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How Fort Worth Drove Down WC Costs…

The biggest myth in healthcare is that better care costs more. The city of Fort Worth, Texas busted that myth. Using advanced analytics to establish and monitor a provider network, the city got its injured employees better care while driving its workers’ compensation costs down, not up.

In 2015, Fort Worth had 6,250 employees, and its total workers’ compensation costs ‒ claims plus indemnity payments ‒ were $9.7 million. After implementing the provider network, the city’s costs in 2016 fell to $9.1 million, and they’ve fallen every year since. In 2019, the costs were only $8.2 million, despite the city’s number of employees increasing to 6,900.


How did Fort Worth do it? The city created a physician panel under Chapter 504 of the Texas Labor Code that would be available to its employees only. To identify the providers to include, the city applied the outcome algorithms described below to two juxtaposed data sets and found the providers achieving the best outcomes for each injury type ‒ who cost the city less, not more.

Healthcare is not a commodity. We all think that our doctor is the best ‒ or at least above average ‒ but we don’t live in Lake Wobegon, where all the children are above average. Exactly half of all children are above average, and exactly half are below. It’s the same with doctors ‒ and the specialists and surgeons that they refer us to, and the hospitals that they put us in.

Although counter-intuitive, going to a good doctor costs less overall than going to a bad one. 30% of healthcare costs are unnecessary, the result of poor or ineffective care. Good doctors don’t incur those excess costs because they:

  • Make fewer errors;
  • Perform fewer unnecessary procedures;
  • Experience fewer patient complications; and
  • Get their patients better faster.

So how can you do what Fort Worth did? First, you need access to the two data sets on which to run the analytics ‒ your medical and pharmacy claims and your employee absence records. If you’ve self-insured your workers’ compensation program, like Fort Worth does, then you own the medical and pharmacy claims. You still engage a third party administrator (TPA) to process those claims for you, but you are at actuarial risk for them, and therefore you own the claims. If, on the other hand, you’re fully insured ‒ you pay the insurance company a premium, and the insurance company bears the risk ‒ then you won’t own the claims and won’t be able to perform these analytics, although your insurance company could.

If you have the claims, then you match them against the absence records to identify the time that the employee missed from work because of the injury. You can do so in two ways. First, juxtapose the claim dates against your Human Resources (HR) Department’s time and attendance records to find the days missed because of the injury and value that time off at the employee’s pay rate or a normalized rate. Alternatively, you can use the indemnity payments to the employee as a proxy for the absence costs. When a TPA or insurance company uses these analytics, this is the route that they take because they don’t have access to the employer’s HR records.

Next, you must be able to direct care ‒ tell the employee which provider to go to. Every state has its own rules. In Texas, an employer can do so. This can include establishing referral protocols and criteria for medical procedures that don’t require pre-authorization ‒ decreasing the wait times to obtain care and thereby driving down lost days and indemnity payments.

If you meet these three criteria ‒ you own the claims, can direct care and have absence data ‒ read on and learn how you, too, can drive down your workers’ compensation costs while improving the care for your injured employees.

Quantifying Outcomes

We begin with the premise that a “good outcome” is getting an employee back to work and keeping them there. We therefore accumulate all the costs to do so and then rank the providers based on the outcomes that they achieve.

See also: 7 ‘Laws of Zero’ Will Shape Future

First, let’s look at the claims. The chart below shows the average claims costs for 14 specialists treating back injuries. Specialist #1 on the far left is the best, with average claims costs of $1,000, while Specialist #14 on the far right is the worst, at $8,600.

The claims, however, are only half of it ‒ sometimes less than half. You have to add the absence costs, the amounts that the employer paid the employee while out with their injury. Not only are these absence costs a real cost to the employer, but they double as an indication of the effectiveness of the care. The quicker the doctor got the employee better and back to work, the more effective the doctor was. This chart adds each specialist’s average absence costs on top of their claims.

Now Specialist #2 goes from being second best to second worst; and Specialist #9 is doing a better job than we originally thought because that doctor is getting their patients better and back to work faster.

There’s one more step. If you ask any doctor why their costs are more than another doctor’s, they’ll always give the same answer: “Because my patients are sicker.” And sometimes they’re right.

