Tag Archives: snap

States Must Focus on Healthcare Fraud

Fraud in social benefit programs causes much more than economic damage. It can lead to patient deaths and harm from poor-quality healthcare. Fraud also facilitates and masks deeper issues such as substance abuse disorders (SUD), domestic violence and elder abuse. States should invest more resources in detecting and investigating social benefits fraud to limit these negative effects.

Not surprisingly, a state’s or agency’s commitment to fighting fraud can vary. Some have a zero tolerance for fraud, while others see fighting fraud as simply bashing the poor. I argue that not pursuing fraud detection means losing insights that can help detect other problems and may increase the risk of negative outcomes. Here is why:

One of the most tragic repercussions of Medicaid fraud is the poor quality of care and lack of concern for patient safety that can come as an unintended byproduct. In Ohio, three nurses billed for services they did not provide for months, resulting in the death of a 14-year-old girl with cerebral palsy. At the time of her death, Mikayla Norman was covered in bedsores and weighed only 28 pounds. Care coordinators often do not see patients; they rely on the medical records and billed services to track care delivery and assess further service authorizations. They believe services are being provided because services were billed, even if billed fraudulently. The system failed Mikayla Norman, and the Medicaid fraud helped mask what was happening.

Another example comes from Dr. Farid Fata, a Michigan oncologist, who was found guilty of $34 million of healthcare fraud. He billed Medicare and other payers for services not rendered and diagnosed healthy patients with cancer. His medically unnecessary treatments caused severe harm to his patients, including death.

Examining information and data around family behaviors can provide insights to help discover families in crisis. As a case manager, after looking at a report card, I once asked a recipient why her kindergartner was absent or tardy dozens of times. The conversation started with “I have trouble getting up in the morning” and finished with “I need some help. Can you get me into a treatment facility?” This person completed treatment, earned an education, entered a training plan and got a job. That one odd data point changed the trajectory of this person’s life and the family, but only because the data was examined.

During my government service working in social benefits fraud, we noticed law enforcement officers talking about drug dealers found with Supplemental Nutritional Assistance Program (SNAP) electronic benefit transaction (EBT) cards. Maine is one of several states working to address this issue, but trafficking and abuse occur in every state. State investigators monitoring SNAP retailers also reported shop owners trafficking SNAP EBT benefits for alcohol, drugs and even guns. By not examining SNAP EBT fraud closely, states may be turning a blind eye to these other behaviors.

See also: COVID-19 Risk and Buyers’ Psychology

SNAP retailers who traffic EBT benefits prey on recipients. If a recipient sells his or her monthly benefit once, it is often for an urgent need. Did the state or county office tell SNAP recipients there are programs to help with emergency needs like a car battery or rent assistance? Does the program operate quickly enough to actually meet emergency needs? For recipients who consistently traffic SNAP EBT benefits, is intervention and treatment needed? Are there children in this home who are now at further risk of going hungry or being neglected?

Government coffers are just the first “victims” of healthcare and benefits fraud. Maybe fraudsters don’t consider the patients and citizens who are collateral damage in their schemes. Maybe they don’t care. But states must.

Governments need to make fraud detection a greater priority. States must identify and remove more SNAP retailers who traffic benefits and take advantage of recipients. Government fraud fighters must punish more providers that put patients at risk — not just to end their financial schemes but to improve population health and patient outcomes.

Combatting fraud is usually talked about as a way to reduce costs. And it is! Billions of dollars of spending are avoided or recovered every year through government fraud fighters. But, too often, fraud leads to some people paying the greatest price of all.

How Tech Created a New Industrial Model

With a connected device for every acre of inhabitable land, we are starting to remake design, manufacturing, sales. Really, everything.

With little fanfare, something amazing happened: Wherever you go, you are close to an unimaginable amount of computing power. Tech writers use the line “this changes everything” too much, so let’s just say that it’s hard to say what this won’t change.

It happened fast. According to Cisco Systems, in 2016 there were 16.3 billion connections to the internet around the globe. That number, a near doubling in just four years, works out to 650 connections for every square mile of Earth’s inhabitable land, or roughly one every acre, everywhere. Cisco figures the connections will grow another 60% by 2020.

Instead of touching a relatively simple computer, a connected smartphone, laptop, car or sensor in some way touches a big cloud computing system. These include Amazon Web Services, Microsoft Azure or my employer, Google (which I joined from the New York Times earlier this year to write about cloud computing).

