Supreme Court found that Utica then proceeded to engage in a series of actions that were sufficient to constitute a finding of bad faith in refusing to settle a claim where liability was clear and established. Among those actions:

• Repeatedly requesting medical documentation that had already been furnished.
• Failure to respond to an initial settlement demand and subsequent failure to make a settlement offer to a second settlement demand.
• Violating its own policies which prohibited interviewing claimants represented by counsel.
• Failure to perform more than an initial medical exam, because as the trial judge found, Utica believed “the results of an IME would be more likely to harm Utica’s interests than to help them.” (Clegg v Butler – Middlesex Superior Court, Civil Action No 93-0640, Findings of Fact, 14)
• Making an offer of settlement a series of structured settlements well under the policy limits, which the trial judge found, “unrealistic, unreasonable, and unjustified.”

Clegg v Butler clearly illustrated a flawed liability claim management process as well as a failure to adhere to a rigorous best practices regimen. Had best practices been established and been implemented and reinforced in a liability decision support system, many of the specific elements constituting the bad faith claim would not have been allowed to occur. For example, a properly configured liability decision support system would have alerted the adjuster to the existence of required medical documentation and prevented multiple requests for such documentation. See “The Role of Liability Decision Support Systems in Mitigating Bad Faith Claims” section below for further information.

Hovet v. Allstate – New Mexico

Summary:

In Hovet v Allstate the New Mexico Supreme Court combined two different accident cases. In both cases plaintiffs alleged that Allstate violated unfair and deceptive claims practices by failing to offer an adequate settlement amount even though both insureds admitted fault.

The New Mexico Supreme Court used Hovet to extend the right of third party claimants to bring private causes of action directly against a liability insurer for violations of the unfair claims practices sections of the New Mexico Insurance Code.   (NM Supreme Court Decision – Hovet v. Allstate Insurance Company Docket No. 27,969, Opinion Number: 2004-NMSC-010, (April 8, 2004))

Key Points of the Case

At trial a jury found that plaintiff Hovet incurred in excess of $11,000.00 in direct medical bills as a result of an accident with a vehicle driven by Steven Lujan and owned by Arthur Lujan, Allstate’s insured. The Lujans admitted liability. Allstate’s highest settlement offer was $7,200 – substantially less than the plaintiff’s medical bills alone. The jury awarded $62,050.00 in damages.

 (The second case was similar, with the injured parties combined medical bills totaling $5410.00 and Allstate offering $3000.00. At trial a jury found for the plaintiffs in the combined amount of $8700.00)

 In both cases, after appeals, the New Mexico Supreme Court affirmed the third party right to sue an insurer.

 Hovet’s suit against Allstate alleged unfair and deceptive trade practices. These practices were outlined in an Amicus brief filed by the New Mexico Trial Lawyers Association, which asserted:   (Hovet v Lujan and Allstate – New Mexico Court of Appeals Decision, April 7, 2003. Discussion, 10)

• Allstate’s treatment of Hovet was a single instance of a nationwide practice adopted by Allstate of a “Settle for ‘X’ or Litigate policy applicable to cases where the liability of Allstate’s insured is reasonably clear at the outset.
• Allstate makes a “one time ‘take it or leave it’ offer” generated by a computer program that evaluates claims “without any real regard for the individual characteristics of any particular claim or claimant.”
• The settlement offers generated by Allstate’s computer program are “approximately 25-40% of the historical values” for similar claims and frequently do not even equal the amount of claimant’s medical bills.”

Hovet v Allstate offers a perfect example of the need for a comprehensive liability decision support system that combines and reinforces liability claim management best practices, with an objectively fair and defensible settlement range analysis engine. In determining settlement ranges for general damages, a liability decision support system must apply fair and consistent rules for liability claims of a similar type, while still allowing an adjuster the flexibility to account for the individual variations found in a particular liability claim. Such a system will allow an insurer to rebut claims of bad faith whether through “low-balling” settlement offers, or analyzing liability claims using a “cookie-cutter” approach.

The Role of Liability Decision Support Systems in Mitigating Bad Faith Claims

What does a liability decision support system have to do with these litigation cases?  In our opinion, everything.

For insurers the key to avoiding, or failing that, defending against bad faith actions is consistent adherence to a set of carefully developed, fully documented, and rigorously enforced liability claim management best practices. Those best practices must be applied consistently to every liability claim handled by the organization. The liability decision support system used by adjusters in evaluating liability claims must not only provide settlement range suggestions which are justifiable and fair, it must also reinforce the best practices of the organization throughout the entirety of the liability claims management process.

