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How to Help Reverse the Opioid Epidemic

Across the U.S., the number of reported events exemplifying the opioid and heroin epidemics continues to skyrocket. U.S. Government Publishing Office data shows that the usage of both prescribed stimulants and prescribed opiates increased by a factor of 19 in just two decades since 1994(1). On Dec. 18, 2015, the U.S. Centers for Disease Control and Prevention (CDC) released a report showing drug overdose deaths reached record highs in 2014, fueled in large part by the abuse of narcotic painkillers and heroin. In 2014, more than 47,000 Americans died from drug overdoses, an increase of more than 14% from 2013. About 61% of those deaths involved the use of opioids. From 2000 to 2014, the report noted that nearly half a million people have died from overdoses in the U.S. In 2014, there were approximately one and a half times more drug overdose deaths than deaths from motor vehicle crashes!(2)

A very worrisome statistic and trend…

For workers’ compensation insurers, opioid use in treating chronic pain has also exploded over the past two decades. Although there appear to be some signs that opioid use is finally cresting, insurers still have a long way to go in helping to ensure that physicians and the injured workers they treat are fully educated on the pros and cons of using opioids with various types of injuries and pain. As the Risk & Insurance article “Paying for Detox – The Opioid Epidemic Is Addressed by Detoxification Programs” notes, some workers’ compensation insurers have been funding tapering and detoxification programs to help dependent or addicted patients wean themselves off the very medications that were designed to ease their pain(3). Unfortunately, recidivism is common, with experts noting that it can take several attempts to wean someone off narcotics.

This article will highlight some of the challenges in front of us and share some innovative ideas on potential ways to help prevent opioid dependency and addiction before the habits requiring tapering and detoxification programs are ever formed.

The Challenge in Front of Us

In January 2011, USA Today shared a powerful story about David Fridovich, a three-star Green Beret general who has become an advocate for warning soldiers about the epidemic of chronic pain and the use of narcotic pain relievers sweeping through the U.S. military(4). Much like others across the country who have suffered a severe back injury, the general began taking narcotics for chronic pain in 2006. Over time, the general became addicted to narcotics. During one 24-hour period the general took five dozen pain pills. After going through a detoxification program, the general has been helping other soldiers avoid the complications he faced because he was unaware of the addictive nature of the pills he was taking.

In a recent book about the opioid and heroin epidemic in the U.S., Dream Land author Sam Quinones shares his research on the history of how we ended up where we are today. From a workers’ compensation perspective, the author shared a story about a prison guard who had injured his back during a fight with an inmate. The doctor, who took the guard off of work for six months, also prescribed opioids to be taken twice a day for 30 days. After becoming severely addicted, the guard said, “It really humbles you. You think you’re doing stuff the way it’s supposed to be done. You’re trusting the doctor. After a while, you realize this isn’t right, but there really isn’t anything you can do about it. You’re stuck. You’re addicted.”

Both stories illustrate how the use of painkillers can lead to dependency and addiction without warning. They also highlight the critical role prescribing physicians play in educating patients about the warning signs and addictive nature of opioid prescriptions. As part of this education process, prescribing guidelines and analytics can play an important role in driving better outcomes.

Opioid Prescribing Guidelines

For workers’ compensation insurers, it is critical to understand the opioid prescribing guidelines that underlie the way physicians are treating injured workers. The more the insurers can help educate physicians on best practices, the better off insurance companies may be in helping to prevent any issues that may arise because of unnecessary or excessive opioid prescribing.

The CDC worked with the National Drug Institute, Substance Abuse and Mental Health Services Administration and the Office of the National Coordinator for Health Information Technology to review existing opioid prescribing guidelines for chronic pain. Their review and analysis of eight prescribing guidelines highlighted a number of important provider actions, such as the review of pain history, medical and family history, pregnancy, prescription drug monitoring programs (PDMP), urine drug screening, evaluations of alternatives to opioids, rational documentation, tapering plans, referrals for medication assisted treatment, evidence review, conflicts of interest and more(5). In January, Kentucky Attorney General Andy Beshear announced his support for national guidelines for prescribing opiates for chronic pain, stating: “In Kentucky, we face a crushing epidemic of addiction. One of my core missions as attorney general is to better address the drug problem faced by our Kentucky families and workforce.”(6) In his speech, the attorney general mentions that he is joining other state attorneys general in voicing support for the CDC guidelines for prescribing opiates for chronic pain.

