How to Spot Medical Fraud in Workers' Compensation

by Karen Wolfe

The chatter about fraud in Workers’ Compensation usually centers around employee or employer fraud. However, fraud and abuse in medical treatment and management is evermore prevalent. Finding the perpetrators is key. 

Incompetence is not fraud 

Poorly performing medical doctors are 100% predictive of high costs and poor claim outcomes. They are associated with adverse events during treatment resulting in poor outcomes. Post-operative infection and medical complications can signify a doctor’s poor performance when it occurs with some regularity. Additionally, lost time and high indemnity costs can indicate the doctor is unaware of the unique needs of Workers’ Comp. However, incompetency does not necessarily mean the doctor is fraudulent or abusive. 

Medical fraud 

When a doctor knowingly over-treats, costs increase and outcomes are compromised. The best approach to managing these doctors is to avoid them altogether. Identify the low-value doctors and carve them out of networks. However, deliberate fraud ups the ante.

Avoiding inept medical doctors prevents the needless spiral of high costs along with injured workers’ inconvenience, financial drain, and pain. However, medical fraud and abuse takes provider performance to another level altogether.

Poorly performing treating physicians are out there and they can be found by analyzing the data. But when they are also dishonest or corrupt, the damage can be exponential. These perpetrators can also be found in the data, but different sleuthing is required. 

Anti-fraud analytic strategy 
Efforts to find the perpetrators requires a well-designed analytic strategy. Most would agree with this logic, yet few medical networks in Workers’ Compensation have undertaken the challenge. The data, when analyzed appropriately, will point to medical doctors who are abusing the system. 

Trail of abuse 
Fraudulent medical doctors and other providers leave a trail of abuse in the data. Integrated bill review data, claims payer data, and pharmacy data, including history will paint a clear picture of undesirable practices. Outliers underscore themselves.

Among the outliers found in the data are exploited frequency and duration of medical treatment. Fraudulent providers have significantly higher treatment frequency and duration than their counterparts for the same medical conditions. Naturally, such inflation increases cost.

Other outliers found in the data involve use of the most costly treatment procedures as first and short term treatment choices. The timing of treatment can produce suspicion of corruption. More aggressive treatments like surgery are selected early after injury rather than less aggressive, more conservative approaches. 

Subtle abuse 
More subtle forms of medical fraud involve manipulating the way bills are submitted. Standard computerized systems can be fooled with tactics such as overbilling. Bill review systems will automatically adjust the bills downward, but consistent, excessive over-charging can be an indicator of fraud. 

Misleading identifying codes 
Similarly, codes used to describe procedures can deliberately mislead. Choosing NOS (Not Otherwise Specified) diagnostic codes makes analysis difficult. Likewise, electing a CPT code such as 99199, which is “unlisted special service, procedure, or report”, allows almost any charge to slip through without review.

Another tactic is to bill under multiple tax identifiers and from different locations. Computer systems will automatically treat these as different providers, thereby creating duplicates in the system. Performance analysis of multiples of the same provider can be misleading and their abuse completely missed. Results of analytics are skewed, as well. Provider records must be cleansed, merged, and then re-evaluated to arrive at more accurate performance scores. 

Multiple NPI’s 
Still another method used by disreputable providers is obtaining more than one NPI number (National Provider Identifier) from CMS (Centers for Medicare and Medicaid Services). Once again, the data is obfuscated and performance analysis is misleading. Combining all the data related to an individual provider for analysis is made difficult because perpetrators deliberately misrepresent themselves. 

Referral “rings” 
The data can also be analyzed to discover patterns of referral among less-principled providers and attorneys. Referral clusters in claims should be monitored. Kickbacks will not be found in the data, but questions should be raised about repeated associations. Referral clusters almost always result in litigation, claim complexity, and high cost. 

Calling a spade
Many medical providers who skirt ethical practices would be shocked to be called fraudulent. Yet, they are. Changing the name does not whitewash the behavior. 

