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