Examples of Liability Best Practices and Their Application to Mitigating Bad Faith Claims

• General damage calculations should use the same metrics for all liability claims of similar type and take into account specifics for individual liability claims such as injury severity, long term implications, prior injuries, contributory negligence, etc. The liability decision support system must evaluate each claim using clearly understood and defined rules which have been incorporated into the liability claim management best practices of the organization. Those rules (reflecting the best practices) should be based on the historic evaluation of cases of similar characteristics previously settled by the company. The rules must be unambiguous and fully documentable.
• Adjusters must fully document all encounters made during the life of a liability claim. Each contact with claimants, attorneys, witnesses etc., needs to be fully documented so as to avoid charges of bad faith negotiations or failure to fully investigate, etc. The liability decision support system plays a key role prompting and aiding adjusters in fully documenting all encounters with parties to the case. It can be configured to remind adjusters of the importance of not incorporating unnecessary commentary into their documentation.
• Adjusters must respond to demand letters. Failure to do so can be evidence of failure to negotiate in good faith, or ignoring an opportunity to settle – both frequent elements of bad faith claims. The liability decision support system should prompt and ensure that adjusters respond in a timely and appropriate manner to demand letters.
• Complete and full documentation of the case including medical reports, police and witness statements, photos, investigation results, etc., must be available to, and used by, adjusters as they make decisions throughout the course of the liability claim. One of the most frequent elements of bad faith claims is a claim of failure to fully investigate. A complete liability claim file can rebut a charge of failure to fully investigate. The liability decision support system is key to this element. It plays two roles, prompting the adjuster if there is missing or incomplete information, and providing the adjuster instant real-time access to all documentation regarding the claim.

Exposure Management – Litigation Management and the Liability Decision Support System

The best way to mitigate a bad faith claim is not to have one arise in the first place. The liability decision support system can play a key role in preventing bad faith claims before they start. It can do that in two ways. In an earlier article in this series, “Information is Key to Successful Negotiations,” we quoted author Mikel Benton in an article in Claims in which he quotes attorney Allen Church as saying:

Adjusters need to say to themselves, “I’m going to do everything I can, professionally, to prevent this claimant – each and every claimant – from acquiring the title of plaintiff, hiring an attorney. (Benton, 1999 p.90)

The first way that the liability decision support system can prevent a claimant from becoming a plaintiff (and possibly filing a bad faith claim) is for the adjuster to use that system to satisfy the claimant that he or she is being offered fair compensation for their damages or injuries. The ability of an adjuster to prove to a claimant that they are using fair and objective criteria to analyze and settle the liability claim is based almost entirely upon the best practices built into the liability decision support system. If those criteria can be rationally explained to a claimant during the negotiation process the chances of settling the liability claim before it goes to litigation are substantially improved. Even if a claimant does eventually retain an attorney, the same elements hold true assuming that the claimant’s attorney is using a common sense approach to the negotiations. In either case the liability decision support system itself can play a decisive role in preventing a claim of bad faith.

The second way that a liability decision support system can prevent a bad faith claim is by providing the adjuster with an accurate estimate of the true strength of case for both the insurer and the claimant. The most advanced liability decision support systems will take into account all aspects of the liability claim, even including participating attorney records and the dynamics of the venue in which the case would be heard. Such systems can provide the adjuster an accurate indication of the overall strength of the case and whether or not a decision to settle prior to trial is in the best interest of the insurer. In such cases settling would prevent later claims of bad faith and the potential for large punitive judgments.

Medical Specials Documentation and the Liability Decision Support System

Medical specials represent an area where sophisticated liability decision support systems, combined with an adjuster’s experience and expertise, can convince a court or jury that a settlement offer was reasonable in light of the totality of the circumstances of the liability claim. In order to do so, complete and accurate documentation of the adjuster’s decision process is vital.

The liability decision support system should provide the factual foundation upon which the adjuster decides the amount of a settlement offer.  State of the art decision support systems allow adjusters to assess diagnostic and treatment related medical specials using both the insurer’s historical data and standardized government reimbursement guidelines such as the annual physician fee schedule (PFS) published by the Centers for Medicare and Medicaid Services (CMS). In addition, adjusters can use the decision support system to assess the appropriateness and effectiveness of treatments provided to a claimant using medically authoritative ICD9 diagnostic and CPT treatment databases.

The liability decision support system should also provide a fact-based, objective, documentable, and defensible settlement value range. Adjusters can then assess the unique elements of a liability claim such as contributory negligence, comparative fault, pre-existing conditions, etc, – clearly documenting each element and its effect upon the adjuster’s valuation of the liability claim.

Having a relatively transparent liability workflow process that an adjuster can point to and explain during a litigation proceeding can play a significant part in overcoming a claim of bad faith.

