While there
is considerable talk about fraud in Workers’ Compensation, the chatter usually refers
to claimant or employer fraud. Unfortunately, fraud and abuse also occurs in
medical management.
Medical fraud
Poorly
performing medical doctors are 100% predictive of high costs and poor claim
outcomes. When they are also corrupt, the damage can be exponential. We know poorly
performing and corrupt doctors are out there. More importantly, we also know how to find them!
When a
doctor knowingly over-treats, costs increase and outcomes are compromised. Disciplining
such providers by not paying them is one solution, but a more proactive
approach to managing them is to avoid them altogether. Identify the bad doctors
and carve them out of networks. Avoiding corrupt and inept medical doctors
prevents the needless spiral of high costs and adverse outcomes resulting from misbehavior.
Identify the perpetrators
Efforts
to solve the problem should focus on identifying the perpetrators by means of a
well-designed analytic strategy. Most agree with this philosophy, yet few
medical networks in Workers’ Compensation have seriously addressed the issue. The
data, when analyzed appropriately, will point out medical doctors who perform
badly.
Trail of abuse
Fraudulent
medical doctors and other providers leave a trail of abuse in the data. Bill
review data, claims payer data, and pharmacy data, when integrated at the claim
level including both historic and concurrent data, present a clear picture of undesirable
practices. Outliers float to the surface.
Among the
outliers found in the data are exploited frequency and duration of medical treatment.
Fraudulent providers have higher treatment frequency and duration than their
counterparts. Other outliers found in the data involve use of the most costly treatment
procedures, selected as first option. The timing of treatment can produce
evidence of corruption such as when more aggressive treatments like surgery are
selected early in the claim process.
Subtle abuse
Some of
the more subtle forms of medical fraud involve manipulating the way bills are
submitted. Corrupt practices attempt to trick standard computerized systems. They
consistently overbill, knowing the bill review system will automatically adjust
the bills downward. But systems can miss subtle combinations of diagnoses and
procedures and allow payment. If a doctor consistently overbills, what is the
motive? Likewise, some practitioners bill under multiple tax identifiers and from different locations. Unless these behaviors are being monitored, computer systems simply create different records for different tax ID’s and locations, making the records appear as different doctors. When attempting to evaluate performance, the results are skewed. Provider records must be merged and then re-evaluated to arrive at more realistic performance scores.
Another
method used by disreputable providers is to obtain multiple NPI numbers
(National Provider Identifier) from CMS (Centers for Medicare and Medicaid
Services). Once again, the data is obfuscated and deliberately made misleading.
Referral “rings”
The data
can also be analyzed to discover patterns of referral among less principled providers
and attorneys. Referral patterns can be monitored.
Litigation association
Medical
abuse also occurs in other ways. The data can be scrutinized to find doctors
who are consistently associated with litigated cases. That may mean they are
less effective medical managers or it could be an indicator they are part of a
strategy to encourage litigation and certain attorney involvement. Kickbacks are
not in the data, but the question is raised.
Calling a spade…
Many doctors
who skirt ethical practices would be shocked to be called fraudulent. Yet that
is exactly what it is. Changing the name does not whitewash the behavior.
Happy trails
Happily,
the good doctors are also easy to find in the data. Their performance can be
measured by multiple indicators in the data as they float to the surface with
the best in class. When analyzed over time and across many claims, they consistently
rise to the top.
Outcome-based networks
Selecting
the right doctors and other providers for networks is a complex but important
task. Data from many claims where individual providers and groups are involved
must be analyzed to distinguish how physicians perform in the Workers’ Compensation
context over time. Subtleties of questionable performance can be teased out of
the data. The most powerful approach is
to monitor the data in real time so that interventions effectively thwart the
perpetrators.
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
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