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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, March 30, 2017

Intelligent WC Medical Management, a Process for Efficiency and Measured Results

by Karen Wolfe

Technology in Workers’ Comp is hardly new, but new ways to infuse technology and predictive analytics into the claims and medical management processes can significantly improve accuracy, efficiency, outcomes, and, importantly, profitability. Well-designed technology that streamlines operational flow, provides key knowledge to the right stakeholders at the right time, promotes efficiency, and generates measureable savings is formidable. The system is intelligent and includes these key components:
1.     Predictive analytics
2.     Data monitoring
3.     Knowledge for decision support

Predictive analytics
Predictive analytics is the foundation for creating an intelligent medical management process. Analysis of historic data to understand the risks and cost drivers is the basis for an intelligent medical management system. For the risks identified, the organization sets its standards and priorities for which stakeholders are automatically alerted to those specific conditions in claims as they occur.

The stakeholders are usually claims reps and nurse case managers but others inside or outside the organization can be alerted, such as upper management or clients, depending upon the situation and the organization’s goals. Upper management establishes specific action procedures for specified conditions or situations, thereby creating consistent procedures that can be measured against outcomes.

Data monitoring
Incoming data must be updated and monitored continuously. Random or interval monitoring leaves gaps in important claim knowledge that is overlooked until the next monitoring session. The damage may have escalated by then. With continuous data monitoring, everything is reviewed continually so nothing is missed. When the data in a claim matches the conditions outlined by the predictive modeling, an alert is sent to the stakeholder so action or intervention is initiated.

Some say the stakeholders will not comply with such a structured program because they resist being directed. To solve that problem, accountability procedures in the form of audit trails in the system act as overseer. At any point, management can view what alerts have been sent, to whom they were sent, for what claim, and for what reason, thereby observing participation and supporting accountability.

Knowledge for decision support
The alerts sent offer collected knowledge about the claim needing attention so the stakeholder is not forced to search for information before deciding upon an action. The reason the alert was triggered, detailed claim history including medical costs paid to date is displayed for alert recipients. Importantly, the projected costs for a claim with similar characteristics are portrayed, making reserving adjustments easy and accurate.

The projected ultimate medical costs for the identified claim is portrayed for the claims rep based on the analytics, thereby providing decision support for adjusting reserves. Data entry into the system is never needed, therefore, accuracy and efficiency is optimized.

At the same time, a nurse case manager is automatically notified of the situation if indicated by the organization’s rules in the system and is informed with the same claim detail. Now the case manager and claims rep are collaborating to mitigate the costs for this claim. They know the projected ultimate medical cost for the claim and the projected duration of the claim so they have a common and concrete target to challenge. Moreover, improvements on the projections offer objective and defensible cost savings analysis.

Predictive analytics combined with properly designed technology to create an intelligent medical management process establishes a distinct advantage. Knowledge made available at the appropriate time for the right people leads to efficiency and accuracy. Early, intelligent intervention drives better results.  Stakeholders coordinate efforts to mitigate the claim, working toward a shared goal. Finally, knowledge provided for decision-support positions for measureable, objective, reportable savings at claim closure.

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