Data is Your Weapon of Choice

by Karen Wolfe

Managing the medical portion of Workers’ Compensation claims can be daunting. The variables are endless. Vendors of all types, extraneous and overlapping events, and even participant attitudes can impact the cost equation. Moreover, injured employee recovery lies in the balance, making the effort essential.

Longstanding methods

Current managed care initiatives have long been in play. They include bill review, utilization review, discounted medical provider networks, medical case management, fee schedules, guidelines, and peer review. That should do the job, but apparently not.

The medical portion of claims continues to rise while its portion of overall case cost is also increasing in most states. Medical costs are 60% of case costs, yet in some states, it is approaching 70%. 

The ‘tried and true” methodologies have been in place in Workers’ Compensation for about twenty-five years. Basically, the industry is continuing to follow the same pathways while hoping for different outcomes. Enough said.

Save the baby

This is not to say we should scuttle the strategies in place. Instead, the focus should be on updating and intensifying the existing processes to achieve their intended results.

Workers’ Compensation is an industry replete with transactions that are recorded digitally. First reports of injury, bill review, pharmacy benefit programs, and claims system paying bills and documenting events, all continually contributing to the data mass for each claim. Effectively analyzing that data on a concurrent basis and making the business knowledge available to claims adjusters and other decision makers is a powerful approach to strengthening current systems.

Data is your weapon

Analyzing data and converting it to useful information is the key to enhancing current medical management techniques. Writing reports and analyzing trends cannot impact outcomes. Such measures focus on the past that cannot be changed. Data must be utilized in new ways.

The first prerequisite is getting data-derived information to the front lines quickly. The business units should have access to analyzed information as concurrently as possible. Early information sets the scene for early intervention and resolving problematic situations in claims before they spin out of control.

Continuous data monitoring

Distributing information continuously requires that the data be electronically monitored and analyzed continually, not at the end of the month or quarter. When conditions that portend risk occur, the appropriate person is automatically notified. That might be the claims adjustor, medical case manager, medical director, supervisor, or manager. Importantly, the notified person will follow the organization’s approved procedures, thereby lending structure to the process.

Monitoring data and notifying the right people when indicators in claims point to risk mobilizes proactive medical management. Refer to the article, Early intervention drives better outcomes, but is not really pursued.

Other unique data initiatives can be even more compelling.

Select the best to improve networks

Research in the industry irrefutably shows poorly performing medical providers lead to high cost and poor results. Poorly performing doctors in the Workers’ Compensation context are those who have little understanding of the system or deliberately abuse the system through overutilization. Indicators of such poor performance are readily found in the data.

The data will reveal the poor performers, those who ignore basic Workers’ Compensation needs such as early return to work, as well as those who bleed the system with excessive treatment practices.

Treating doctors essentially cause, influence, or control the significant portion of medical costs. Once the injured worker is in the doctor’s care, opportunities to steer the course with medical management methods nearly disappear. Consequently choosing the right physician at the start is essential.

Directing care

Using data analysis to select the best practice doctors is the way to prevent problems and smoothly lead to the most optimal outcome. In many states this is possible and encouraged. In other states directing care is not allowed. Nevertheless, non-traditional applications of analytics can optimize results.

Behavior modification

When directing care to the best doctors is not possible, the next best option is to change the perpetrating doctors themselves. The fact is, people, and maybe especially doctors, do not like to look bad. Presenting them with analytic representations of their performance compared to others of the same specialty in the state is a powerful behavior change methodology. Those who are outliers will begin to move toward the mean.

Changing medical provider performance is not impossible! When they see themselves graphically compared to others based on the data, the information is indisputable. Of course, they will first attempt to push back. One way they argue is to say they treat only the more serious cases. That could be true.

Pièce de résistance

However, the pièce de résistance is to correct for medical severity in performance analytics, thereby leveling the playing field. Those who treat more serious injuries as evidenced in the data are compared only to others who treat similarly difficult cases.

Adjusting for case risk or severity by diagnosis is how to diminish resistance for poorly performing treating physicians. Graphic presentations of comparative performance cannot be disputed. The fairness is built in.