California’s “Division of Workers’ Compensation Guideline for the Use of Opioids to Treat Work-Related Injuries” documented treatment protocols for three specific pain categories:

  1. Opioids for acute pain (pain lasting as much as four weeks from onset)
  2. Opioids for subacute pain (one to three months)
  3. Opioids for chronic pain and chronic opioid treatment (three months or more)(7)

The guidelines state that, in general, opioids are not indicated for mild injuries such as acute strains, sprains, tendinitis, myofascial pain and repetitive strain injuries. Just as important, the guidelines clearly warn physicians to consider and document relative contraindications (e.g., depression, anxiety, past substance abuse, etc.). The document provides an abbreviated treatment protocol for the three pain categories that address important topics like prescribing a limited supply of opioids, documentation, accessing California’s PDMP, monitoring opioid use, evaluating the use of non-opioid treatments, completing opioid use, educating patients on opioid usage and potential adverse effects, responsibly storing and disposing of opioids, tracking pain level, screening for the risk of addiction, testing urine for drugs and more.

At the end of the day, it is important for workers’ compensation insurers and physician employees to clearly understand the opioid prescribing guidelines that help physicians achieve a proper balance between treating workers’ pain and keeping them safe from any adverse impacts of excessive opioid usage. With more insurance companies leveraging early physician peer-to-peer outreach to open a dialogue between the insurance company physician and the treating physician, knowing prescribing guidelines and sharing that knowledge will be more important than ever in improving outcomes and return to work.

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The Inspiration for Using Analytics

For more than a decade, Deloitte Consulting’s Advanced Analytics & Modeling practice has been developing claim predictive solutions designed to help insurance companies, self-insureds and third-party administrators better segment and triage predicted high-severity from low-severity claims, enabling business decisions and actions that can help drive loss cost savings of as much as 10% of an organization’s annual claims spending. (See Claims Magazine articles “Analytics on the Cloud: Transforming the Way Claims Leverages Advanced Analytics “(2011)(8), “Enhancing Workers’ Comp Predictive Modeling With Injury Groupings” (2012)(9), “Reaping the Financial Rewards of End-to-End Claims Analytics” (2014)(10) and “The Challenges of Implementing Advanced Analytics “(2014).(11) A large part of the claims modeling success is attributed to gaining actionable insights as early as first notice of loss before adverse chain reactions can set in, and shortly thereafter with the three-point contact investigation where additional information is learned about the patient’s history and co-morbidities.

The authors, having observed the success of predicting claims complexity outcomes early in the claim’s lifecycle, became excited about the application of similar models to help identify early warning signs of future excessive opioid usage by injured workers. With as much as 60% of workers’ compensation spending going toward medical costs, one-fifth of that related to prescription drugs(12), we believed the use of predictive models… combined with physician peer-to-peer outreach and proper prescribing guidelines… could help workers’ compensation insurers improve the lives of the injured workers while significantly reducing medical expenditures. The following sections explain the analytics journey undertaken to help move the needle on this issue.

Defining the Target Variable: Predicting Future Excess

An important part of any analytics journey is defining the target variable (i.e., what we are trying to understand and predict). Excessive opiates usage is difficult to ascertain, as higher consumption may indeed be necessary for the most severe injuries. Therefore, various tests on the most appropriate target variables were conducted to probe these hypotheses. Many versions of opioid supply days were tested (i.e., ultimate total supply days across all opiates drugs prescribed to, and consumed by, the injured worker). Variations of opiates prescription counts were also considered (i.e., ultimate count of opiates prescriptions through the lifecycle of the claims). Similarly, supply units were analyzed (i.e., ultimate sum of all individual opiates pills prescribed to, and consumed by, the injured worker from the day of the injury until the claim closure). Figure 1 illustrates the calculation of total supply days for three different opiates that were prescribed to, and consumed by, the injured worker over the duration of his workers’ compensation claim:

fig1

Figure 1. Supply Day Illustration

Methodology and Data Considered

Using predictive analytics and data science, a number of algorithms were built, tested, iterated and fine-tuned to better understand those like-injury cohorts (i.e., same injury sustained) that consumed more opiates than their corresponding peers who managed to consume a lower amount. Various thresholds of “excess” were analyzed by injury and venues, thus controlling for differences that affect the prescription base.

