Typical caseloads for workers' comp claims adjusters run approximately 150 files per person. Some companies have models that are lower, some have models that are higher, but these days about 150 files per person is the standard.
Of course, each case in the futurity, or inventory, requires a different level of activity. A claim involving a simple soft tissue sprain with a return to work date within 30 days of the injury does not require the same level of attention as a case with surgical intervention and open-ended disability. The key issue has always been to be able to early identify the injuries that will most likely result in more costs, and apply the claims organization's finite resources to them in the beginning stages of the case.
Prior to the advent of computers on every desk, the claims adjuster and claims supervisor were expected to use their experience (which was often considerable) to early identify cases that had the most potential to deteriorate. Of course, this was also in an age when a standard adjuster's caseload was 60 cases. Now with caseloads two or three times larger, and often less industry experience, the caseworker's mission remains the same. But analytics and predictive modeling is available to help ease the burden of selecting the claims that require more upfront attention.
Catastrophic claims are not the issue in terms of this exercise. Those cases are immediately identifiable as requiring more resources because of the extreme nature of the injury. The claims that companies try to quickly identify are the ones that do not seem initially to be very serious but wind up spiraling out of control. A typical scenario is a back injury that is soft tissue in nature, but then ultimately results in multiple diagnostic images, hospitalization, surgery, more diagnostic images, prescription painkiller use, and an employee who becomes solidly entrenched in a disability syndrome.
Claims, like the ones described above, are the ones begging for more attention in the early stages of the case in order to prevent the claim from spinning disastrously out of control. The issue is being able to accurately identify these stealth high-cost cases as quickly as possible. Unfortunately, the early identification issue has proven to be historically problematic.
If the street-wise claims adjuster "sniff test" doesn't work, current technology can assist. This can be through predicative modeling algorithms that measure pressure points such as:
* Treatment codes
* Prescription drug use by category
* Type and number of diagnostic images
* Length of disability without an established return-to-work date
* An employer who does not want the employee back in their labor force
* Employee data (age, education, experience, etc.)
* Repeated hospitalizations
* Early representation of the employee by a skilled attorney who is well versed in the tenets of the worker's comp system
All of these areas can provide clarity into whether or not more resources should be timely directed toward certain cases. Since resources are far from unlimited, and carry a certain amount of expense to employ, these choices have to be made wisely. But the application of more resources to manage the claim early in the life of the file can make the difference between a superior outcome, and a less than propitious conclusion.
In terms of additional resources assigned to assist control high-risk claims, these can include nurse case managers, occupational rehabilitation specialists, outside investigators, independent medical evaluations by highly regarded physician specialists, structured settlement specialists, high powered defense attorneys, etc. The right combination of these resources applied at the right time in the life of each high-risk case is the objective of every claims organization.
Even if advanced analytics are utilized to identify possible high-cost claims, the decision to apply additional resources is ultimately always a human one. All a predicative modeling system can do is frame a group of claims to examine for possible issues. The responsibility for pulling the trigger on employing the various elements that may best help is a human judgment call. Choose unwisely, and allocated and unallocated costs will increase with little or no appreciable impact on the outcome of the claim. The helter-skelter "silver bullet" approach ("well, this didn't work, so let's throw something else at it") is rarely successful and almost always wasteful.
In the final analysis, a combination of computer-driven analytics and shrewd human judgment, informed by a surfeit of practical experience, is most likely the best tonic for success in the proper allocation of resources at the right time on the right claims. The companies that can accomplish this correctly more often than not, be accurate in that decision are going to experience better outcomes in the long run even on problematic cases.
There is no magic elixir or computer legerdemain that will substitute for a well thought out and constructed approach to early identification of possible high-risk claims and proper resource allocation on potentially these cases. As inconvenient as the hard work needed to construct a proper approach is, the payback will justify the investment of time and effort.
As the United States Marine Corps is prone to say: "After the pin is pulled, Mr. Grenade is not our friend." The point of the entire exercise is to keep the pin in on these potentially explosive cases.
December 12, 2012
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