The Importance of Providing Consistency Across Liability Claims

A well-defined and managed liability claim workflow that conforms to and supports liability strategy and best practices will ensure consistency across liability cases. In combination with a liability decision support system designed to reinforce those best practices, an insurer will be able to minimize the variations in settlement values among claims of a similar nature. Being able to prove that an insurer is applying the same objective standards across all liability claims, and that those standards are fair, reasonable, and in line with industry standards, is an important element in defending against, or even preventing bad faith claims.

Because bad faith claims represent serious threats to insurers on many levels it is imperative for insurers to act preemptively to avoid being placed in bad faith situations. The best way to do this is to ensure consistent, provably fair, liability claim standards which are adhered to by all claims adjusters and which are reinforced by well defined organizational best practices that are incorporated into the liability decision support systems used by the organization.

The Vatti-Manhattan Group team would like to acknowledge and thank the American Insurance Association for their valuable assistance in researching elements of this article.

Albright, Brian (March 12, 2009): p3: New legislation challenges “bad faith” claims practices. Auto Body Repair News (ABRN). Retrieved from: http://abrn.search-autoparts.com/abrn/article/articleDetail.jsp?id=586762

Barker, William T (June 14, 2010): Legislative Approaches to Bad Faith Litigation – New Appleman Insurance Bad Faith – Chapter 10. LexisNexis Communities – Insurance Law Community Blog. Retrieved 11/28/2010 from: http://www.lexisnexis.com/Community/insurancelaw/blogs/insurancebytespoweredbynewappleman/
archive/2010/06/14/legislative-approaches-to-bad-faith-litigation-new-appleman-insurance-bad-faith-litigation-chapter-10.aspx

Benton, Mikel (June 1999): p90: Adjuster’s Repertoire Should Include Negotiation. Claims

Prahl, Robert J. (Undated): Bad Faith and Excess Liability – Insurer Conduct on Trial. American Association of Insurance Services (AAIS). Retrieved 11/29/2010 from: http://www.aaisonline.com/articles/badfaith.html

Case References

Clegg v Butler

Middlesex Superior Court, Civil Action No 93-0640 (http://www.bwglaw.com/lawyer-attorney-1369135.html)

Appeal of Trial Court Decision to Supreme Judicial Court of Massachusetts, Middlesex – Clegg v. Butler, 07216 (Mass. March 12, 1997) (http://caselaw.findlaw.com/ma-supreme-judicial-court/1418069.html)

Hovet v Allstate

New Mexico Court of Appeals – 66 P.3d 980 (2003): 133 N.M. 611: 2003-NMCA-061 Hovet v Lujan and Allstate http://scholar.google.com/scholar_case?case=9086812093971735021&q=related:5iZ8SIuH9d4J:scholar.google.com/
&hl=en&as_sdt=40000002&as_vis=1

NM Supreme Court Decision – Hovet v. Allstate Insurance Company Docket No. 27,969, Opinion Number: 2004-NMSC-010, (April 8, 2004). http://www.supremecourt.nm.org/pastopinion/VIEW/04sc-010.html

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This article may be copied and distributed freely provided that you keep this copyright notice intact and is provided for free and without charge.  We have to the best of our knowledge abided by all copyrights, trademarks and quoted material.  Any comments, omissions, misuse concerns etc. regarding the use of trademarks and copyrights should be directed to
info@vatti-manhattangroup.com.

To realize improved health care quality, efficiency and patient safety, the criteria for meaningful use will be staged in three steps over the course of the next five years. Stage 1 sets the baseline for electronic data capture and information sharing. Stage 2 (est. 2013) and Stage 3 (est. 2015) will continue to expand on this baseline and be developed through future rule making.

Insurers know that as goes Medicare so goes the rest of the nation’s health care system. Insurers that prepare to take advantage of the new electronic billing and record mandates will have a distinct competitive advantage over those that do not.

EHR Opportunities and Potential

In the area of claims handling the move to electronic health records will provide a vast opportunity for insurers to capitalize on the correlation between medical specials and fully digitized medical records that include reports, chart notes, images, examination and treatment documentation, and even prescription records. EHRs have the potential to provide the claim handler with unprecedented abilities to reconcile the medical specials with injury causation, providing that they have the tools and data platform to take advantage of these digital representations of what traditionally was a paper / image driven process.

The greatest impact of the EHR transformation will be in the traditional medical bill transcription workflow. The delays and errors inherent in most carrier’s current system of manual transcription will be a thing of the past. This will speed up the entire claim handling process.