By testing these algorithms, it was determined that segmentation was similar across the different target variables. However, total supply days seemed to exhibit the most robustness from a modeling perspective and had intuitive interpretability (i.e., number of days an injured worker consumes opioids).

The algorithms used more than eight years of lost time workers’ compensation claims to accumulate enough data credibility. Claims were selected for various injury groups where opiates were prescribed and consumed for at least one prescription. The data was organized for a longitudinal study observing a claimant over time and quantifying her consumption of opiates. The comparison to this usage to like-injury counterparts over thousands of cases and using hundreds of attributes is what helped the model shed light on claimants who consumed excessive amounts of opioids relative to the entire population.

Over the years, Deloitte healthcare practitioners and claims professionals used ICD-9 codes that describe a disease or condition, as well as National Council on Compensation (NCCI) nature of injury and body part codes, to create more than 70 proprietary injury groups that are factored into the model to provide enhanced segmentation within like injury claims.(13) For illustration purposes in this article, we presented results for the injury group representing medium- and high-complexity spinal disorders (e.g., ICD-9 codes 722.0 – displacement of cervical intervertebral disc without myelopathy, 722.10 – displacement of lumbar intervertebral disc without myelopathy, 724.9 – other unspecified back disorders, etc.). We selected medium- and high-complexity spinal disorder claims because they are significantly more severe than the average workers’ compensation claim, and, as expected, these claimants typically have more prescriptions filled by their physicians. In addition, the models aren’t run on just any injury group. For example, an injury group containing low-complexity injuries such as finger cuts and minor open wounds would not be part of our analysis. Claimants with these types of low-complexity injuries do not require opioids, given the nature of injury, so it would not make sense to include these injury groups in the model.

Predictive variables

The information attributes used to understand excessive consumption were sourced from similar data sources used in developing our claim-severity models. They are large in number and varied in terms of coverage. They include claimant data (e.g., claimant age, gender, job classification, years of employment, wage, claim filing lag, cause and nature of injury, etc.), prior claims data (e.g., prior frequency and type of claims), employer information (e.g., financial characteristics, years in business, etc.), injury circumstance (e.g. location, type, body part injured), three-point contact information (e.g., co-morbidities, early medical services) as well as other standard external third-party data sources (e.g. lifestyle, behavioral, geo-demographic).

Modeling Results

The lift curves shown in Figure 2 illustrate the segmentation achieved by using multivariate equations to predict total supply days. Each claim below was scored using the model, which generated scores from 1 to 100, with lower scores corresponding to smaller predicted supply days and higher scores corresponding to larger predicted supply days. This score is represented on the x-axis of Figure 2, where each “decile” refers to a group of claims that compose 10% of the data. The actual supply days are tracked and plotted on the y-axis in the appropriate decile.

fig2
Figure 2. Lift Curve – GLM model

As one can see from Figure 2, injured workers studied who are predicted to fall in decile 10 have more than 18 times the supply days as workers predicted to fall in decile 1. Injured workers studied who scored in decile 10 consume, on average, more than three and a half years of opioid supply days! This very large and widespread segmentation suggests that individuals sustaining the same injury can still vary significantly in their future consumption of opioids… and this variation ranges from a couple months to more than three and a half years.

In Figure 3, we compare two 24-year-old male claimants with very similar injuries but drastically different predicted outcomes.

fig3
Figure 3. Similar Injuries, Drastically Different Outcomes

As one can see from Figure 3, the claimant scoring in decile 10 has a number of variables that correlate with the potential for excessive opioid use. Given the combination of co-morbidities, worker health, reporting lags, employer business conditions and additional attributes collected on the individual from external sources (e.g. lifestyle and behavioral data), it is possible for the insurance company to identify and analyze the early drivers that may lead to future excessive opioid the first few days after receiving notice of the claim.

