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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, November 8, 2016

Analytics-Informed Early Intervention Drives Best Outcomes

by Karen Wolfe

Early medical management intervention in Workers’ Compensation drives better outcomes. When a problem is discovered early, finding a positive solution is quicker, easier, and more effective. Moreover, predictive analytics-informed early intervention is even more powerful.

Past is prologue
Even though early medical management intervention is known to work, it is not always pursued aggressively. To be most effective, knowing what to look for in open and active claim data is key. 

The past is a preface to the future. Analyzing historic data to identify the kinds of conditions that have been costly to the organization reveals what to look for going forward. Some conditions are generally known. Examples are comorbidities that accompany injuries and certain problematic or severe injury or illness types. Yet, other less obvious, but troublesome conditions and preemptive situations must be teased out of the data using predictive analytics methodologies.

Predictive analytics
Predictive analytics is a methodology used to identify historic claim conditions that are likely to be troublesome in future claims. Conditions in claims that have led to high costs and poor outcomes in the past are isolated. Once the conditions are pinpointed a system is designed to continually monitor the data going forward and to notify adjusters and medical case managers when those conditions occur.

Continuous data monitoring
A practical method for uncovering problematic claims is to electronically monitor the data to reveal dicey conditions as they occur. Technology is used to find the claims that bear high risk conditions whenever they occur throughout the course of the claim. All claims are monitored continuously, so nothing is missed. Even subtle claim migration is exposed.

Data monitoring for conditions discovered through predictive analytics is powerful. Yet, the next step is also essential. Organizations that implement an analytic process for identifying risky claims early stand to overlook the entire benefit unless they also structure procedures for intervention. Importantly, the appropriate persons must be notified immediately and they must carry out the organization’s recommended procedures.

Claims adjusters are often alerted first. However, when medical case managers are alerted as well, the two can execute intervention procedures collaboratively. Claims adjusters may neglect to refer to medical case management as early as they could. But when the automatic referral to medical case management is made simultaneously by the system, that issue is eliminated.

Collateral opportunity
When claims adjusters receive an alert of adverse conditions developing in a claim, they know reserves should be adjusted. Predictive analytics can also inform adjusters of the probable ultimate medical reserve amount for that claim based on history, thereby making reserving easy, timely and accurate.

Measured success
A bonus advantage of an early intervention process informed by predictive analytics is the ability to objectively measure success. At claim closure, costs and other outcomes can be measured and compared with those for similar claims in the past. The savings effects of early problem identification and intervention by claims reps and medical case managers are posted for constituents as objectively measured savings.

Simply stated, early intervention is more effective than later intervention. Damage control is far more achievable. The problems have not yet morphed into catastrophic or irreversible states. Predictive analytics-informed systems and data monitoring can be established to automate tagging problem conditions in claims as they occur. Those who will intervene early are alerted. Finally, reporting objective measurements of success is the payoff.

Karen Wolfe is the founder and President of MedMetrics®, LLC, a Workers’ Compensation, analytics-informed medical management and technical services company. MedMetrics offers online apps and alerts that link analytics to operations, thereby making them actionable and measureable. We don’t do medical management. We make your medical management stronger. karenwolfe@medmetrics.org