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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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Friday, April 14, 2017

How to Monetize Intelligent WC Medical Management

by Karen Wolfe     

”If data is the currency of the new digital economy, then organizations that know how to monetize data will generate the highest returns. They will make better decisions that lower costs, grow customer loyalty, and increase revenues.”[1]
Over the past twenty-five years, the Workers’ Comp industry has collected vast amounts of data. Moreover, organizations within the industry have easy access to their most valuable asset: their data. Their challenge now is to monetize the data and profit from it.
Experts say medical costs now amount to 60% of claim costs in Workers’ Comp. If true, organizations should be charging ahead to find ways to optimize medical loss management and monetize their data for profit.
Data integration
The first step toward monetizing medical data is to integrate data from disparate data silos. All bill review, claims system, pharmacy (PBM) and other relevant data should be integrated at the claim level to gain a full picture of individual claims. Once integrated, predictive analytics methodologies are applied to covert the data to usable information.
Past is prologue
What happened in the past is a good indicator of what will occur in the future when similar conditions appear. Organizational culture, protocol, and individual preferences are consistent influencers. Consequently, data gathered from other organizations may offer inaccurate results.
Analyze historic data using predictive analytics to discover conditions that are cost drivers or cost accelerators. Uncover trends. What conditions or combinations initiate or perpetuate high cost situations? Where are the gaps in timing in operational flow? What actions encourage positive or negative claim resolution? Finally, the information must be made actionable.
Inform stakeholders
Portray the predictive analytics-informed information for claim stakeholders in timely, informative notifications when risk situations occur. An example of this is a diagnosis of a comorbidity such as diabetes appearing in the data long after the date of loss. Predictive analytics has determined the comorbidity of diabetes adds complexity and cost to claims, therefore an alert is generated and key Information is conveyed to appropriate persons.
Probable ultimate medical costs
Based on predictive analytics, the probable ultimate medical costs for the claim are portrayed for the claims rep along with other key information regarding the claim in question. The claims rep adjusts medical reserves accordingly and moves on. Time is saved and accuracy is optimized.
At the same time, the predictive analytics-informed system automatically notifies the nurse case manager based on the organization’s referral protocol. The claims rep is informed of the referral but is not required to take action.
Similar claim information is presented to the nurse case manager for quick review, thereby integrating and coordinating claims and nurse case management initiatives.
Monetize medical management
Data is made intelligent and can be monetized through predictive analytics combined with a timely information delivery system. Searching for decision-support information takes time and is inefficient. Manually entering data is time-consuming, annoying, and often inaccurate. On the other hand, intelligent information delivered appropriately is monetized as claim stakeholders make informed decisions quickly, effortlessly, and accurately without need for data gathering and data entry.
Projected probable ultimate claim cost with comprehensive supportive information displayed for claims reps does not require data search or data entry. Even less-experienced adjusters are accurate and efficient. Accuracy and efficiency is optimized, productivity is increased, and profitability follows. Moreover, early intervention through timely alerts allows for action before further damage is incurred.
Medical loss management is also monetized by the ability to objectively measure claim cost savings. Having projected the ultimate medical costs for a claim, quantifiable cost savings are available at claim closure due to coordinated medical management initiatives. Monetization is realized through client satisfaction, customer loyalty, and client retention. Moreover, the story is proof of value serving the organization’s strategic competitive advantage.
Intelligent medical management
Organizations that monetize their data have greater returns, including return on investment. The intelligent medical management system is monetized internally and externally, thereby paying for itself. Such statements are familiar as sales platitudes, but with intelligent medical management, positive results are objectively measured. Savings are greater than the cost.

[1] Eckerson, W. How to Monetize Data: Strategies for Creating Data-Driven Applications. Eckerson-How-to-monetize-data.pdf Zoomdata. March, 2016.

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 measureable. karenwolfe@medmetrics.org