With more than 60 predictive variables in the model (e.g., co-morbidities, prior claims history, job classes, injury causes, business characteristics, claim characteristics, etc.), the most influential categories and reason codes driving the score represent “eyeglasses” for the insurance company physician. The model helps the insurance company physician weigh together multiple pieces of information but doesn’t replace his judgement. Analogously, many of us wear eyeglasses to read a dinner menu, but those eyeglasses do not order the food for us.

Armed with a plethora of facts and the opioid prescribing guidelines, a physician can open a dialogue with the treating physician to help guide the discussion in a direction that best benefits the injured worker. The physician, using the prediction from the model, can tailor appropriate decisions and actions – from low touch or regular prognosis for the first claimant above, to a much more closely managed case for the second individual.

Figure 4 provides a drill-down into the actual versus predicted supply days achieved in the highest-scoring 30% of medium- to high-complexity spinal disorder claims for the train/test data and validation data. Using the train/test/validation approach, the models were trained and enhanced using approximately 70% of the claims data. The validation results shown below were derived from the remaining 30% of the claims data that was held in “cold storage.” Using this kind of blind-test validation data helps ensure that the model’s estimated “lift” (i.e., segmentation power) is true and unbiased.

fig4
Figure 4. Highest Score Drill-Down

Approximately 60% of claims scoring in deciles 8, 9 and 10 exceed one year in supply days. For a quarter of the claims, the injured workers take in excess of four years in supply days of opioids. At the far end of the spectrum, roughly 4% of medium- to high-complexity spinal disorder claims scoring in deciles 8, 9 and 10 will exceed a decade’s worth of opioids in supply days.

One Last Check

In addition to the generalized linear models (GLMs) discussed above, focused on predicting the actual supply days, we also ran a logistic regression model focused on predicting which claimants would take more than a year’s supply of opioids. Using classical statistical measures of precision (i.e., how many of the positively classified results are relevant), recall (i.e., how accurate the model is at detecting the positives) and specificity (i.e., how good the model is at avoiding false alarms), we achieved the following results: a precision of 59%, a recall of 64% and a specificity of 72%.(14) As one last test of the logistic regression model’s segmentation power, we calculated the receiver operating characteristic (ROC) curve.  At almost 80%, it represented a good model from a statistical perspective. Although illustrative, we prefer the GLM model presented above.

Behavioral Economics and Nudges

All across the country, physicians and medical boards are spreading the word about the responsible prescribing of opioids. State and federal agencies are toughening criminal and administrative penalties for doctors and clinics that traffic in prescription drugs. Governors across the country are forming opioid working groups that include senior Health and Human Services professionals, attorneys general, drug courts, hospital professionals, elected officials and more.

Research shows that a number of factors can help insurance companies better understand the severity of claims early on in the life cycle of a claim. Two studies by the National Council on Compensation Insurance, Inc. (NCCI) highlight the effect of obesity on workers’ compensation claims. According to “Reserving in the Age of Obesity,” a Nov. 1, 2010, NCCI study by Chris Laws and Frank Schmid, the ratio in the medical costs per claim of obese to nonobese claimants deteriorates over time from a ratio of 2.8 at the end of one year, to 4.5 at the end of three years, to 5.3 at the end of five years.(15) In a following study from May 29, 2012, “Indemnity Benefit Duration and Obesity,” authors Frank Schmid, Chris Laws and Mathew Montero found the duration of obese claimants is more than five times the duration of nonobese claimants, after controlling for primary International Classification of Diseases (ICD)-9 code, injury year, state, industry, gender and age for temporary total and permanent total indemnity benefit payments.(16) Deloitte’s claim predictive models have shown that the number of medical conditions at the time of injury plays a significant role in determining the ultimate severity and potential for excess opioid usage (e.g., claims with three or more existing medical conditions are 12 times more costly than claims with no existing medical conditions).

