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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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Thursday, September 28, 2017

The Myth of Predictive Analytics--Really??

by Karen Wolfe

Mark Walls recently posted an article entitled, “The Myth of Predictive Analytics”[1] where he says he has yet to see cost savings from predictive analytics. Such a statement will surely generate a firestorm of comments. This is one of them—and it specifically addresses predictive analytics-informed medical cost management in Workers’ Comp.

The power of predictive analytics to mitigate medical costs is entirely dependent on the operational design of the delivery system. Predictive analytics is the information vehicle that creates knowledge for claims adjusters and others in the medical management process. System design determines how the information gained from predictive analytics is operationalized. How the information is implemented makes all the difference.

Walls goes on to say, “However, the potential for cost savings doesn’t come from the flag, but what you do in response to it. You need to take action and do something differently than you would have done without the flag.”[2] To a point, that’s true. However, the timing and method of delivery and format of the “flag” is critical. The conditions of information delivery that drive cost savings are timeliness, accuracy and efficiency, ease of use, and structured protocols. All are functions of delivery system design.

Timeliness for early intervention
Information must be delivered in the form of alerts as concurrently as possible. The claims rep should receive the information very close to the time of the risk occurrence. To achieve that, the data must be monitored continually with alerts sent immediately. Factors unknown early in the claim can occur at any time throughout the claim. Timely notification activates early intervention, before further damage is done and before the situation becomes more complex. That saves time, money, and leads to better outcomes.

Accuracy and Efficiency
An alert is useful only if it contains all the information the claims rep needs to make an informed decision, to adjust reserves, and to initiate measures that will prevent further medical loss. Predictive analytics is used to calculate and portray projected costs based on history, differentiated costs, and expected time lines. The alert also displays a medical summary of the claim. All the information is portrayed for the claims rep and requires no data look-up and no data entry.

Accuracy and efficiency are cost savers because they are time savers. Even less-experienced claim reps can take accurate steps when all necessary information is provided.

The information generated by predictive analytics notifies and informs the claims adjuster at the appropriate time without additional effort on the part of the adjuster. The system automatically portrays all pertinent information without need for searching or data entry. At that point, the adjuster can take appropriate and informed action.

Structured protocols
Medical management in Workers’ Comp is traditionally designed and delivered by individuals in the organization in one-off situations. That means processes are inconsistent. Good system design that draws from predictive analytics infuses structure and measurability into the process. Those situations in claims that should be referred to a nurse case manager are tagged in the system by senior management in advance, so they are referred automatically. The claims adjuster is relieved of the problem of when to refer.

The system is designed to make referrals automatically, thereby making them timely and consistent. Pre-determining what kinds of conditions will be referred and to whom, is how the organization sets up standardized medical management protocols. Such consistent, intelligent process management generates measurable results.

Measure results
Cost savings are objectively and accurately measured in a predictive analytics-supported system. On case closure, actual medical costs for the claim are compared to predicted costs based on documented history. Because of predictive analytics and continuous data monitoring, interventions are executed early, making them more effective. Appropriate referrals are made automatically according to protocol rather than intuition. The medical management team collaborates to improve on projected costs.

Documented process
Medical management alert activity on the claim has been documented by the system throughout the course of the claim. Therefore, costs can be appropriately allocated to the claim, the client, or policy-holder including activity detail, thereby creating transparency and trust among constituents. The organization enjoys increased profitability and strategic competitive advantage.

Walls also states, “In the end, good old-fashioned claims handling skills are still the best way to achieve superior outcomes on claims.”[3] However, when the claims handler is supported by a well-designed, predictive analytics-informed intelligent assistant, claims handling the old way is simply obsolete.

Karen Wolfe is the founder and President of MedMetrics®, LLC, a Workers’ Compensation, predictive analytics-informed medical loss management and technical services company. MedMetrics offers intelligent medical management systems that link analytics to operations, thereby making insights actionable and the results measurable. karenwolfe@medmetrics.org

[1] Walls, M. The Myth of Predictive Analytics. Leaders Speak. WorkCompWire. 9-19-2017. http://www.workcompwire.com/2017/09/mark-walls-the-myth-of-predictive-analytics/
[2] Ibid.
[3] Ibid.