Sicker patients cost more and take longer to get better. If you have two employees with the same back injury, one of them young and otherwise healthy, while the other is older, overweight and diabetic, the older employee is going to cost more. So we adjust for comorbidities by assigning each employee a risk score. That way our rankings are based solely on the provider performances, not the patients that they treated.

There are a number of risk-scoring systems. One that is open-source is the Chronic Illness and Disability Payment System (CDPS). CDPS was designed by the University of California, San Diego and is employed by many Medicaid programs around the country. Accordingly, it is demographically appropriate for a working age population.

The CDPS system looks at various demographic and clinical data, including age, gender, diagnoses and the prescription drugs that a patient is taking and assigns the patient a score: 1.00 being an individual of average health, below 1.00 healthier than normal (the lower the score, the healthier) and above 1.00 sicker (the higher the score, the sicker).

The chart below shows the relationship between an employee’s risk score and the number of days that they miss from work. As you would expect, the higher the risk score ‒ the less healthy the employee ‒ the more time that they miss.

Going back to our back specialists, when we risk-adjust their patients and level the playing field the results change again.

Now the doctors’ total costs and rankings are based on their performances, not the patients that they treated. Doing this, we see that Specialist #13 was doing a better job than we initially thought. This doctor would now be ranked 10th, not 13th.

When we re-order the doctors based on their average risk-adjusted total costs, Specialist #1 is still the best, and Specialist #14 is still the worst. But other than Specialist #12, the order has completely changed. The green arrows show the doctors who moved up, and the red arrows show the ones who moved down.

We can also show this on a quadrant graph. Along the horizontal axis, we graph each provider based on their average claims costs relative to the group average, and along the vertical axis we do the same for the absence costs. The best providers are in the upper right quadrant ‒ low claims costs and low time off ‒ and the worst providers are in the lower left quadrant, with high claims costs and high time off.

Fort Worth’s Provider Network

Fort Worth used these analytics to identify the best providers by injury type and then placed them in its own workers’ compensation provider network. An injured employee must stay within this panel when seeking treatment.

But Fort Worth didn’t just look at its workers’ compensation claims and rank the doctors handing its current cases. Instead, it threw in its health plan claims, too. That way, it identified great doctors not currently handling workers’ compensation cases, but whom the city wanted to in the future.

By sending injured employees to the best doctors, Fort Worth achieved fantastic results ‒ a decrease of 23% in its costs while getting its employees better care!

Benchmarking and Predictive Analytics

Fort Worth didn’t stop there, but incorporated the Official Disability Guidelines (ODG) for benchmarking and predictive analytics, too. ODG is a nationwide database of workers’ compensation and occupational health injuries owned by the Hearst Health Network.

Using these guidelines, Fort Worth not only compares the providers in its network against one another but benchmarks them against national and regional best practices and averages for claims, time off work and other metrics. These other metrics include whether the doctor is seeing the employee more often than usual for a particular type of injury, or whether the doctor is billing unusual procedure codes (which could be either good or bad but bears investigating). In addition, comparing claims against the database allows Fort Worth to categorize them as being within the normal range for that injury type ‒ which the city can pay without further scrutiny ‒ or outside those norms, in which case the city flags the claims for investigation.

Fort Worth also uses the guidelines to perform predictive analytics. When an injury occurs, the city predicts the claims and lost time based on specific factors and then monitors the case and intervenes early when the actual results begin to stray from the predicted ones. For example, using ODG, the table on the left predicts 47 days off and $7,925 in total expenses for an employee suffering a lower back sprain with the following particulars:

  • 40 years old
  • Living in Texas
  • Job involves “medium” physical demands (not sedentary, like an office worker, or heavy, like a construction worker)
  • No risk factors or comorbidities
  • Case involves some time off work, so it is more severe (80% of all workers’ compensation cases involve only medical expenses, no lost time)

The table in the middle shows that keeping everything the same, except adding that the employee has diabetes, increases the prediction to 62 days off and $11,204 in total expenses. And the table on the right shows that, if the employee hires a lawyer ‒ not a comorbidity for an employee, but definitely a risk factor for an employer ‒ everything more than doubles!

