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.

Analytics
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.

Accountability
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.

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[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

If You Don't Know Where You're Going, You Might Land Somewhere Else

by Karen Wolfe

If you don’t know where you’re going, you might land somewhere else. It may at first seem like a senseless phrase, but research, planning, and goal-setting are important directional steps in both our personal lives and in business. The alternative is to react impulsively as events occur and conditions change following no particular plan or strategy. That sort of seat-of-the-pants approach insures landing off course.

Past is prologue
Even more importantly, without analysis of past performance, organizations will miss opportunities for designed excellence. If you don’t know where you’ve been, you could land somewhere else. Actions might be habit-based and detrimental in this fast-paced world.

Decisions and actions will be miscalculated when they are based on mere recollection of the past. Analyzing and understanding the past using technology tools is the way to gain insights that lead to knowledgeable actions going forward. That means analyzing the past to identify pivotal conditions and develop competitive or profitable responses.
 
Analytics of past performance will notify organizational leaders of conditions that should lead to strategic actions. Alerts are sent to the right persons at the right time regarding current situations with pre-planned initiatives.

However, simply studying the past is not enough. Too many organizations stop at the data analysis stage, missing the opportunity to maximize efficiency, accuracy, and profitability gained through applying analytics-informed insights. The insights gained through analysis should be conveyed to those making daily decisions for the organization. Still, there is a prerequisite to successfully leveraging analytics to inspire intelligent action. 

Spoiler alert
The spoiler for analyzing history to design the future is the organization’s data. Data must be accurate and complete to be reliable and worthy of logical planning based on it. For years the Workers’ Comp industry has focused on and relied upon billing and payment data. Most of it is accurate enough to pay bills, however, in this new age of analytics, gaps in data are obvious and sometimes crippling.
 
For instance, incomplete medical provider data in payer systems can be explained by the fact that in the past only an address and tax ID were necessary to pay a bill. But now analysts are asked to determine which providers are best, particularly for treating and appropriately managing injured workers. Such decisions cannot be made based on an address and tax identifier and making judgements based on inaccurate and incomplete data is perilous. In particular, medical provider data is often too lacking in quality and accuracy to be used in assessing medical quality.

Missing and misleading data
Provider name and address remain critical to performance analysis. However, the address on the bill should be the treatment rendering address rather than a PO Box. Granted, medical providers often list the PO Box because it is the location of accounts receivable, but it is no longer acceptable as the only address submitted with the bill. The rendering address is important to convenience for injured workers and employers, but it also is important in distinguishing individual providers and their practice patterns.

CMS (Centers for Medicare and Medicaid Services) requires the physician NPI (National Provider Identification) on all bills, as do all general health payers. The Workers’ Comp industry has not followed suit but now it must require NPI numbers. The NPI is essential for recognizing individual providers in all their rendering locations found in the data and distinguishing individual providers in group or facility settings.

The NPI is also crucial for assigning medical specialties when that significant data element is missing as it often is. Fortunately, the specialty can be ascertained from the CMS NPI. By insuring the organization’s data includes these few critical data elements, identifying the best medical providers and establishing outcome-based networks can be a straightforward and reliable process.

Take-away
Understanding the past is essential to intelligent development and consistent execution of organizational planning. Analytics relies on accurate and complete data to inform the best business strategies. Moreover, accurate and complete data is the tipping point because without it, the organization will land somewhere else.

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

How to Make WC Analytics Profitable

By Karen Wolfe

Organizations in Workers’ Comp are allocating significant dollars to develop analytics but many are still unable to realize its benefits. In fact, nearly all organizations in the industry are entertaining advanced analytics including data analysis, predictive analytics, or predictive modeling. Yet, they are unable to experience positive results. That is because analyzing the data is only half the job.

Stated simply, the way to accelerate return on investment for analytics is to make its insights actionable. In other words, translate analytic insights to specific actions that inform frontline professionals, making them more accurate and efficient.

Predictive analytics
Predictive analytics is a way of predicting the future using data from the past, thereby helping organizations and their professional workers respond quickly and in more appropriate or consistent ways. It enables organizations to tap their collected data to predict future business outcomes when similar conditions occur or inform workers of the best action based on historic outcomes. It is also provides guidance, accuracy, and decision support for frontline workers, thereby making them more efficient. Analytic-informed action is triggered by an automatic alert.

Intelligent actions
Analytic-informed alerts are directed to those who make day-to-day decisions. The technology-driven process of analyzing, then monitoring data is designed to provide timely and accurate information to those on the front lines, thereby streamlining operational processes. Analytics-informed efficiency and accuracy generate savings. However, many organizations stop at the data analysis stage, missing the opportunity to maximize efficiency and accuracy that leads to profitability.

Informed
Efficiency is achieved when those making frontline decisions are automatically provided the information they need when they need it. Search, lookup, and data entry are not needed to make a decision and move forward because the needed information is at hand. Consider how timely, comprehensive information sent to adjusters for Workers’ Comp reserving that includes probable ultimate medical costs based on historic information would offer process efficiency. Moreover, automatic coordination with medical case management based on predetermined protocols enriches the process and outcome.

Timeliness
The timing of delivered information with insights is critical. Systems should be designed to push correct information to the right person at the right time, requiring no effort on the part of the recipient. They simply act on the insights gained through predictive analytics, the key to making historic data valuable.

Comprehensive intelligence
Analytic-informed intelligence sent to frontline professionals in the form of an alert should be comprehensive, meaning all the information necessary to make a decision is provided in the alert. When the information is incomplete, other steps, including research and data entry are required and the efficiency advantage is lost. Moreover, the recipient, pressed by other matters, is less likely to heed the alert when required information is absent.

Accountability

Some complain claims reps are so busy they ignore alerts. However, a predictive analytics-informed system will automatically create an audit report of alerts sent, to whom, along with the claim and issue that prompted the alert.  Management then has an easy means of overseeing individual accountability and follow-through. Recall the Hawthorne Effect that demonstrated observed behavior results in improved performance.

Profitability

Analytic intelligence is redrafting the laws of profitability and providing direction for how to create new strategies and operational efficiencies. The opportunities to gain accuracy and efficiency through analysis of historic data are nearly limitless. Unfortunately, organizations stop at the data analysis stage, missing the opportunity to maximize profitability.

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