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 Avoid Insuretech Disruption

By Karen Wolfe

In insurance, those who hold the data, hold potential power. Those who analyze the data and apply the knowledge control their destiny.

“The abundance of data – and the technology used to capture it - is driving profound disruption in the relationship structure of the insurance industry. As the traditional gatherers and guards of massive amounts of data, insurers face threats from new, tech-savvy competitors who can adapt to changes more quickly.

There are very powerful trends coming together to cause serious industry disruption. That can be a big threat, but if insurers start responding now and embracing the change, it could also be a big opportunity.”[i]

What is Insuretech?
Google defines Insurtech as referring to the use of technology innovations designed to squeeze out savings and efficiency from the current insurance industry model. Insurtech is a portmanteau of “insurance” and “technology” that was inspired by the term Fintech (Financial Technology).

The problem
Longstanding reluctance to change is preventing many organizations in the Workers’ Comp industry from embracing new technology, especially technology that streamlines processes and worker performance. However, this approach is no longer sustainable. Simply stated, those who cling only to the old-time culture and ways will be disrupted. Think Amazon or Uber.

“Big Data and analytics are forcing insurers to adjust their processes when it comes to collecting and using data. With the expansion of the Internet of Things, sensor technology, machine learning and artificial intelligence, there is more information available than ever before.”[ii]

Data, the asset
Organizations that continue to ignore the facts will wonder why they are no longer competitive. Others who are open to new approaches using new technology will experience positive results. It is a matter of attitude and willingness to try newer methods.

Nevertheless, insuretech need not be invasive or costly. To make a positive impact on processes and outcomes, an organization must first take the position of data-centeredness, believing data is its valued asset.

Step ahead of disruption
Having accepted the position that data is the organization’s valuable asset, accepting and incorporating new technology requires focusing on only three basic initiatives: data quality, data analysis, and intelligent application of the intelligence gained through analytics.

Data quality
If data is an asset, then its quality must be valued and protected. Using poor or erroneous data never ends well. Information gained from poor quality data will not improve an organization’s processes or outcomes, will lead to poor decisions, and detrimental actions. Therefore, resources must be applied to guaranteeing quality data input. Moreover, considerable resources may be needed to improve historic data.

Over the last twenty-five years organizations have been focused on collecting data, but little attention has been paid to insuring the data is accurate and complete. Now that must change. A data-centered organization will also guarantee its data is pristine.

Analytics
The second initiative needed to avoid insuretech disruption is to analyze the organization’s data. Collect and analyze all data over the previous five years. Methods such as predictive analytics can be applied to gain greater understanding of the organization, how well it operates, and what are the cost drivers both operationally and at the transaction level. This is simply a matter if analyzing historic data and monitoring concurrent data to reveal trends, threats, and possibilities. Know thyself.

Intelligent knowledge application
Having quality data and analyzing it leads to the next critical step of designing intelligent solutions to problems identified during the analysis phase. Apply the knowledge gained to specific areas of need by creating “apps” that solve problems and improve processes in the organization.

Alert the right person when conditions or events pose a risk to the organization or work product identified in the analysis phase. Deliver key intelligence to specific individuals or groups at the exact time they need it for decision support. Facilitate timely communication within the organization. Knowledge assistance provided at the right time to the right persons saves time, creates accuracy, efficiency, and increases profitability.

Stepping into the world of insurtech and avoiding disruption is largely a matter of perspective and attitude. It requires a view that data is an asset and when properly managed, lets the organization define its destiny.

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[i] Will You Survive the Great InsureTech Disruption? James Dodge, Senior Consultant, Advanced Analytics & Data Solutions, Milliman. Risk and Insurance. 6-27-17

[ii] Ibid.

 

MedMetrics, a WC insuretech company, leverages predictive analytics to provide WC claims reps knowledge assistance by projecting probable ultimate medical losses, automatically integrating claims and medical management to contain predictive medical threats, and offering additional intelligent tools such as provider performance analysis and diagnostic severity scoring. MedMetrics clients are easily and affordably more accurate, efficient, and profitable.