To fully realize the potential savings that EHR’s can provide, insurers will need to ensure that their medical management and cost containment systems are fully compliant with EHR data and security standards, and that those systems provide their claims handlers the flexibility to fully utilize the EHR data.

Since EHR data standards are still evolving, insurers planning for their future implementation will need to make sure that the tools and systems they are considering are standard-aware and ready for implementation when final standards are determined. Of course any systems and tools being considered must also support current image based standards since the transition to an EHR system will occur in phases over the course of many years. It is critical during the planning stage, to question both internal IT and perspective vendors as to how they are prepared to leverage these standards as they transition from the current system to a fully implemented EHR system.

EHR Standards and Interoperability Requirements

As noted above, EHR standards are evolving. One key factor for a universal EHR system is the interoperability of the system between healthcare providers, payers, government agencies, regulators, vendors and other stakeholders. Health Level Seven International (HL7) is a non-profit, ANSI-accredited international standards developing organization that is playing a key role in developing the standards that will be used to meet the “meaningful use” criteria outlined by the CMS. An HL7 press release describes the process of creating these standards: (Health Level Seven Background Brief)

The enactment of the American Recovery and Reinvestment Act in the U.S., which has earmarked $19 billion in federal funds to support the spread of health IT, has provided new opportunities for HL7. One of the criteria for showing “meaningful use” of an EHR-a requirement for receiving government financial incentives-is to exchange electronic data with other healthcare providers. The HL7 standards already in place, and those that HL7 is developing or bringing online in the U.S., will be instrumental in achieving the interoperability that will enable providers to exchange data easily across healthcare communities. In fact, the Office of the National Coordinator for Health Information Technology in the U.S. Department of Health and Human Services selected HL7 Version 2 and the HL7 Clinical Document Architecture (CDA) / Continuity the Continuity of Care Document (CCD) in its initial set of standards, implementation specifications and certification criteria for EHR technology.

The HL7 Clinical Document Architecture (CDA) is an important step to achieving interoperability. The CDA is an ISO approved standard that provides an exchange model for clinical documents (such as discharge summaries and progress notes) and brings the healthcare industry closer to the realization of an electronic medical record. There are large-scale CDA implementations in North and South America, Europe and Asia Pacific. The Continuity of Care Document (CCD) is a CDA implementation of the continuity of care record (CCR), created by the American Society for Testing and Materials (ASTM). Disparate information systems can employ the CCD to exchange clinical summaries that contain key data about individual patients, such as diagnoses, medications, and allergies.

Stage 1 of the Meaningful Use program initially contained two requirements that included billing and administrative transactions, – first that a user be able to determine through the EHR system a patient’s insurance eligibility, and second that a user was able “to electronically submit claims to public or private payers in accordance with the standard and implementation specifications specified in 45 CFR 170.205(d)(3).” (Federal Register Vol. 75, No. 144 p.44612). Due to time constraints and technical difficulties these requirements were subsequently removed from Stage 1. However the Department of Health and Human Services has made it clear that the requirements will be reinstated in Stage 2 and beyond:

“Therefore, we intend to include for adoption, administrative transaction standards and certification criteria to support meaningful use Stage 2 rulemaking, and expect health care providers and Complete EHR and EHR Module developers to take this into consideration leading up to 2013.” (Federal Register Vol 75, No 144 p 44613).

EHR standards and requirements are set forth in the Code of Federal Regulations – “Health Information Technology Standards, Implementation Specifications, And Certification Criteria And Certification Programs For Health Information Technology.” (45 CFR Part 170) They specify criteria for ambulatory (170.304) and in-patient (170.306) settings. For an ambulatory setting the requirements include:

• Computerized provider order entry – medications, laboratory, radiology/imaging
• Electronic prescribing
• Patient demographics recording
• Electronic patient reminder generation
• Clinical decision support including real time notifications of contraindications
• Electronic copy of health information – generation and retrieval
• Problems – ICD-9 Vol. 1 and 2 and ICD-10 code sets
• Laboratory Test results
• Medications
• Timely access
• Clinical Summaries
• Exchange clinical information and patient summary records with other providers and organizations

As noted above, administrative transaction data (CPT and billing data) is not yet included in the requirements – however with the implementation of Stage 2 and beyond, this information will be included as part of the EHR data structure. To effectively use EHR information insurance medical cost containment and liability management systems must be able to extract the relevant claim data from the enormous amount of data that will be part of EHR records. In effect medical management and cost containment systems must be able to isolate the trees from the forest.