Health Plans

You can use these analytics for your health plan, too. When doing so, there are two differences.

As discussed above, in workers’ compensation, many states permit the employer to direct care. In most health plan settings, however, you can’t do that. You can only encourage someone to go to the best doctor. They can go to whomever they want.

So how do you get your employees and their dependents ‒ your health plan members ‒ to the best doctors for what they need? You could ask your TPA to include only the best doctors in the provider network, or at least eliminate the worst ones, but your TPA usually won’t do that. In fact, many of the contracts that TPAs sign with health systems preclude the TPAs from excluding any of the health system’s providers from the network or steering patients away from them.

Although you won’t be able to set the network, you can stratify it. Tier the network and decrease or eliminate co-pays and out-of-pocket costs when members go to the best doctors. If you have an HDHP (High Deductible Health Plan) married with HSAs (Health Savings Accounts), you can even pay employees to go to the top-ranked doctors by contributing to their HSAs when they do so.

You can also give a list of the best providers for each root diagnosis to:

  • The case managers handling your high-cost and chronically ill members so that those case managers can suggest the best providers to them;
  • The primary care physicians (PCPs) in your network to use when referring your members to specialists and surgeons; and
  • The employees themselves so that they and their dependents can look up the best providers for what they need.

The second difference is that your health plan will have not only employees in it but their dependents, too. You won’t be able to use the algorithms above on the dependents because you won’t have any absence data to match against their claims.

See also: Startups Must Look at Compensation Plans

Instead, you can use a different algorithm on the dependents that uses only the claims data. For the employees, we combine the claims and absence data and ask how much it cost and how long it took to get the employee back to work and keep them there. For the dependents, we flip the question and ask how much it cost in claims to keep them well.

We define being well in terms of healthy days, which we can see in the claims. Healthy days are days that the person does not spend in the healthcare system (e.g., hospital stays, doctor’s visits, etc.) or at home in a non-functional state (e.g., recuperating or otherwise unable to carry out their normal activities).

We put this information in a fraction. The numerator is the patient’s risk-adjusted claims for a particular root diagnosis during the year, and the denominator is the patient’s healthy days during that year. We then rank each provider by root diagnosis, from the best with the lowest average risk-adjusted claims per healthy day when treating patients with that condition, to the worst with the highest.

Not only can you rank providers based on their claims per health day, but you can rank wellness programs and just about anything else, too. The chart below compares the risk-adjusted claims per healthy day to keep employees with behavioral health issues at work (instead of out sick) against the claims per healthy day to keep employees without those issues at work (almost everyone has some claims and absences during a year). The risk-adjusted claims per healthy day for a person without any issues is $10, while the claims per day for a person with headaches is double that at $21 per day, and the claims per day for a person with drug and alcohol problems is double that again at $44.

Better Care at Lower Costs

,Fort Worth busted the myth that better care costs more. By sending injured employees to the best doctors the city drove down its costs, while getting its employees better care.

This article originally appeared in the March/April 2021 issue of Public Risk, the member magazine of the Public Risk Management Association (PRIMA).

2022 Will Challenge Health Insurers

Looking toward 2022, health insurers are going to be wrestling with all the ways COVID has transformed the health insurance industry and what it means for coverage, pricing and patient care for years to come. 

Some positive things have come from the response to the pandemic — the rise of telemedicine and a blunted cold and flu season both come to mind. But, more than anything, the pandemic has brought uncertainty that is going to take months, if not years, to completely work through, including within the health insurance industry. 


Before COVID-19, telehealth made up a sleepy corner of the health care delivery system. 

Held back by uneven reimbursement schedules, telehealth served as a niche solution for just a few healthcare problems. 

But as social distancing and government-imposed lockdowns swept the country, many people gave telehealth a fresh look. Perhaps more importantly, federal regulators changed how Medicare and Medicaid reimbursed telehealth appointments within their programs. 

A recent assessment by McKinsey showed a 38-fold increase of telehealth appointments during the core of the pandemic. And it makes sense. Patients were looking for ways to stay away from other people, but they still needed healthcare. Seeing a doctor from the comfort of their own couch was a great solution. 