 

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.

 

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[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 

The Secret Power of the NPI

by Karen Wolfe

This is a David and Goliath story. It’s about how the seemingly insignificant NPI code can fight medical fraud and positively impact effective Workers’ Comp medical management. Many in the industry consider the NPI irrelevant. Yet it is a powerful factor in medical management and medical fraud detection.

The NPI
The NPI is the National Provider Identifier assigned by CMS (Centers for Medicare and Medicaid) to individual medical providers and organizations that deliver medical services. It is required on bills for Medicare and Medicaid. Individual medical providers and medical groups must include their NPI on all bills submitted. 

If the NPI is required for Medicare and Medicaid reimbursement, it follows probably all medical doctors have a NPI number from CMS that uniquely identifies them. The problem is that many Workers’ Compensation payers do not ask for the NPI, do not require it, and even when the NPI is available, do not record it or transfer it to the next level. 

State requirement
Some, but not all states require the NPI on Workers’ Comp bills. However, even if it is added to the bill, it often goes no further.

Why bother?
The value of the NPI is that it uniquely identifies individual medical doctors. It carves out individual treating physicians in groups, organizations and facilities. Without the NPI associated with individuals, all those in a group are lumped together under the organization’s NPI or, worse, the entity’s Tax ID. This matters. The assumption is all members of the group practice exactly the same. But they do not.

Distinguish individuals
The ability to parse individuals from groups in the data is essential to fair performance analysis. Individual differences evidenced in the data can be distinguished, even when associated with a group with individual NPI’s. This is essential to creating quality preferred provider networks and directories. It is also indispensable for leveraging the data to create a teaching platform for improving provider performance in Workers’ Compensation.

Behavior change
Physicians should be given the opportunity to see themselves portrayed in graphic reports comparing their performance to others like them. By nature, they are high achievers and they want to show well. The graphic presentations are targets or guides for improvement. 

Simply paying attention to a treating doctor in this objective manner will result in behavior change!  Using the comparative data is invaluable, however, success depends on accurately identifying individuals in the data using the individual NPI.

Specialties
Another valuable use of the NPI is to assign medical specialties to individuals. Professional specialties can be obtained electronically from CMS databases using the NPI. Specialty is yet another data element missing in much of the bill review and claim system data. If the NPI number is available, specialties can be derived. 

Specialties are important so that treating doctors are grouped with other doctors who are similarly prepared and licensed. The argument from doctors that they only treat the more difficult cases is nullified when they are compared only to others in their specialty. The best example is pain management specialists who really do treat the more difficult cases. Their performance should always be compared to other pain specialists.

Fraud by NPI
Unfortunately, there are those who twist the positive aspects of the NPI for fraudulent purposes. Close examination of the data reveals less reputable medical doctors and other providers obtain multiple NPI numbers, using them in different locations or situations to deliberately obfuscate the data.

When multiple NPI numbers are fraudulently used, the door is open to undetectable duplicate billing. Systems cannot recognize overall performance for the individual because their performance is fragmented across multiple NPI’s. In order to accurately analyze performance for an individual, all treatment incidences should be combined for one practitioner, thereby creating a critical mass of data for that individual.

Much ado
While some will think the focus on NPI is much ado about nothing, it is not. Individual NPI numbers on all medical bills is essential. Payers should insist on it. In fact, reimbursement should be withheld until the correct information is included on the bill as is done in Medicare. 

Impact on medical management
Treating doctors not only drive direct medical costs, but also indemnity costs, return to work, and disability ratings at the end of the claim. They can also influence legal involvement. Consequently, finding the best doctors and avoiding the bad ones is crucial. 