EHRs and the Claims Handling Process

Once fully implemented a standardized EHR system will increase the efficiency of the entire claim handling process, including document review, bill transcription, and the review of injuries and the medical treatments provided. The mandated move to ICD-10 diagnosis coding and ICD-10 PCS (inpatient procedure coding), scheduled to occur on Oct. 1, 2013, along with the Jan. 1, 2012 move to the Version 5010 electronic claims standards set, will begin to put in place the EHR foundation that will eventually become standard industry wide. (CMS website – “ICD-10 Basics for Payers,” Sept. 2010)

Currently an enormous amount of time is spent by claim handlers in reviewing the medical documentation associated with a claim. Most of that documentation comes in the form of scanned images of handwritten forms, notes, charts, admission and treatment records, etc. Essentially the claim handler is looking at electronic representations of dozens, or in some cases, hundreds of paper documents. For the claim handler these documents can present substantial difficulties:

• Handwriting is often illegible, forcing the claim handler to spend large amounts of time in simply trying to decipher what the clinician was saying. In addition because these records encompass the totality of the claim, from initial presentation through all subsequent treatments, many individuals will have made notes often using shorthand and non standard terminology. This forces the claim handler to spend even more time reconciling these notes with bills and treatment codes.
• Documentation is often incomplete, forcing time consuming delays while claim handlers attempt to locate the missing records and update the claim file.

EHRs will do away with these problems and allow claim handlers to use their time in the most efficient way possible. Fully digitized EHRs will give the claim representative access to both the entire medical record of the claim (including notes, charts, histories, and images), as well as the claimant’s medical history. Rather than spending valuable hours interpreting and deciphering electronic versions of printed documents, EHRs will allow claims handlers to focus their attention on analyzing, investigating and clearing claims. This will enable claims handlers to close claims faster and increase the volume of claims handled by claims departments.

Within the claim handling process, medical bill transcription has always been costly in terms of both time and money. It is a labor intensive process that many insurers choose to outsource. Bills are subject to the same problems of illegibility as are other medical documents and, in addition, they can be miscoded by the provider either inadvertently or with the intent of up coding or unbundling. Additionally the bill transcription process itself can add many days to the overall claim settlement process.

Because EHR systems need to be interoperable with each other (so that patient records are fully and immediately accessible to any provider, using any system, anywhere in the country), they will impose a data structure that will eventually do away with the need for insurance companies to maintain either an in-house or outsourced medical bill transcription capacity. Since all records related to treatment will have been digitized for use in the EHR system either immediately or shortly after creation, insurance companies will be able to use those digitized records directly without the intermediate step of transcription. EHR structured data will also make the detection of up coding, miscoding or unbundling easier to detect. (Note – an interesting article covering this topic – “The Importance of Transcription In The EHR Age”, by Ken Congdon, can be found at the Healthcare Technology Online website.)

For the claim handler and the insurer, no single element of the claim review process is as important as reviewing the medical records for causality and the appropriateness of treatments provided. Ensuring that providers are treating and billing within accepted medical guidelines and only for those injuries covered under the claim, is key to containing medical related costs.

A major consideration for insurers in paying claim related medicals is the existence of undisclosed or disguised pre-existing conditions or injuries that are not related to the claim. For the claim handler, documentation is usually limited to the current claim. Unless a provider makes note of a pre-existing condition or injury, or the claimant mentions it to the adjuster, such pre-existing conditions may go unreported and result in payments for treatments unrelated to the claim.

A standardized EHR system, once in place, will greatly reduce the costs of insurers by minimizing inappropriate payments associated with pre-existing conditions. Because an EHR will contain the complete medical history of a patient/claimant, claim handlers will no longer have to play medical detective in attempting to link treatments to previous undisclosed conditions or injuries. Insurers are likely to see reduced costs in both man-hours and savings in inappropriate payments.

The Analytical Potential of EHRs for Insurers

We have outlined some of the potential benefits in medical management and cost containment that a standardized and universal EHR system can provide. However, given the wealth of detail inherent in EHRs there is the potential for an insurer to utilize that data (stripped of identification elements) in statistical models that can be used in analyzing medical trends in claims data.

Given where we are in the progression of electronic data – EHRs add an effective dimension to the data capabilities of carriers. Not only can the marriage between EHR data and auto physical data form the determination of causality, it can also serve as an exposure determinate and predictor.

More to come on those interesting topics in the future.