But many patients also embraced the new healthcare delivery for other reasons. People with transportation challenges flocked to telemedicine as a way to avoid the commute to the doctor, and parents used telemedicine to help solve child care dilemmas. Plus, telemedicine was a convenient way for professionals to see a doctor from their cubicle during their lunch break. 

So, what started as a pandemic workaround looks like it may be here to stay. 

The question mark when it comes to telemedicine is whether the more generous reimbursements offered to providers during the pandemic will continue into the future. If insurers or federal regulators change back reimbursement schedules, many providers may pull back on virtual appointments, even if their patients are still asking for them. 

See also: On COVID Vaccine: Do the Math

Mental Health

One of the areas of healthcare that has thrived during the pandemic, including via telemedicine, is mental health. Therapy appointments don’t rely on physical evaluations, so they seem to be a natural for telemedicine technology. 

That still doesn’t mean that every patient who was looking for mental health services could find it, even though it is covered by all Affordable Care Act-compliant plans. An October 2021 report published on insurancequotes.com cited data from the National Alliance on Mental Health, which found that as many as 55% of psychiatrists are not accepting new patients, and that a third of people who want to find a mental health provider say they cannot find someone who would accept their insurance.

The lack of availability is bad news. According to the Kaiser Family Foundation, four in 10 adults reported anxiety or depression during the pandemic, up from one in 10 before. 36% reported having difficulty sleeping, 32% reported changes in eating patterns and 12% reported an increase in alcohol or substance use. 

Some industry analysts hope that innovations in telemedicine may continue to ease the bottleneck, but a shortage of mental health providers is likely to continue into the foreseeable future.


COVID-19 has thrown a major wrench into the normally well-oiled policy pricing system. Because premiums are priced according to past years’ experience periods, the past two years pose a problem. 

For one, COVID-19 disrupted normal care patterns. Early in the pandemic, people avoided routine care, and many of those who did contract the virus faced astronomical ICU costs. Pandemic surges also forced some overburdened hospitals to delay elective procedures. 

In addition, most insurers have now stopped waiving patient shares of COVID treatment, and there is very little in the way of reliable pricing from the recent past to use to set future premiums. 

Other major challenges include the uncertainty about whether there will be future COVID waves, whether a relaxation of masking and social distancing will cause cold and flu cases to again surge and how two years’ worth of deferred or avoided care could affect morbidity when it comes to chronic conditions. 

With all of that, insurers run the twin risk of either over- or undercharging premiums for 2022. 

Political influences

Discussions of health policy and COVID cannot be had in a political vacuum. Whether the conversation is about vaccine hesitancy or employer vaccine mandates, tempers flare. 

The biggest question for health insurance providers is how the courts are going to handle so-called COVID surcharges. While the Affordable Care Act mandates that different premiums cannot be charged to similar people based on their health history, many employers are charging unvaccinated employees surcharges on their health costs. Employers are taking different routes, ranging from wellness programs to EEOC-endorsed incentive programs, but, no matter the legal justification, the issue is almost certain to land in federal court. 

Navigating the political waters is going to be a challenge for every health insurer for the year to come. 

See also: Mental Health in Post-COVID Era


COVID-19 will have a lasting impact on the healthcare industry. Navigating pricing, the future of telehealth and the political uncertainty is going to take a careful hand. 

But, for companies that respond deftly, 2022 also has the potential to offer a cautious return to normalcy, even amid massive uncertainty. 

Aduhelm: Case Study on Paying for Health

In July, I wrote an article that criticized the newly authorized Alzheimer’s drug Aduhelm. Six months later, the market response is heartening and, in my opinion, a case study in what it will take to fix the way that we pay for healthcare in America. 

A review of the problem

The FDA approved the first new drug to treat Alzheimer’s in June. Of 11 scientists who reviewed the research and science behind the new treatment for the FDA, 10 voted against approval, and one was undecided. The FDA approved Aduhelm despite the lack of evidence that it either cures or slows the progression of the Alzheimer’s and has given the company nine years to conduct a confirmatory trial. Three of the scientists resigned as a result. The head of the FDA also took the very unusual step of asking for an investigation into unusual/informal contacts between the manufacturer and people at the FDA.