The way to determine who should be included in quality medical provider networks is to analyze past performance based on the data. The only way to accurately analyze performance is to identify individual treating doctors in the data and evaluate their performance across multiple claims based on the relevant performance factors. Correct NPI numbers included on medical bills are essential.

What to do
Workers’ Compensation payers must require correct individual NPI numbers on all medical bills. This is not an outrageous demand and does not add to costs. However, it does require attention to the matter. The benefits are too great to miss this simple, yet powerful opportunity.

The simple little NPI is a powerful element in Workers’ Compensation medical management. It is the David that can effectively and affordably fight the medical fraud Goliath.

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

 

Make Your Data a Work-in-Process Power Tool

By Karen Wolfe

Heard recently, “Our organization has lots of analytics, but we really don’t really know what to do with them.” This is a common dilemma. Analytics (data analysis) are abundant, they are presented in annual reports and published in colorful graphics. Too often the effort ends there. Nice information, but how does it change operational flow, claim outcomes and profitability?

Obviously, the basic ingredient for analytics is data. After that comes skill, ingenuity, and creativity. Business intelligence and knowledge are severely limited without data. Fortunately, the last thirty years have been primarily devoted to data gathering.

Data evolution
Over the past thirty years or more, all industries have evolved through several phases in data collection and management. Main frame and mini-computers produced data and with the inception of the PC in the 80’s, data gathering became the business of everyone. DOS systems were clumsy and there were significant restrictions to screen size and data volume.

Recall the Y2K debacle caused by limiting  the year to two characters instead of four. The two digit year was made necessary in early computing because of restricted capacity.

Happily for the data gathering effort, progress in technology has been rapid. Advancement was enhanced first by local and wide area networks, then by the Internet along with ever more powerful hardware and lower costs. Data gathering has been overwhelmingly successful.

Big data
Now we have truckloads of data, often referred to as Big Data. In fact, a new industry has developed around understanding and managing huge data volumes. Once Big Data is corralled, analytic possibilities are endless. 

The Workers’ Compensation industry has also collected enormous volumes of data. Now, much is being done in the industry to actualize the analytics to produce knowledge that support reductions in costs and improved outcomes.

Imbed analytic intelligence
The best way to apply analytics in Workers’ Compensation is to create ways to translate and deliver intelligence to the operational front lines, to those who make critical decisions daily. Knowledge derived from analytics cannot change processes or outcomes unless it is imbedded into the work of adjusters, medical case managers, and other key personnel. These professionals make decisions that affect the course of claims and they need electronic knowledge tools to assist them.

Consulting graphics for guidance is cumbersome, interpretation is uneven or unreliable, and the results cannot be verified. Therefore, intelligence must be made easily accessible and easy to interpret and apply. Front line decision-makers need online tools designed to support decisions and direct actions.

Electronic monitoring
To effectively imbed analytic intelligence into operations, all claims data must be continuously monitored electronically. Data in claims must be monitored continuously so the system can identify claims that contain conditions cautioned by the analytics. The interpreted information is then linked to operations.

By electronically monitoring all claims for high risk events and conditions informed by analytics, high risk and migrating claims cannot slip through the cracks.

Personnel can be alerted of all claims with risky conditions identified through analytics. Additionally, the analytic delivery system should automatically document itself.

Self-documenting
The system that is developed to deliver analytic knowledge to operations should automatically self-document. That is, it should keep its own audit trail to record to whom the intelligence alert was sent, when, and why.

Without self-documentation, the analytic delivery system lacks authenticity. Those who receive the information cannot be held accountable for whether or how they acted on it. When the system automatically self-documents, those who have received the information can be commended for, or held accountable for their part. Management is able to review current status at any time.

Self-verifying
A system that is self-documenting can also self-verify, meaning results of delivering analytics to operations can be measured. Claim conditions and costs can be measured. Moreover, further analyses can be executed to measure what analytic intelligence is most useful, in what form, and importantly, what action responses generate best results.