45 CFR Part 170
Retrieved from http://ecfr.gpoaccess.gov/cgi/t/text/text-idx?c=ecfr;sid=5c04367d65136717775673a2c1e334de;rgn=div5;view=text;node=45%3A1.0.1.4.75;idno=45;cc=ecfr#45:1.0.1.4.75.3.27.3

CMS website – “ICD-10 Basics for Payers,” Sept. 2010
Retrieved from http://www.cms.gov/ICD10/Downloads/ICD10PayerFactSheetFINAL.pdf

CMS website – Meaningful Use – Retrieved from
https://www.cms.gov/EHRIncentivePrograms/35_Meaningful_Use.asp#TopOfPage

Federal Register Vol. 75, No. 144 p.44612 Retrieved from
http://edocket.access.gpo.gov/2010/pdf/2010-17210.pdf

Health Level Seven Background Brief Retrieved from
http://www.hl7.org/newsroom/HL7backgrounderbrief.cfm

Congdon, Ken. (9/28/2009). The Importance Of Transcription In The EHR Age. Healthcare
Technology Online: http://www.healthcaretechnologyonline.com/article.mvc/The-Importance-Of-Transcription-In-The-EHR-Ag-0001

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This article may be copied and distributed freely provided that you keep this copyright notice intact and is provided for free and without charge.  We have to the best of our knowledge abided by all copyrights, trademarks and quoted material.  Any comments, omissions, misuse concerns etc. regarding the use of trademarks and copyrights should be directed to
info@vatti-manhattangroup.com.

Information technology supports the key psychological aspects of negotiation. In this article we will explore the key elements of the negotiation process and how they directly correlate to information technology and more importantly the key elements of data to make the negotiation process consistent within an organization.

Psychology of Negotiations

In negotiating settlements with claimants or their representatives, claims adjusters must balance a series of competing needs. They need to satisfy the claimant that he or she is receiving fair compensation for the damages or injuries they have suffered while understanding that the claimant’s view of their required compensation may not be in line with reasonable expectations. They also must balance the need to close cases and at the same time prevent as many claimants as possible from becoming plaintiffs. Author Mikel Benton makes note of this in an article in Claims where he quotes attorney Allen Church as saying:

Adjusters need to say to themselves, “I’m going to do everything I can, professionally, to prevent this claimant – each and every claimant – from acquiring the title of plaintiff, hiring an attorney.” Including good negotiation techniques early…can prevent claims from going to court. (Benton, 1999)

In order to balance these competing needs the claim adjuster must pursue their negotiations from a psychological point of view of achieving a “right end,” or in other words, a settlement that is a fair and reasonable conclusion for all parties involved. A key element in achieving a “right end” negotiating philosophy for a claim adjuster is their confidence in the data they use in constructing their negotiation strategy. That data must be of sufficient detail to provide a true and unambiguous view of the key elements of the claim. It must also be immediately accessible to the claim adjuster so that the adjuster can reference it in real-time ongoing conversations and negotiations. By having access to detailed and trusted data the claim adjuster has the foundation to pursue the negotiation process from a “right end” perspective.

Negotiation Process

For the claim adjuster, whether negotiating directly with a claimant or with a claimant’s attorney the “principled negotiations” strategy is by far the most productive. The principled negotiation theory was pioneered by the Program for Negotiation at the Harvard Law School, and first published in the book “Getting to Yes: Negotiating Agreement Without Giving In” by Roger Fisher and William Ury. (http://www.pon.harvard.edu/tag/principled-negotiation/). Principled negotiation theory is based on four basic criteria – these are defined by USLegal:

Principled negotiation is a negotiation strategy that emphasizes interests, not problems. The four fundamental principles of principled negotiation include: 1) separate the people from the problem; 2) focus on interests, not positions; 3) invent options for mutual gain; and 4) insist on objective criteria.

The principled negotiation concept is ideally suited to situations where information technology is a key element of the negotiation process. Because accurate data and information are inherently objective they allow claim adjusters (and those they are negotiating with) to approach negotiations with a set of shared expectations based on the true facts of the claim. This allows both parties to the negotiations to enter into those negotiations with realistic expectations as to their outcome.

Most plaintiffs’ attorneys will generally recognize this common sense approach to negotiations. In the Association of Trial Lawyers of America publication Trial, attorney Michael Heatherly notes this common sense approach to negotiations:

Maintain credibility. As in the settlement demand, when negotiating, I try to avoid overstatement, acknowledge true weaknesses of the case, and emphasize my best-documented points. Exaggerating or making claims that can’t be backed up objectively will immediately undermine credibility.

Ask adjusters to prove their claims, too. While I try to put forward the best possible documentation of my claims when I begin negotiation, I expect the other side to do the same. For example, if an adjuster claims that the plaintiff was partly at fault because of speeding, I say, “I’ll take that into consideration if you send me something I can show my client to prove that’s true.” I usually find out immediately whether the adjuster is bluffing or stating a legitimate defense. (Heatherly, 1995)

Enhancing Negotiations with Key Data Elements

In the paragraph above attorney Michael Heatherly noted that he would “Ask adjusters to prove their claims, too” during negotiations. The ability to prove your negotiating points, whether to an attorney or the claimant themselves, is the key factor that will enable a claim adjuster to achieve a successful outcome in the negotiation process. Information technology and the information it provides is the key to that ability.