The drug price is set at a whopping $56,000 per year, and the real price tag is more like $100,000 when you include the cost of performing the infusion in a provider’s office, testing to monitor for brain bleeds, etc. With 6 million Alzheimer’s patients in America today, having just one in six get a prescription would drive costs of around $100 billion into the system. Total outpatient Medicare drug spending with pharmacy prescriptions was $136 billion for 2019.

A review of the last six months

Biogen and other analysts projected sales of $103 million this year, about $1 billion in 2022 and $5 billion-plus in 2023. However, the market has responded in a very encouraging way. Sales have just totaled $2 million thus far.

What happened? The Veterans Administration, several Blue Cross Blue Shield companies and most notably Medicare are not yet paying for the treatment. Highly respected medical institutions like Cleveland Clinic and NY City’s Mount Sinai have also chosen not to administer the drug. So have many well-managed, large employer health plans. All are waiting for real evidence the drug is effective in either slowing the development of or in curing Alzheimer’s disease. 

See also: How Synthetic Data Aids in Healthcare

How we will make real progress

The free market is the only viable solution — if we can get to one in the way that we pay for healthcare.

I am often asked when we will see real progress in our insurance payment model. I typically laugh and say, “As soon as lobbying is no longer effective.” But that is not the end of the story. I more seriously share that we are seeing the problem get solved one employer at a time (another way of saying it will be solved by the free market). When employers build a health plan with a consultant that provides transparency around the actual cost of care and then build their plan to reward good consumption, it is amazing how quickly they can get to a place, where costs go down and quality goes up. 

For change that will affect the system more broadly, we need government to ensure that we have rules in place that require transparency. Until that happens, we will be stuck handling the problem one employer at a time.

How Synthetic Data Aids in Healthcare

Finance and insurance companies have been leveraging synthetic data for many years to improve their workflows while ensuring information confidentiality. With the COVID-19 pandemic, scientists who are striving to find ways to combat the virus have considered synthetic data. How can this technology be of use in healthcare, and how does it help to cope with the pandemic?

What Synthetic Data Is

Without going into convoluted definitions, synthetic data is artificially generated data. It is similar to real data but doesn’t copy it. Synthetic data is generated automatically with the help of dedicated algorithms. It can be in the form of text, video, image, audio or information from tables. 

Synthetic data can be applied in various areas. Waymo uses it to train its driverless cars. American Express uses artificially generated financial information to improve its fraud detection system. Synthetic data helps companies calculate risk accurately while protecting real customers’ data. The OpenAI team has taught the language model GPT-3 to compose texts similar to those that a human would write. A program belonging to Nvidia creates photos of people based on images of real individuals.  

In healthcare, using synthetic data means that important analysis can be done without associating particular people with their medical records. After the outbreak of the coronavirus pandemic, the need for applying such data in healthcare has increased. 

Synthetic Data in Healthcare

Secure data exchange is one of the major concerns in healthcare. According to the General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act (HIPAA), any confidential information can’t be disclosed without the consent of the person it belongs to.

Information from patient records must be stored and transferred securely Using the data without specifying the name of the patient is prohibited, too, as it is possible to identify an individual based on the data set. 

That’s why it is more lawful and secure for researchers to create synthetic data as they conduct studies crucial for humanity. Prototypes of training software for machine learning models are trained with synthetic data so they can work with real patient data later. Developers don’t have access to the real information — they can’t read it, extract it from software or use it in any other way.

See also: Avoiding Data Breaches in Healthcare

How Synthetic Data Is Generated

If the true patient is not at risk of being identified, information from real medical records can serve as the basis of synthetic data, though joint case records are much more commonly used. There is also the sort of approach that Mitre offers via Synthea, an open-source tool that allows for creating fictional patients based on publicly available information: scientific research data, disease statistics, demographics and so on. Although the generated dataset is not as reliable as “fakes” of the real medical records, the platform continues to be improved under the auspices of the U.S. government.

