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The MedMetrics blog provides comments and insights regarding the world of Workers’ Compensation, principally, issues that are medically-related. The blog offers viewpoints regarding issues affecting the industry written by persons who have long experience in the industry. Our intent is to offer additional fabric, perspective, and hopefully, inspiration to our readers.

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Tuesday, July 29, 2014

A Trail of Abuse--Spotting Medical Fraud in Workers' Compensation

by Karen Wolfe

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

Monday, July 14, 2014

Balancing Medical Quality and Cost A Zero-Sum Game?

by Karen Wolfe

Many believe medical quality is sacrificed when attempting to control costs. The logic assumes the way to achieve quality medical care is to deliver more of it. The other side of the same reasoning is that less medical care means less quality. However, the cost-quality balance is not a zero sum game.

Zero sum games
A zero sum game means that when one element of the equation prevails, the opposite is suppressed. That would mean efforts to control medical costs by reducing the amount of medical care will result in poor medical quality. Cost control efforts such as not authorizing treatments and procedures necessarily result in poor quality.

Coexisting factors
However, these supposed opposites can, and should coexist in managing the medical portion of Workers’ Compensation claims. Quality is not counter to cost management in medical treatment. For instance, managing the number of visits or encounters, prescriptions, and the number of specialists the claimant encounters are just a few ways to limit medical services that may, in fact, improve quality.

Visits and services
On the one hand, the treating doctor should see the injured worker often enough to understand, direct, and maintain control over the recovery process. Yet, some physicians embellish their revenue flow by seeing patients more frequently than necessary. To manage excessive utilization of office visits and services, evaluate the data to learn what is reasonable and what is disproportionate. To be effective, the data must be monitored concurrently so that intervention has an impact.

Analyze the data
The way to objectively measure excessive visits is to monitor and analyze the data. For specific injuries in a given jurisdiction, what is the mean number of medical visits? Outliers can be interpreted to mean either the treating physician is fraudulent or the claimant is in trouble. Either way, focused attention to the matter is needed.

Standards and legislation
A claims payment organization can set standards for what should be considered the threshold of excessive for given conditions. Beyond that point, the claim is examined and intervention initiated. Some states legislate frequency of care.

The state of California, for instance, has placed limits on the number of physical therapy and chiropractor visits. The data system can mobilize notification to the appropriate persons when the benchmark is approaching so that limits are not exceeded. Applying similar methods to a variety of medical visits and services adjusted by diagnosis and other factors such as age and comorbidity will similarly impact costs while sustaining quality.

Another example of balancing quality and cost is controlling frequency or volume of services by electronically monitoring prescription practices, especially those for Schedule II or Opioid drugs. The literature is replete with examples of ineffective and poor outcomes when Opioids are over-used. By monitoring current data, usage and cost can be checked through appropriate intervention.

Yet another indicator found in the data reflecting excessive medical treatment is multiple medical referrals. Too often when the patient is not improving, the doctor’s response is to refer to specialists. The data gives up that information by noting the number of medical providers and specialists involved in a claim. Assuredly, a claim with multiple specialists is a claim in trouble, or at least progressing poorly, needing attention.

Industry research speaks for itself. Consider this Washington state study, “Long-term Outcomes of Lumbar Fusion Among Workers Compensation Subjects: An Historical Cohort Study”[1] This study concluded, “Lumbar fusion for disc degeneration, disc herniation, and/or radiculopathy in a workers comp setting is associated with significant increase in disability, opiate use, prolonged work loss, and poor RTW status.”

Intervene early
Monitor the data to discover outliers early so that interventions will effectively impact outcomes. The key to supporting quality while impacting cost is identifying potential problems early. The longer an issue persists, the more challenging it is to correct it.

Balancing quality and cost
Consider both medical quality and cost control equal goals. They are not mutually exclusive nor is it a zero-sum game. The medical profession itself is recognizing and addressing the issues of over-prescribing, over-testing, and over-treatment. Medical managers need to assist in the process.

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