• The more advanced decision support negotiation / liability systems will give adjusters the ability to drill into medical treatment patterns and determine whether treatments were medically justified for the injury being claimed, were provided in the most cost-effective manner, and whether or not they were effective in treating the condition.

• Medical bill charges. Sophisticated decision support negotiation / liability systems allow adjusters to instantly assess whether treatment charges are reasonable by comparing those charges to a detailed UCR database containing charge information for providers providing similar services within the same geographic locations (Historical / Medicare UCR is a unique methodology created and supported by VMG).

• Settlement range suggestions based on comparisons of like cases against a comprehensive database of extended historical claim and settlement data. Settlement ranges are calculated using formulas that take into account various factors such as injury severity, length and type of treatment received, prior existing injuries, aggravating circumstances, contributory negligence and the geographic area.

• Real-time access to claims documentation materials including police reports, witness statements, accident scene photos, medical reports, etc. Having instant access to data of this type allows the adjuster to discuss highly specific elements of the claim in detail with the claimant or their representative in real time. The adjuster can look at photos or medical reports directly while negotiating and use the information to counter or refute specific elements of the claim.

• Strength of Case, as described and referenced in this article, references the most advanced decision support negotiation / liability systems that provide the adjuster an indication of the overall strength of the case should the case proceed into litigation. This is a sophisticated data model that looks at the claim in a holistic manner that includes not only claim specific elements (injuries, loss of wages, pain and suffering etc.), but other elements which might be of major influence in a trial environment. Such items are assessed with the understanding that a jury will evaluate the case with respect to all the participants involved, (insured, claimant and attorneys). These are important elements for an adjuster to consider because they are also routinely considered by the claimant’s council as noted by attorney Heatherly in Trial:

A client’s character is perennially cited as one of the most critical factors at trial. Communicating character to an insurance adjuster in a demand package is difficult. However, photographs and accounts of a client’s praiseworthy personal and social activities are of great help, giving the opposition a better first impression than simply identifying the client as “a 24-year-old male carpenter.”

On the other hand, in assessing the value of a claim, don’t overlook a client’s downside. The defense will surely bring up any negatives if the case goes to trial.

You should also assess the defendant’s presentability. If he or she was intoxicated, driving recklessly, or is simply a poor witness, the insurance company will be less enthusiastic about challenging your claims regarding liability and the mechanics of the accident. (Heatherly, 1995)

As can be seen from Heatherly’s observations of these data points, they contribute to the overall ability to negotiate a claim successfully. When combined into a trusted whole they provide the adjuster the ability to negotiate from a position of confidence and strength.

Close

Insured’s (and claimants) judge insurance companies through only one prism – how they handle claims. Ensuring that claims are handled fairly and consistently is a key element to a company’s reputation and survival.

For claim adjusters trustworthy, accurate data, formulated consistently across the organization is a pre-requisite to ensuring their confidence during the negotiation process. When adjusters have faith and trust in the data that they are using, they can negotiate settlements confidently – to the right end. This will in turn enhance the organization’s reputation among its employees, its competitors, its customers and the public at large.

Benton, Mikel (June 1999): p90: Adjuster’s Repertoire Should Include Negotiation. Claims

Heatherly, Michael J. (August 1995): p58(5): Negotiating From Strength: Sure Steps Toward a
Settlement. Trial – published by the Association of Trial Lawyers of America

USLegal – definition of Principled Negotiation. Retrieved from:
http://definitions.uslegal.com/p/principled-negotiation

(CC) October 2010 Vatti-Manhattan Group
This article may be copied and distributed freely provided that you keep this copyright notice intact and is provided for free and without charge. We have to the best of our knowledge abided by all copyrights, trademarks and quoted material. Any comments, omissions, misuse concerns etc. regarding the use of trademarks and copyrights should be directed to info@vatti-manhattangroup.com.