With energy and momentum building around addressing the opioid epidemic, insurance companies can leverage behavioral economics and data-driven nudges to help treating physicians improve outcomes and return to work. Leveraging prescribing guidelines and the model results and reason codes that help explain the top five drivers behind the model prediction, insurance company physicians can be more strategic in shaping the discussions they have with treating physicians. For the highest-scoring claims, the insurance company may want to use a mix of peer-to-peer contact and data-driven nudges (e.g., “did you know that 95% of physicians we work with follow the state prescribing guidelines and only prescribe 30 days of opioids for this type of claim,” ”for injuries of this type, physicians we work with usually prescribe less than x milligrams of strength,” etc.). For lower-scoring claims, the insurance company may touch base with the treating physician but skip any reference to data-driven nudges.

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Conclusion

In the end, it is important for workers’ compensation insurers and their medical professionals to clearly understand opioid prescribing guidelines and the internal and external factors that could affect the opioid usage and habits of their injured workers. A Business Insurance white paper titled “Opioid Abuse and Workers’ Comp – How to Tackle a Growing Problem,” described the challenge well: “Monitoring or managing opioid abuse is another key step for workers’ comp managers. It’s not enough to simply dive into the data and look for claimants who appear to be using lots of opioids. Nor is preventing doctors from prescribing opioids a desirable action. The goal is to find claimants who are struggling with a problem they never intended to have, and support those claimants in solving that problem.”(17)

However, our hope is that through the use of predictive analytics (i.e., the ability to identify, in the first few days of receiving a claim, individuals most likely to become high consumers of opioids), prescribing guidelines and physician peer-to-peer outreach, we can help increase insurers’ and treating physicians’ awareness as they work to help prevent injured workers from struggling with dependency and addiction before the behaviors or habits ever form.

As former British Prime Minister Benjamin Disraeli once said, “What we anticipate seldom occurs; what we least expect generally happens.” The science and passion exists today to better anticipate opioid trends and help prevent opioid dependency and addiction before it happens.

As used in this document, “Deloitte” means Deloitte Consulting LLP, a subsidiary of Deloitte LLP. Please see www.deloitte.com/us/about for a detailed description of the legal structure of Deloitte LLP and its subsidiaries. Certain services may not be available to attest clients under the rules and regulations of public accounting.

This communication contains general information only, and none of Deloitte Touche Tohmatsu Limited, its member firms, or their related entities (collectively, the “Deloitte Network”) is, by means of this communication, rendering professional advice or services. Before making any decision or taking any action that may affect your finances or your business, you should consult a qualified professional adviser. No entity in the Deloitte Network shall be responsible for any loss whatsoever sustained by any person who relies on this communication.

Copyright © 2016 Deloitte Development LLC. All rights reserved.

[1] James W. Harris, PhD, CSO Vatex Explorations LLC, www.gpo.gov

[2] http://www.cdc.gov/media/releases/2015/p1218-drug-overdose.html, http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6450a3.htm?s_cid=mm6450a3_w

[3] http://www.riskandinsurance.com/paying-detox/

[4] http://usatoday30.usatoday.com/news/military/2011-01-27-1Adruggeneral27_CV_N.htm

[5] http://www.cdc.gov/drugoverdose/prescribing/common-elements.html

[6] http://harlandaily.com/news/6473/cdc-guidelines-will-help-ky-with-rx-drug-abuse

[7] http://www.dir.ca.gov/dwc/ForumDocs/Opioids/OpioidGuidelinesPartA.pdf

[8] http://www.propertycasualty360.com/2011/02/22/leveraging-analytics-in-workers-comp-claims-handli

[9] http://www.propertycasualty360.com/2012/07/23/enhance-workers-comp-predictive-modeling-with-inju

[10] http://www.propertycasualty360.com/2014/02/03/reaping-the-financial-rewards-of-end-to-end-claims

[11] http://www.propertycasualty360.com/2014/10/01/the-challenges-of-implementing-advanced-analytics

[12] www.ncci.com

[13] http://www.propertycasualty360.com/2012/07/23/enhance-workers-comp-predictive-modeling-with-inju

[14] Precision measures the ratio of true predicted positives to the ratio of true predictive positives plus false predicted positives. Recall, also referred to as sensitivity, measures the ratio of true predicted positives to the ratio of true predicted positives plus false predicted negatives. Specificity measures the ratio of true predicted negatives to the ratio of true predicted negatives plus false predicted positives.