As the treating provider outliers move toward the performance mean, they may never achieve best-in-class, but their outcomes will gradually improve. They will also be aware of continued surveillance so the impact persists. Positioning data in this way is your weapon of choice for a powerful, yet bloodless medical management solution.

Karen Wolfe is the founder and President of MedMetrics®, LLC, a Workers’ Compensation medical analytics and technology services company. MedMetrics analyzes the data and offers online apps that super-charge medical management by linking analytics to operations, thereby making them actionable. karenwolfe@medmetrics.org

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Early Intervention Drives Better Outcomes, But is Not Really Pursued

by Karen Wolfe

Early intervention drives better outcomes. It’s a statement that garners little resistance. Everyone agrees when a problem is found early, the solution is easier. Thwarting a problem early in its course produces better results. Yet few systems are in place to guarantee early intervention into problematic Workers’ Compensation claims.

Early intervention is a fine idea, but not always pursued. Work flows and systems in the industry are not typically designed to target the goal. To be effective, early intervention requires identifying the claims needing attention as soon as possible in their course, then mobilizing action procedures.

Predictive modeling

One effort to identify claims early that is widely acclaimed in the industry is predictive modeling. Elaborate analysis of the data using advanced mathematical methods is used to identify new claims that will likely become problematic. Regardless of the sophistication of the math, finding those claims remains a guessing game. Not every future problematic claim will be tagged. Likewise, claims that do not meet the modeling criteria, yet migrate anyway, will not be recognized. Predictive modeling can be helpful but it is imperfect and costly.

Containerizing human responses

Containerizing human conditions and responses is possible to a point. However, predicting human behavior is imperfect at best. Moreover, a second step is necessary: consistently intervening in the identified problematic claims. Once the troublesome claims are detected, certain action steps must follow.

Data monitoring

A more practical methodology for identifying costly claims is to monitor the data on a concurrent basis to uncover dicey conditions in them.

Rather than predicting which claims will be risky, the conditions that portend risk and cost in claims are isolated and then identified in claims as they occur.

Technology is used to find the claims that bear those conditions whenever they occur throughout the course of the claim. All claims are monitored, so none are missed. No guesswork is involved.

Step two

The data monitoring approach is powerful, but as with predictive modeling, that is true only when the next step is taken. Organizations that undertake a process for identifying risky claims early stand to lose the entire benefit unless they also structure procedures for intervention. The appropriate persons must be notified about problematic claims immediately and those persons must act to carry out the recommended procedures.

Whether the alert recipients are claims adjusters, medical case managers, or someone else, they must follow intervention procedures for best results. Using the data monitoring approach, each condition that is sought in the data should be associated with a prescribed intervention procedure.

Standardized interventions

Follow up procedures should be specific so that analyses can be made of their effects. For instance, when the condition identified in a claim is the third prescription for a Schedule II drug, the system might be set to alert the medical director. A standard method of intervention or approach for intervening with the treating doctor is followed.

Another example of a problem is extended medical treatment past a designated point for low back strain. The alert is sent to the claims adjuster whose procedure is to engage a medical case manager to investigate. The investigation procedure is standardized.

Examples of how this works are unlimited, but the important thing is that intervention procedures are analyzed in advance and clearly stated so the actions are consistent across the organization and going forward, regardless of who actually carries out the intervention. Obviously, details of actions may be variable, but the general course should be followed.

Measuring results
The plight of medical case management has long been that results could not be measured. Consequently, medical case management as a strategy has been undervalued.

Categorize interventions

Moreover, medical case management could not be measured because interventions are delivered by individuals, even though usually professional nurses, each is different. However, intervention tactics can be categorized so outcomes can be calculated. The benefit of using a standardized approach is that outcomes can be compared and measured by the cause condition and intervention employed.

Automated referral

Claims adjusters sometimes fail to refer to medical case management for a variety of reasons. When early intervention procedures are standardized, the referral is automatically made by the system, thereby eliminating the burden of referral for claims adjusters. Efficiency is good.

Summary

Simply stated, early intervention is more effective than late intervention. The problems have not yet morphed into catastrophe and are usually easier to solve. Moreover, systems and procedures should be established to automate problem claim identification and follow up procedures. Best results can be pinpointed and continued. Lesser results can be modified. The upward spiral of quality improvement is continuous.

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