Documents, records and the data they contain are the lifeblood of any insurer. A report by the research and consulting firm Celent LLC, entitled, “Document Management for Insurers: Overview and Solution Spectrum,” notes that, “Document management is a key issue for insurers. Every step of the insurance product life cycle from product definition through distribution, underwriting, service, and claims relies on the creation and handling of internal and external documents.” (Celent, 2006)

For insurers, whether they are considering a move to a full-scale ECM solution, or a more limited upgrade to their existing document management capabilities, a number of factors need to be considered before they commit to an expensive and potentially disruptive process. An article in the journal Insurance & Technology, entitled “Achieving True Enterprise Content Management Proceed With Caution,” by Wendy Toth, said this of the challenges presented by such a move:

Any insurance company trying to achieve the elusive goal of true enterprise content management (ECM) faces a rising tide of structured, semi-structured and unstructured data, as well as a wave of technology types and vendors offering ECM solutions. For an industry still trying to break free from siloed business processes and under increasing regulatory scrutiny, the challenge of integrating disparate data and systems is formidable. (Toth, 2005)

In the same article, John Mancini, president of the Association for Information and Image Management, suggested the following:

When companies look at the complexity and scale of content management, they need to find the first level – the areas where they are most exposed – and begin by really knowing their own business processes, while keeping one eye looking toward the bigger picture. (Toth, 2005)

Most insurers today find themselves using a patchwork of different legacy document management systems chosen by individual business units and geared to the needs of those business units, rather than the enterprise as a whole. For these insurers, switching wholesale to an enterprise-wide ECM system may simply not be an option. Instead, pulling content from within silos may be a much more viable strategy. An article in Insurance & Technology by Anthony O’Donnell, quotes the director of strategy for IBM’s Information Management division Andy Warzecha, as saying:

The reality today is that insurance organizations still do have multiple [content] repositories and that will continue – there will not be just one place to go to get all of your unstructured information . . . It is much more likely that we will see technologies that allow you to federate across the different repositories you may have, regardless of what they are. (O’Donnell, 2007)

A major consideration for insurers in the current hyper-regulatory environment is that whatever document management / ECM solution they choose, that solution needs to meet current and future regulatory and compliance standards. Document retention, integrity, and accessibility during legal and regulatory discovery processes, has become a major concern for all insurers, regardless of size. In addition, HIPAA, Sarbanes-Oxley, Gramm-Leach, as well as state-specific requirements, have added further regulatory requirements to the document management function. In an article in Claims Magazine, author Gary Blake, notes that:

The enactment of the Federal Rules of Civil Procedure (FRCP) on Dec. 1, 2006 has been the catalyst for renewed emphasis on document retention. . . . The simple fact is this: once legal counsel declares that a document is subject to discovery, the document must be preserved from being altered or destroyed. No state will accept excuses in the place of your competent execution of policies and implementation of appropriate technology. Lest we forget, courts can sanction those that fail to produce well-preserved documents. (Blake, 2000)

Further, Gary Corcoran, systems manager at Central Insurance observes:

Certainly the Sarbanes-Oxley Act, GLBA, and changes in the FRCP alerted companies to develop better internal controls to guard privacy and prevent and detect fraud . . . GLBA requires all financial institutions to design, implement, and maintain safeguards to protect customer information. (Blake, 2008)

The ECM / Document Management ideal is that all content of whatever type, structured and unstructured, is made available to anyone in the enterprise authorized to access it, whenever they need it. The ideal also holds that each document, image, and record, throughout its lifecycle, has a complete audit trail and is readily accessible to auditors, regulators and litigators on an as needed and timely basis.

However, in the insurance industry, real world circumstances are such that the ideal remains elusive and a target rather than an achievement. In reality, there is no one-size-fits-all solution. When considering modernizing their ECM / Document Management systems, each company needs to balance its desire for the ideal, with what can be practically accomplished in the most cost-effective, least disruptive manner.

References:

Blake, Gary. (5/29/2008). Covering Your Bases. Claims Magazine

Retrieved from http://www.claimsmag.com/Issues/2008/6/Pages/Covering-Your-Bases.aspx?k=Covering+Your+Bases

Celent. (8/30/2006). Document Management for Insurers: Overview and Solution Spectrum.

Celent LLC. Retrieved from http://reports.celent.com/PressReleases/20060830/DocMgmt.htm

O’Donnell, Anthony. (6/1/2007). Insurers Advance on the ECM Ideal. Insurance & Technology

Retrieved from http://www.insurancetech.com/showArticle.jhtml?articleID=199900177

Toth, Wendy. (2/21/2005). Achieving True Enterprise Content Management Proceed With

Caution. Insurance & Technology

Retrieved from http://www. insurancetech.com/showArticle.jhtml?articleID=60402365

(CC) August 2010 Vatti-Manhattan Group
This article may be copied and distributed freely provided that you keep this copyright notice intact and is provided for free and without charge. We have to the best of our knowledge abided by all copyrights, trademarks and quoted material. Any comments, omissions, misuse concerns etc. regarding the use of trademarks and copyrights should be directed to info@vatti-manhattangroup.com.