Over the decade since they started coming online, these big public clouds have moved from selling storage, network and computing at commodity prices to also offering higher-value applications. They host artificial intelligence software for companies that could never build their own and enable large-scale software development and management systems, such as Docker and Kubernetes. From anywhere, it’s also possible to reach and maintain the software on millions of devices at once.

For consumers, the new model isn’t too visible. They see an app update or a real-time map that shows traffic congestion based on reports from other phones. They might see a change in the way a thermostat heats a house, or a new layout on an auto dashboard. The new model doesn’t upend life.

For companies, though, there is an entirely new information loop, gathering and analyzing data and deploying its learning at increasing scale and sophistication.

Sometimes the information flows in one direction, from a sensor in the Internet of Things. More often, there is an interactive exchange: Connected devices at the edge of the system send information upstream, where it is merged in clouds with more data and analyzed. The results may be used for over-the-air software upgrades that substantially change the edge device. The process repeats, with businesses adjusting based on insights.

See also: ‘Core in the Cloud’ Reaches Tipping Point  

This cloud-based loop amounts to a new industrial model, according to Andrew McAfee, a professor at M.I.T. and, with Eric Brynjolfsson, the coauthor of “Machine, Platform, Crowd,” a new book on the rise of artificial intelligence. AI is an increasingly important part of the analysis. Seeing the dynamic as simply more computers in the world, McAfee says, is making the same kind of mistake that industrialists made with the first electric motors.

“They thought an electric engine was more efficient but basically like a steam engine,” he says. “Then they put smaller engines around and created conveyor belts, overhead cranes — they rethought what a factory was about, what the new routines were. Eventually, it didn’t matter what other strengths you had, you couldn’t compete if you didn’t figure that out.”

The new model is already changing how new companies operate. Startups like Snap, Spotify or Uber create business models that assume high levels of connectivity, data ingestion and analysis — a combination of tools at hand from a single source, rather than discrete functions. They assume their product will change rapidly in look, feel and function, based on new data.

The same dynamic is happening in industrial businesses that previously didn’t need lots of software.

Take Carbon, a Redwood City, CA maker of industrial 3D printers. More than 100 of its cloud-connected products are with customers, making resin-based items for sneakers, helmets and cloud computing parts, among other things.

Rather than sell machines, Carbon offers them like subscriptions. That way, it can observe what all of its machines are doing under different uses, derive conclusions from all of them on a continuous basis and upgrade the printers with monthly software downloads. A screen in the company’s front lobby shows total consumption of resins being collected on AWS, the basis for Carbon’s collective learning.

“The same way Google gets information to make searches better, we get millions of data points a day from what our machines are doing,” says Joe DeSimone, Carbon’s founder and CEO. “We can see what one industry does with the machine and share that with another.”

One recent improvement involved changing the mix of oxygen in a Carbon printer’s manufacturing chamber. That improved drying time by 20%. Building sneakers for Adidas, Carbon was able to design and manufacture 50 prototype shoes faster than it used to take to do half a dozen test models. It manufactures novel designs that were previously theoretical.

The cloud-based business dynamic raises a number of novel questions. If using a product is now also a form of programming a producer’s system, should a company’s avid data contributions be rewarded?

For Wall Street, which is the more interesting number: the revenue from sales of a product, or how much data is the company deriving from the product a month later?

Which matters more to a company, a data point about someone’s location, or its context with things like time and surroundings? Which is better: more data everywhere, or high-quality and reliable information on just a few things?

Moreover, products are now designed to create not just a type of experience but a type of data-gathering interaction. A Tesla’s door handles emerge as you approach it carrying a key. An iPhone or a Pixel phone comes out of its box fully charged. Google’s search page is a box awaiting your query. In every case, the object is yearning for you to learn from it immediately, welcoming its owner to interact, so it can begin to gather data and personalize itself. “Design for interaction” may become a new specialization.

 The cloud-based industrial model puts information-seeking responsive software closer to the center of general business processes. In this regard, the tradition of creating workflows is likely to change again.

See also: Strategist’s Guide to Artificial Intelligence  

A traditional organizational chart resembled a factory, assembling tasks into higher functions. Twenty-five years ago, client-server networks enabled easier information sharing, eliminating layers of middle management and encouraging open-plan offices. As naming data domains and rapidly interacting with new insights move to the center of corporate life, new management theories will doubtless arise as well.

“Clouds already interpenetrate everything,” says Tim O’Reilly, a noted technology publisher and author. “We’ll take for granted computation all around us, and our things talking with us. There is a coming generation of the workforce that is going to learn how we apply it.”

Medicaid Expansion – A Hand Up Or A Handcuff?