[15] https://www.ncci.com/Articles/Documents//II_research-age-of-obesity.pdf

[16] https://www.ncci.com/Articles/Documents/II_Obesity-2012.pdf

[17] http://www.businessinsurance.com/article/99999999/WP05/120509952

14 ICD-10 Codes That Defy Belief

For every medical diagnosis, disease, injury, symptom, complaint and procedure, healthcare professionals use a specific code to maintain consistent outcomes, data assessment and billing. These codes, formerly called the ICD-9, are a set of characters and numbers that have experienced a series of revisions since they were first put into place. As of Oct. 1, 2015, the ICD-10 (International Classification of Diseases, Revision 10) is in effect.

With such a wide range of known diseases, ailments, symptoms and more, ICD-10 codes can get a little wacky. The infographic below illustrates 14 of the most unusual codes that illustrate the totally bizarre ways in which people manage to injure themselves. From an ice skater’s initial collision with a stationary object to computer keyboarding injuries, the ICD-10 codes don’t miss a trick.

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Electrodiagnostics: a More Powerful FCE?

My recent post on functional capacity exams (FCEs) is a great lead-in to considering another level of related technology. Let’s explore electrodiagnostics as arguably a more powerful arrival in functional exams.

First, let’s recap what quality means in a functional capacity exam: An FCE requires a process that is objective and consistent with the proper balance between specificity to body parts and sensitivity to critical indicators, including pain, range of motion and strength. An FCE must indicate illegitimate effort and attempts to “game” the test by subjects.

I submit to you that, the more a functional exam process can move away from human-tester interventions and totally separate testing steps, the closer it gets to nirvana. This construct is the essence of electrodiagnostics.

A routine FCE process involves various separate tests, including nerve conduction, range of motion and strength. Even with the most advanced equipment, this presents separate processes to assess for validity and to try and formulate into a whole-body issue. What if one test did all of this at once?

Contemplate the electrodiagnostic functional assessment (EFA), where a test subject performs a single test sequence on specialized EFA equipment that measures multiple factors. This provides instant objective credibility. Stated simply, combined factors of muscle strength, pain and range of motion and others need to align in a logical pattern as depicted by computerized readout, or the subject is immediately shown as self-limiting his capability.

The EFA is arguably more accurate than the common FCE in assessing work capacity. EFA has also been proven useful in more specific applications, such as determining the need for hardware removal in post-surgical cases with alleged recurring pain problems.

Consider further that, because the EFA is such a consistent test, it is highly credible as a comparison to prior baseline. The EFA used as a base-line test at time of hire can be saved as a data file without opening until an employee might have an alleged injury at some later period. At such occasion, a new EFA can be performed to compare with the baseline to see what, if any, alleged changes in capacity and pain threshold have occurred. This definitive comparison has held up in court cases, making the EFA evidence as worthy as an MRI would be in comparing pre- and post-injury pictures of a joint or body part.

Quick Tip: Learn More About EFA and the Possible Application to Your WC Claims

– Google “electrodiagnostic functional assessment” to review white papers and scholarly details around the EFA and its applications and case studies.

– For more information, search out Emerge Diagnostics, which has pioneered the application of EFA and which is making efforts to bring EFA to the forefront of medical and legal use. I do not promote specific vendors in “Quick Tips,” and this article is for informative purposes only. However, the EFA is currently a sole-source situation, and reviewing the studies and successes of Emerge Diagnostics is of educational benefit.

– If you want to be cutting edge, do a trial. Pick a WC case or two that is stalled without adequate determination of disability, causation, apportionment or need for surgery, etc. Work to get an EFA entered as evidence and see if the case can turn.