The analytics-informed knowledge delivery system monitors all claims data, identifies claims that contain risk elements, and creates knowledge tools for front-line workers. The data becomes a work-in-process information and decision-support tool while analytics are linked directly to outcomes and savings are objectively measured.

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

 

7 Reasons You Really, Really Want WC Medical Analytics

by Karen Wolfe
In a recent post, Joe Paduda stated, “The workers’ comp, and, for that matter, the entire property and casualty insurance industry, is chronically systems-poor.  While other industries view IT as a strategic asset, continually investing billions in IT, WC/P&C considers IT an expense category to be mined for pennies to add to earnings per share.”[1]

As one who has worked on the vendor IT side of the Workers’ Comp industry for decades, I know for a fact Joe is exactly right. Nevertheless, both inside and outside change is impacting the industry—compliance requirements and how IT is perceived, financed, and implemented.

Moreover, customers are demanding more usable information. So as a way of advancing the perception part of medical analytics, seven reasons are offered here to whet the appetite for analytics-informed medical management

Analytics-informed medical management means collecting, integrating, and analyzing all relevant current and historic data to gain insights that will improve performance and outcomes. The following are a few very good reasons to invest in analytics.

1.    Look forward, not backward
An unfortunate, but persistent perception of business intelligence and data analysis is that reports are for looking at the past—how many claims, the trend in slips and falls, or how much money was spent last quarter. Interesting, but not actionable.

Much greater advantage can be gained from analyzing the data to understand what is happening now in order to improve procedures going forward. Identify cost drivers and develop prompt, appropriate, and consistent actions to redirect the organization.

2.    Find meaning in your data
The industry has been diligently collecting data for years, yet little attention has been paid to what the data might reveal. Analytics looks at the data to derive meaning, suggest direction, and empower informed decision-making.

Corporate leaders are often victims of their own denial, assuming all important information is known and current processes are the best they can be. Rarely is that actually the case and analytics can be eye-opening.

3.    Deliver intelligence to those who need it
Analytics can be used to evaluate medical provider performance, for instance, and deliver the information in real time to those who are directing care. Since poorly performing providers are guaranteed to add cost and complexity to claims, analytics used in this manner will directly impact efficiency, cost, and outcome.

Similarly, information about untoward events and conditions in claims delivered to operations concurrently will add efficiency and improved outcomes.

4.    Standardize procedures
A rule-based approach can be used to monitor data and create alerts of high risk conditions and events that occur in claims. Doing so inserts credibility, consistency, and comprehensiveness into the medical management process. Moreover, when standard procedures and actions are established to respond to specific alerts, the entire process can be measured for organizational improvement, cost-savings, and outcome success.

5.    Data as a work-in-process tool
Data can be a working tool. Analytics can be structured to concurrently tag data items that portend risk and cost in claims, then alert the person who can take action. Front line workers will gain decision support information in time to intervene effectively and usually avoid irreversible damage.

6.    Discover unexpected opportunities
When analytics are employed, newly discovered information or conditions understood differently can reveal opportunities. Interventions, priorities, and procedures might be restructured, streamlined, or enhanced. New products or delivery methods may also be realized and developed.

7.    Ensure the organization’s competitive advantage
Having implemented standard and consistent methodologies, improved outcomes are demonstrated objectively for clients and prospects. Proof of value generates confidence in operations and outcomes, a much easier sell.

The forgoing seven reasons to invest in medical analytics are not by any means all-inclusive, nor are they exhaustive in their portrayal. Much more can be said and gained by implementing medical analytics. The data ingredients are available and waiting.

The general tenor in the industry is to continue business as usual, but doing so has not produced desired results. Nor will it. As Paduda points out, IT in the WC/P&C industry is exceedingly underappreciated and underfunded.

Therefore, a  little creativity may be required to obtain what is needed. Outsourcing to a company that uniquely provides Workers’ Compensation medical analytics is one approach. Fees can be sized to the organization, thereby making it affordable. Being analytics-poor is no longer an option.