Medicaid has several components, but at its core it is a health insurance program for the poor. States can differ, but most provide for those below the poverty level. Federal health reform requires expanding Medicaid to those earning up to 138% of the poverty level (about $25,000 for a family of 3). The U.S. Supreme Court has ruled that each state can accept or reject the expansion of Medicaid. Like other states, Georgia must make that choice. This analysis addresses the human impact — not state financing, our national debt, or deficit spending. The key question: Is Medicaid expansion beyond the poverty level a “hand up” or a “handcuff?”

Unlike other income levels in America, getting ahead is less likely if you are in the bottom 20%. The Economic Mobility Project of the Pew Charitable Trusts shows 65% of children born in the lowest 20% of incomes stay in the bottom two quintiles.

Upper Limit of U.S. Income Quintiles: 2010
Lowest 20% Second 20% Third 20% Fourth 20% Lower limit of top 5%
$20,000 $38,043 $61,735 $100,065 $180,801

If the core philosophy of Conservatives is producing upward economic mobility and Progressives are for helping the poor, why have both ideologies failed the poorest among us? Scott Winship, a researcher at the Brookings Institute has said, “The bottom 20% in the U.S. looks very different from the bottom 20% in other countries.” Americans are more likely than foreign peers to grow up with single mothers. In poor communities, drugs, alcohol, violence, and ineffective primary and secondary schools represent a huge barrier to economic mobility. The United States also has uniquely high incarceration rates, and a longer history of racial stratification.

With all those challenges, the Brookings study showed that regardless of race or ethnic background, if you stay in school at least through high school, don’t have a child until you’re married and over 21, and work full-time at any job, your chances of being poor are only 2 percent and your chances of joining the middle class are 74 percent.

More than other countries, poor Americans have to educate and work their way up from the lower levels. The United States provides many benefits for the poor, disabled, and unfortunate. No one of any rational political or ideological persuasion is opposed to helping those in need.

The key part of Medicaid is also called “Temporary Assistance for Needy Families” or TANF. Under health reform Medicaid would be expanded to 18-20 million new lives. Other health reform subsidies through exchanges are available up to 400% of the poverty level (about $92,000 for a family of 4). Programs affecting larger percentages of the population can create an attitude of entitlement and a culture of dependency that traps segments into intransigent generational poverty.

A study of entitlement programs in Colorado illuminates the concerns for Georgia and other states. Programs are available to low income families to provide housing, food, healthcare, educational, and other subsidies. A single mother with two children making $25,000 could be eligible to receive about $18,000 in government benefits.

Maximum Available Tax and Benefit Programs

Medicaid expansion and other health reforms add new subsidies for low and middle income families. Using the same example of a single mother with two children, Medicaid expansion to 138% of the poverty level can provide an additional $7,500 in benefits to those making $25,000.

Health Benefits

What are the effects on real people as they try to advance economically? The marginal effective tax rate from federal income taxes, payroll taxes, and state income taxes, for a single mom with two children earning $25,000 is about 29.4 percent. If one includes other programs, SNAP (food stamps), state children’s health insurance program, and the new health reform subsidies, the marginal tax rate rises to 54.5 percent.

If benefits like Temporary Assistance for Needy Families, federal housing subsidies, and WIC (nutritional program for Women, Infants, and Children) are considered, the marginal tax rate is as high as 81.9 percent because families lose even more benefits due to higher earnings.

Who would work harder, take that extra job, or seek a promotion when most of the added earnings would be taxed away or government benefits are reduced? The destruction of initiative can be the inevitable consequence of expanding Medicaid with an additional $7,500 (for a total of over $18,000) to someone making $25,000, but providing nothing to a similar family making $75,000.

Clearly, even the most compassionate among us can see that accumulated effects of entitlement programs can break the spirit of personal responsibility and the motivation for upward mobility. Medicaid expansion and the new health reform subsidies to over 50% of the population are likely to produce the same dependence and economic barriers to upward mobility already evident in the lower 20%.

The standard of living in Georgia is directly related to its citizens’ ability to produce goods and services others want to purchase. Subsidizing able-bodied populations does not create economic growth for those individuals or for the state. In our compassion to help those in need, we tend to look away from the politically driven expansion of those programs and the debilitating dependency culture they enable. Georgia has apparently decided not to play that destructive game. Good for us.

As we look to the future and better ways to solve the problems of healthcare and health insurance, maybe Georgia can create an island of opportunity within a sea of growing dependency. Maybe we can remove the handcuffs of those chained to the programs and ideas of the past and offer a hand up rather than a handout.