Although synthetic data is not suitable for studying real diseases and treatment methods, it can be the basis for the development of applications that allow for using real data without breaking the law. 

Thus, synthetic data opens access to research and development of new technologies in healthcare. 

Practical Applications of Synthetic Data 

Soon after the pandemic outbreak, Israeli scientists began testing synthetic data technology based on EMRs from the last 20 years. Sheba Medical Center — the country’s largest hospital — used the MDClone platform to synthesize the data of its coronavirus patients.

The healthcare facility invited analysts who collected all the information about the virus from the data set. The result of the cooperation of medical researchers and software developers was an algorithm that helps the hospital staff decide when to prescribe medications or when inpatient treatment is needed. 

The software allowed Sheba Medical Center to combine the data from its EMRs with the data belonging to another Israeli healthcare facility — Maccabi HealthCare Services. This provided scientists with a broad view of the course of the individual disease, helping estimate coronavirus outcomes for each person. Without synthetic data technology, the project would have taken much longer as permission to use confidential information would have been required.

Of course, medical scientists can’t rely solely on synthetic data in their research, but the data lets them easily analyze an unlimited number of hypotheses that can lead to significant time savings during the approval of new drugs for real patients.

See also: Wake-Up Call on Ransomware

Although some data security experts doubt that synthetic data in healthcare can ensure patients’ anonymity, this data is extremely useful in prognostications, survival analysis, clinical trials, decision-making and more. Such technologies will accelerate innovation in healthcare while helping scientists comply with legislation. 

Aduhelm – and What’s Wrong in Healthcare

The FDA approved the first new drug to treat Alzheimer’s in nearly 20 years in recent weeks, and it is a prime example of why our spending on healthcare is so unnecessarily high and not slowing down anytime soon. The new drug is Aduhelm, an infusion therapy developed by Biogen.

A panel of 11 scientists reviewed the research and science for the FDA, and 10 voted against approval of the new treatment, while one was undecided. In fact, three of the scientists have resigned over the approval. The FDA moved to approve Aduhelm despite the lack of evidence that it either cures or slows the progression of the Alzheimer’s and has given the company nine years to conduct a confirmatory trial.

What is the actual cost of this treatment? The drug price is set at a whopping $56,000/year, and the overall costs will be much higher. According to the Kaiser Family Foundation, when related costs are included (the testing to monitor for brain bleeds and other possible side effects, outpatient facilities and staff, etc.) the real price tag will be more like $100,000/year. 

What is the cost to the individual? Copays will be as much as $11,500 – nearly 40% of the average income for a Medicare, enrollee according to the Kaiser Family Foundation.

How will this affect Medicare Part B premiums? As an infusion given in a provider’s office, administering Aduhelm will be covered by Medicare Part B. The current average premium for this coverage is just under $150/month. This will almost certainly have to be increased, so the impact will be widespread across Medicare enrollees.

See also: Are Your Healthcare Vendor’s Claims Valid?

What are the potential impacts to our overall healthcare spending? Biogen estimates that 1 million to 2 million Alzheimer’s patients match the patients studied in the clinical trials. Overall, we have approximately 6 million people who have Alzheimer’s in the U.S., and most are enrolled in Medicare. Interestingly, the FDA has approved the medication widely not just for those who are in the early stages of the disease with mild symptoms like those in the trial. If 1 million people are given this treatment, it could cost Medicare $56 billion annually. Medicare Part B spent $37 billion in total on drugs in 2019. Total outpatient Medicare drug spending with pharmacy prescriptions was $136 billion for 2019.

Biogen’s estimates of future sales are seemingly conservative. The company and other analysts are expecting $103 million in sales this year, about $1 billion in 2022 and $5 billion-plus in 2023. 

When you factor in the incentives paid to prescribing physicians by Medicare ($3,360 for each prescription in this case), it seems we have a real problem on our hands.  

The Centers for Medicare and Medicaid Services could decide not to cover Aduhelm, but if the past is any indicator this is not likely. Private insurers that provide Part B benefits could also place some limitations on the drug’s use. But, all things considered, It is clearly time for us to take a serious look at how we have allowed a fifth of our economy to get to this point.