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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, February 14, 2019

Merge Workers' Compensation Analytics with Automation to Gain Efficiencies

by Karen Wolfe

“Industry 4.0[1] allows manufacturers to capture and analyze data from nearly every point in their operations. When these capabilities are coupled with data analytics and automation tools, manufacturers can wield insights to improve processes, discover efficiencies and implement cost-saving measures like predictive maintenance.”[2] Workers’ Compensation payers can mirror this process to achieve the similar results.

The key factors to achieve these results are to 1) capture data, 2) make data the operational glue, 3) analyze the data, 4) Implement automated tools to transmit knowledge, 5) institute accountability and 6) report efficiencies and cost savings. These functions implemented by Workers’ Compensation claims and medical case managers lead to efficiencies and measured cost-savings.

Data capture
Industry captures and analyzes data from every point in their operations. Claims management payers similarly capture data from multiple sources. Among the data points are bill review, claims systems, utilization review, case management, and pharmacy benefit management. However, in order to analyze the data it must be merged to view the entire claim. Fragmented data points will always omit important information.

Data glue
Raw data is known to be nearly useless for analysis. Moreover, fragmented data or data sets are similarly insufficient. Data is the operational glue that when merged at the claim level provides a comprehensive view of a claim, risk factors as they emerge, and progress of the claim. When the data is captured, merged, and monitored at the claim level, it can be analyzed to gain actionable insights for optimal claim management efficiency.

Pre-defined analyses of the integrated data is executed at all points in the claim process by monitoring the data continually. Risks, conditions, and events are identified in the concurrent data that merit attention. They are tagged and transmitted to the appropriate professional in the organization.

Automated tools
A powerful form of automation in claim medical management are electronic alerts generated throughout the claim process. Systems are designed to concurrently monitor the integrated claim data and automatically generate alerts of situations, conditions, events, or other information of concern to the appropriate persons immediately. Early and timely intervention is known to improve outcomes and save money. The alerts provide claim and case management professionals with actionable insights.

Decision support
Actionable insights are made even more powerful when combined with knowledge support. Relevant information accompanying an alert prompts appropriate and timely action, thereby creating efficiency in the medical management process.

In manufacturing as well as in claims management, automated alerts are ineffective if the targeted professional ignores them. Therefore, the automated system must be accompanied by an accountability system that documents alerts sent, to whom, for what claim, and the reason for the alert. This does two things: It creates a tool for management to follow up on automated alerts and it also provides the necessary information to allocate costs appropriately.

Report efficiencies and savings
Analysis of automated alert activity creates even more efficiencies. Compare claim outcomes with similar past claims to measure savings gained through intense data monitoring, analysis, and early intervention. Document the efficiencies and cost savings achieved by information-supported timely intervention. Additionally, compare the process and outcome efficiency and savings with other payer organizations through medical management benchmarking by a third party.

Benchmark outcome performance
Payer clients and constituents such as senior management want and deserve proof of claim and medical management quality. Historically, savings have been reported in terms of medical network discounts and reduction from billed to paid amounts from bill review. Both are problematic. However, benchmarking claim outcomes against independent third party payer data offers reliable proof of quality performance. Moreover, it offers outcome information with enough granularity to guide improvement in performance going forward.

[1] Industry 4.0, refers to the fourth industrial revolution, the cyber-physical transformation of manufacturing.www.TechTarget.com
[2] Tiernan, K. Discover New Efficiencies with Data Analytics and Automation. https://www.linkedin.com/pulse/discover-new-efficiencies-data-analytics-automation-kirstie/?trk=eml-email_feed_ecosystem_digest_01-recommended_articles-10-Unknown&midToken=AQEsLNGx7t4Zlg&fromEmail=fromEmail&ut=3qM8IQ5R7khUA1
 Karen Wolfe is the founder and President of MedMetrics®, LLC, an independent 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. MedMetrics also provides medical management outcome benchmarking services.  karenwolfe@medmetrics.org