Happy trails 
Happily, value 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. 

Quality-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 Workers’ Compensation over time. Subtleties of questionable performance can be teased out of the data.

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

How to Manage Medical Provider Networks in WC

by Karen Wolfe

David DePaolo posted a response to the CWCI’s[1] recent study of the use of networks in California and their related savings entitled “MPN Means Managed”.[2] The CWCI study compares three network formats in California since the year 2000: PPO’s 2000-2002, the transitions years from PPO’s to MPN’s, 2003-2008, and MPN”s 2009-2011.  “While the use of the networks to medically manage treatment of work-related injuries has fulfilled the legislative intent to encourage network use, over time the MPN’s have not lowered the cost of medical care.”[3]

DePaolo says medical cost savings is only part of the picture. MPN’s need to be managed because the medical impact on other aspects of claims such as disability, indemnity, return to work, and other factors is significant.


So true. But if networks mean managed—the question is how?


Networks can be managed only by evaluating and monitoring individual performance.


Network—a sum of its parts
A network is the sum of its parts, the parts being the physicians and other medical providers in the network. A network cannot be managed as a whole. Each individual medical provider acts independently and with differing results. Moreover, each provider, even within groups or facilities, acts independently. Consequently, they must be evaluated and managed individually.


Since networks began in Workers’ Comp back in the 1980’s, their rationale has been discounting services to create savings. Units of service are discounted and portrayed to payers as savings. The assumption is that all medical providers are equal and all offer equal, quality medical care. But no one checked.


Evaluating provider performance
No one checked because it was easier to claim savings through discounts than to evaluate the performance of individual medical providers in the network. Evaluating medical performance is especially tricky in Workers’ Compensation because in addition to cost and medical treatment factors there are elements unique to the industry that must be considered. Indicators of quality performance are many and varied and they can be found in the data.


Quality indicators 
Quality indicators include medical treatment indicators such as direct medical costs, prescriptions, surgery, hospitalization, and medical procedures analyzed by injury type. Non-medical performance indicators that are influenced by medical providers include return to work, indemnity costs, and legal involvement, along with ultimate outcome indicators such as claim closure and disability ratings at the close of the claim.


The way to manage networks is to Identify the best providers and monitor their performance.


Objective evaluation 
The data necessary to evaluate medical provider performance, particularly physician performance, can be found in bill review data, claims system data, pharmacy data, and the utilization review system. Unfortunately, the data resides in different silos, but by combining the data from these sources at the claim level, individual provider performance can be measured. 

Because the data reflects actual treatment and events, it is objective and quantifiable. Select quality indicators in the data, adjust for case mix, and keep them constant over time.

Swapping discounts for quality
Medical costs have increased to 60% of claim costs, calling into question the benefit of network discounts. The truth is medical providers long ago learned how to overcome the cost of discounts by increasing treatment frequency and claim duration, as well as prescribing expensive procedures, among other tactics. Discounts on more looks like more savings.


Going forward, the major hurdle in managing networks effectively is to de-emphasize discounts, while underscoring and rewarding quality performance. In order to make that financially feasible for the networks, a different approach to discounting should be entertained. For instance, those providers who rate highest in quality performance would be excused from discounts. Likewise, those performing the worst would be discounted the most.



Managing the network
To manage a network, the performance of individuals within it must be evaluated and monitored continually. No longer does it suffice to sign up providers for the network and walk away. When individual provider ratings slip, action should be taken. Moreover, let providers know they are being monitored. It has been proven that observed performance leads to behavior change.

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. MedMetrics also analyzes and scores medical provider performance. karenwolfe@medmetrics.org

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[1] California Workers’ Compensation Institute. http://www.cwci.org/research.html

[2] D. DePaolo. MPN Means Managed. DePaolo’s Work Comp World. June 10, 2015. https://www.workcompcentral.com/depaolo/index/post/1670487372170531417

[3] Ibid.