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Paduda, J. Who’s running your company. 05/20/2016 http://www.joepaduda.com/2016/05/whos-running-company/#sthash.LJIERvyq.dpufv

Karen Wolfe is the founder and President of MedMetrics®, LLC, a Workers’ Compensation, analytics-Informed medical management and technical services company. MedMetrics analyzes and scores medical provider performance and offers other online apps that link analytics to operations, thereby making them actionable. karenwolfe@medmetrics.org

Analytics-powered WC Medical Management

by Karen Wolfe

“I firmly believe based on extensive qualitative and quantitative research and the many interviews and discussions I’ve conducted with insurance industry leaders—that analytics represent the industry’s best path to success and survival in a rapidly transforming world.”[1] 

This is not a controversial statement. Most people now acknowledge the importance of analytics. The question is what is the best approach to analytics in order to achieve optimum results? It’s not enough to prepare analytic graphs and pin them to the wall or publish them in reports for the C-Suite. The information might be eloquent, but nothing will happen or change until it is pushed into operations where action can be taken. Analytics should solve problems. 

Solve problems 
In Workers’ Compensation, a major problem is our inability to contain continually increasing medical costs. Cost containment initiatives implemented to date have helped, but the job is far from complete. Happily, a new methodology is now available—analytics-powered medical management. 

Analytics defined 
Analytics is basically a fancy term for data analysis and there are many forms. A good place to begin is with descriptive analytics, a preliminary stage of data processing that creates a summary of historical data and integrates data from different sources to yield useful information. It also prepares the data for further analysis. 

Developing knowledge 
The data can be re-organized to make it easy to identify patterns and relationships, not otherwise obvious. The data can be queried and reported for more insight. It can also be re-packaged for better understanding or to initiate an action. To an individual in an organization, analytics can make the information derived from the data easy to locate, access, understand, and act upon. 

Real time intelligence 
When the data is monitored continuously, business units gain the advantage of near real time intelligence. Concurrent knowledge of conditions and events in a claim offers the opportunity for early intervention. Early intervention means the damage can be curtailed, thereby reducing claim costs and complexity. Outcomes are improved. 

Actionable information
Information is most powerful when it is current. What occurred two months ago may not be accurate or even relevant now. Conditions about events may have changed substantially so time is wasted manually updating the information before taking action.

One of the most important benefits of analytics is the ability to push timely information to the people who need it and can act on it most effectively. In the case of Workers’ Compensation, those persons are most likely claims adjusters and medical case managers who are in the trenches with claims. When these business units are alerted to pre-defined conditions in claims, their responses are more authentic and better outcomes result. 

Structured notification 
Specific information in claims pushed to the appropriate person in near real time is powerful. That person might be a claims adjustor, medical case manager, supervisor, or medical director who will act on the information based on procedures developed by the organization. The organization determines what situations in claims should be addressed, those potentially the most costly or disruptive based on historic analysis. Moreover, the organization determines what actions should be taken, and by whom. 

Structured response 
Structured notification and responses in the form of standardized procedures lead to consistency. As with any organizational procedure, allowances are made for professional authority, nevertheless, cost savings gained through consistent processes can be reliably measured. 

Spon
Measureable results 
Measures of medical management savings in Workers’ Compensation have been elusive. Without structured problem identification and response, apples to apples comparisons and analyses are impossible. A major benefit of analytics-powered medical management is the ability to dependably measure the benefits derived through data monitoring, analysis, notification, and response.

Karen Wolfe is the founder and President of MedMetrics®, LLC, a Workers’ Compensation, analytics-powered, medical management company. MedMetrics analyzes and scores medical provider performance and offers online apps that link analytics to operations, thereby making them actionable. karenwolfe@medmetrics.org

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[1] Applebaum, S. Analytics and Survival in the Data Age. LinkedIn Pulse. news@linkedin.com. February 18, 2016.