Proof of Value for Medical Management

In workers' comp, predictive analytics based on your historical data can measure what costs would have been without your interventions.

Everyone knows the bulk of workers’ comp costs now are medical. Claims reps and nurse case managers handle injured workers and their medical costs with utmost care. Anecdotes show that their work saves time and money. The problem is that concrete evidence of their value has been elusive—until now. How can costs avoided and time saved be measured? The measurements are like rabbits pulled from a magician’s hat. What really happened? Quantifying what did not happen is usually impossible. However, quantifying and measuring savings is completely feasible through a different approach, using predictive analytics. The workers’ comp industry does not readily embrace change or innovation. That is changing as pressure increases to become more efficient to sustain profitability as resources shrink. The best approach to meeting this challenge is incorporating advanced technical strategies such as predictive analytics that are designed to support and streamline the business process and make workers smarter. The collateral benefit is being able to objectively measure and report savings. The solution is to extensively analyze the organization’s historic data using predictive analytics and deliver the insights in the form of actionable information to all the stakeholders, including claims reps, medical managers and other decision-makers. Just a few steps are needed, including data analysis, data monitoring, informing and integrating the efforts of stakeholders and measuring the savings. The first and most critical initiative is analyzing an organization's historic data using predictive analytics methodologies -- because each organization has unique internal and culture processes regarding claims handling and medical management, using others’ data, regardless of how large the database, can mislead. See also: 2017 Issues to Watch in Workers’ Comp Situations and conditions found in the past are likely to recur. Once the risks are identified in historic data, they can be searched programmatically in current data through continuous data monitoring. When problematic situations occur in the data, appropriate responses and interventions are mobilized immediately. The insights are delivered to medical management stakeholders, including claims reps, medical case managers, senior management and others as appropriate. The knowledge delivered is structured to assist them in decision support and coordinating efforts. Risk information in claims is delivered concurrently to stakeholders so they can make early and sound decisions, then initiate appropriate action. Importantly, all medical management participants receive similar information so initiatives are coordinated and integrated, thereby implementing strong, multi-disciplinary approaches. When risk conditions in claims are identified in this manner, reserves in that claim need attention, as well.  When events and conditions in claims change, indicating a need for more intense medical management, reserving should also be addressed. Based on predictive analytics, the probable ultimate medical costs are projected and portrayed for claims reps, thereby providing key knowledge to support appropriate action. Data monitoring identifies claims with risk conditions concurrently and informs the stakeholders immediately. Intervention efforts are coordinated among claims reps, medical case managers and others, providing broad-based, integrated initiatives leading to improved results. Savings are gained through proactive, coordinated intervention by professionals who are offered key information for decision support making them accurate, efficient, and effective. See also: On-Demand Workers: the Implications When claims are closed, objective savings are measured by comparing projected performance based on predictive analytics with what was accomplished through active, integrated initiatives across all medical management participants. The calculations are quantifiable and objective. The simplest and most rewarding approach is to outsource this process to a knowledgeable medical analytics company. Internal processes need not change, but professionals and business processes are made more accurate and efficient—a win for the organization, its employees and its clients. Technology is far less expensive than people. When it is designed to assist professional workers by making them more accurate and efficient, the return on investment is profound.

Karen Wolfe

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Karen Wolfe

Karen Wolfe is founder, president and CEO of MedMetrics. She has been working in software design, development, data management and analysis specifically for the workers' compensation industry for nearly 25 years. Wolfe's background in healthcare, combined with her business and technology acumen, has resulted in unique expertise.


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