– If you do try EFA, let me know your results. I would like to continue related reporting on this and see how much future influence EFA might have on the larger WC landscape.

IME: Success or Fishing Expedition?

Independent medical exams (IMEs) are widely used throughout the workers’ compensation insurance industry. However, as with any tool, you generally need a good carpenter or mechanic to get the best results. Because of the time required to arrange these medicolegal exams and because of the complexities of determining causation, pre-existing conditions, degree of impairment, etc., most insurance companies and third-party administrators (TPAs) outsource this function, which generates findings that can be used in the formal claims adjudication process.

The problem with outsourcing IMEs is that it typically removes from the process the only stakeholder who actually knows the injured worker: the employer.

The employer can make better decisions about whether to request IMEs — which are very expensive — by looking for red flags that, in many cases, only the employer could know about.

The most basic reason is if there is a legitimate question as to whether an injury or illness was caused by a work-related accident or industrial exposure. Red flags that might indicate the need for an IME include: The accident/injury wasn’t witnessed by other employees; reports of how the injury occurred are vague; or the injury was not promptly reported. Other triggers that only the employer would know include: a history of disciplinary, attendance or other HR issues; prior work history and the possibility that the employee is working a second job; or participation in sporting and recreational activities outside the workplace.

Other flags could be: Healthcare providers indicate that the employee may not be able to return to work, based on subjective complaints, or have proposed treating plans that are open-ended, with no clear-cut goals.

Other key issues that should be identified early in the claims process are: pre-existing conditions; any unauthorized medical treatment; any treatment by known “provider mills”; all litigated or potentially litigated claims; any potential subrogation opportunities; any doctor shopping; prescriptions for opioids; recommendations for elective surgery, such as on the back or for carpal tunnel issues; and any plain, old-fashioned tips from other employees.

IME providers often miss three fundamental questions: Can this injury or illness be caused by the workplace? Under what circumstances? Did these circumstances exist in this case?

Medical providers performing IMEs often make decisions in a vacuum, with little, if any, input from the employer. Leading medical experts who routinely perform IMEs state they are often “flying blind” and would have conducted a whole different physical exam or diagnostic testing if they only had more information. They tell me that they often have no idea why an IME has been scheduled. Miscommunication is common, and prior medical reports are often delayed or even lost.

IMEs should be conducted within a well-planned strategy at both the local level and the corporate level, between an employer and its insurer or TPA. The success or failure depends on active involvement and strong communications by all involved, including employers, IME providers, injured workers and insurance carriers and claims administrators.

As noted in previous articles, employers may consider using an OSHA-sanctioned “contemporaneous” medical exam – conducted at the moment of injury/illness notification but done outside the workers’ compensation system. Employers may consider this approach when they suspect a difficult or potentially litigated claim in states where they have little control over the choice of medical provider or face other jurisdictional or claim-specific challenges.

Employers, whether they are fully insured or self-insured, should ask detailed questions about how IMEs are handled on their behalf. Most insurers and TPAs outsource some, if not all, of the process of scheduling and arranging IMEs. There are dozens of questions I would ask about IME panel selection and quality assurance, including; credentialing, board certification, training, continuous education, experience, expertise, reputation, affiliation with university-based teaching hospitals or sports teams, along with knowledge and utilization of AMA impairment guidelines, evidence-based treatment protocols and application of disability guidelines from state workers’ comp, the Americans with Disabilities Act  (ADA) and others.

The only true stakeholder in what can be a very expensive, time-consuming and frustrating process to obtain quality IMEs is the employer. It is the employer that should be asking about “other” workers’ compensation costs and whether IMEs, which often include “hidden” costs, are actually having a positive outcome in successfully denying, closing or settling difficult and contentious workers compensation claims.

The 80/20 rules applies in both workers’ compensation and healthcare — 20% of claims will generate 80% of the costs. Employers need to have strategies in place both early and often to help confirm the relationship between reported injuries and illnesses and the workplace.

The employer’s ability to obtain credible and authoritative medical opinions is key to containing workers’ compensation costs from medical, indemnity (lost-wage replacement), permanent disability awards and administrative, legal and other fees.

