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The MedMetrics blog provides comments and insights regarding the world of Workers’ Compensation, principally, issues that are medically-related. The blog offers viewpoints regarding issues affecting the industry written by persons who have long experience in the industry. Our intent is to offer additional fabric, perspective, and hopefully, inspiration to our readers.

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Tuesday, October 14, 2014

Early Intervention Drives Better Outcomes, But is Not Really Pursued

by Karen Wolfe

Early intervention drives better outcomes. It’s a statement that garners little resistance. Everyone agrees when a problem is found early, the solution is easier. Thwarting a problem early in its course produces better results. Yet few systems are in place to guarantee early intervention into problematic Workers’ Compensation claims.

Early intervention is a fine idea, but not always pursued. Work flows and systems in the industry are not typically designed to target the goal. To be effective, early intervention requires identifying the claims needing attention as soon as possible in their course, then mobilizing action procedures.

Predictive modeling
One effort to identify claims early that is widely acclaimed in the industry is predictive modeling. Elaborate analysis of the data using advanced mathematical methods is used to identify new claims that will likely become problematic. Regardless of the sophistication of the math, finding those claims remains a guessing game. Not every future problematic claim will be tagged. Likewise, claims that do not meet the modeling criteria, yet migrate anyway, will not be recognized. Predictive modeling can be helpful but it is imperfect and costly.

Containerizing human responses
Containerizing human conditions and responses is possible to a point. However, predicting human behavior is imperfect at best. Moreover, a second step is necessary: consistently intervening in the identified problematic claims. Once the troublesome claims are detected, certain action steps must follow.

Data monitoring
A more practical methodology for identifying costly claims is to monitor the data on a concurrent basis to uncover dicey conditions in them.

Rather than predicting which claims will be risky, the conditions that portend risk and cost in claims are isolated and then identified in claims as they occur.

Technology is used to find the claims that bear those conditions whenever they occur throughout the course of the claim. All claims are monitored, so none are missed. No guesswork is involved.

Step two
The data monitoring approach is powerful, but as with predictive modeling, that is true only when the next step is taken. Organizations that undertake a process for identifying risky claims early stand to lose the entire benefit unless they also structure procedures for intervention. The appropriate persons must be notified about problematic claims immediately and those persons must act to carry out the recommended procedures.

Whether the alert recipients are claims adjusters, medical case managers, or someone else, they must follow intervention procedures for best results. Using the data monitoring approach, each condition that is sought in the data should be associated with a prescribed intervention procedure.

Standardized interventions
Follow up procedures should be specific so that analyses can be made of their effects. For instance, when the condition identified in a claim is the third prescription for a Schedule II drug, the system might be set to alert the medical director. A standard method of intervention or approach for intervening with the treating doctor is followed.

Another example of a problem is extended medical treatment past a designated point for low back strain. The alert is sent to the claims adjuster whose procedure is to engage a medical case manager to investigate. The investigation procedure is standardized.

Examples of how this works are unlimited, but the important thing is that intervention procedures are analyzed in advance and clearly stated so the actions are consistent across the organization and going forward, regardless of who actually carries out the intervention. Obviously, details of actions may be variable, but the general course should be followed.

Measuring results
The plight of medical case management has long been that results could not be measured. Consequently, medical case management as a strategy has been undervalued.

Categorize interventions
Moreover, medical case management could not be measured because interventions are delivered by individuals, even though usually professional nurses, each is different. However, intervention tactics can be categorized so outcomes can be calculated. The benefit of using a standardized approach is that outcomes can be compared and measured by the cause condition and intervention employed.

Automated referral
Claims adjusters sometimes fail to refer to medical case management for a variety of reasons. When early intervention procedures are standardized, the referral is automatically made by the system, thereby eliminating the burden of referral for claims adjusters. Efficiency is good.

Simply stated, early intervention is more effective than late intervention. The problems have not yet morphed into catastrophe and are usually easier to solve. Moreover, systems and procedures should be established to automate problem claim identification and follow up procedures. Best results can be pinpointed and continued. Lesser results can be modified. The upward spiral of quality improvement is continuous.

Karen Wolfe is the founder and President of MedMetrics®, LLC, a Workers’ Compensation medical analytics and technology services company. MedMetrics offers online apps that super-charge medical management by linking analytics to operations, thereby making them actionable. karenwolfe@medmetrics.org