Employers need to take a much more active role in ensuring high-quality healthcare while addressing waste, fraud and abuse in the system. Employers should avoid fishing expeditions but rather use these expensive tools wisely and put them in expert hands. If you are going fishing, make sure you have the right bait, deck hand and captain.

IMEs can be a great tool or waste of time and money. It’s more up to you than you think.

Is Baseline Testing Worth It? (Part 2)

In our first article on this subject, we gave an overview of baseline testing, compared it with a post-offer physical exam, updated recent legal decisions under the Americans With Disabilities Act (ADA) that allow baseline testing and concluded with a legal case highlighting the benefits of a baseline program. While all stakeholders won in the case we cited, we all need to remember that the focus in workers’ comp needs to be the injured worker.

That isn’t always the case, as recent court rulings have shown. Last week, a Pottawatomie County judge in Oklahoma issued a ruling that may erode the exclusive remedy provision for workers’ compensation (Duck vs Morgan Tire). This ruling comes after Miami-Dade District Judge Jorge Cueto ruled in August that the exclusive-remedy provision of the state’s comp statute was unconstitutional. Both cases make a strong case that the rights of injured workers have been deteriorating and that workers no longer have enough protection. (The cases are under appeal.)

The workers’ compensation system is overburdened with red tape: In some states, there are onerous mandates for doctors, delays in legal proceedings, disputes over acceptance of cases…and on and on. An injured person is caught in the middle. Frequently, necessary care is delayed — which often results in even greater damage and costs. Carriers and employers are frustrated, too. With increasing federal mandates complicating this already tangled system, they feel they are being asked to accept claims that “aren’t ours.” They worry about liability and uncontrolled costs, even while knowing that delaying appropriate care can lead to prolonged disability, inefficient medical care and higher costs.

So the question remains: How do we do the best for the injured worker while protecting ourselves?

This article focuses on the heart of the matter: Better diagnosis leads to better patient care. Peel away the layers of comp laws and reforms, and this is what the industry should be about.

Baseline testing helps identify a change in condition, so the person can get the best care possible for work-related injuries. Does this actually happen? Does baseline testing work with soft-tissue injuries, specifically those that appear to be based on subjective complaints, with typically little or no objective findings? (Soft-tissue injuries, although often unsupported by clear and convincing evidence, are the leading drivers of cost in the system.)

Here is a case that shows that it’s possible to use baseline testing to avoid over-treating or under-treating and to do the right thing:

Mr. Jones works for the same employer as was mentioned in Part 1 of this article. He is 34 years old and is employed as truck driver. He underwent a baseline test in June 2014 and was injured at work in September 2014. He was driving his truck when he hit a bump. He was wearing a seat belt but hit his head. He continued to work. He later felt diffuse neck pain and reported the incident.

The following day, he saw a doctor, who couldn’t issue a diagnosis. Mr. Jones had a history of chronic neck pain, so the doctor couldn’t tell if anything was “new.” He thought the pain would go away, but it persisted.

Because Mr. Jones had undergone a baseline evaluation, he was sent for the post-incident, electrodiagnostic functional assessment (EFA). The comparison of the two evaluations revealed a change in condition. The testing indicated he could have an industrially related left cervical radiculopathy. Treatment was redirected to this area, and he received the appropriate care on an expedited basis.

This is a person who had diffuse pathology and a substantial pre-existing condition. As a result, his workman’s comp carrier delayed care, and he pursued treatment by his chiropractor on a non-industrial basis. He was off work, not receiving benefits, while waiting for the causation of his injury to be determined. He potentially could have gotten lost in the system with unresolved treatment and escalating bills while without benefits and out of work.

The employer truly wants the best care for its injured workers and, as soon as the comparison demonstrated a change, ensured that he received all the appropriate care and benefits for his work-related injury.

We truly believe that everyone in this workers’ compensation system wants to do the “right thing” but that is hard to do without objective evidence. Accurate diagnoses lead to better patient care, which is the very basis of workers’ compensation. So is baseline testing really worth the effort? You bet it is!