Tag Archives: trump administration

Big Data Can Solve Discrimination

Big data has the opportunity to end discrimination.

Everyone creates data. Whether it is your bank account information, credit card transactions or cell phone usage, data exists about anyone who is participating in society and the economy.

At Root, we use data for car insurance, an industry where rating variables such as education level or occupation are used directly to price the product. For a product that is legally mandated in 50 states, the consumer’s options are limited: give up driving and likely your ability to earn a living or pay a price based on factors out of your control.

Removing unfair factors such as education and occupation from pricing leaves room for variables within an individual’s control — namely: driving habits. In this way, data can level the playing field for all consumers and provide an affordable option for good drivers whom other companies are painting with a broad brush. In the lon term, everyone wins as roads become safer and driving becomes prohibitively expensive for irresponsible drivers.

This is just one example where understanding the consumer’s individual situation deeply allows for more precise — and more rational — decision making.

But we know that the opportunity of big data goes beyond the individual. For example, the unfair practice of naively blanketing entire countries, religions or races unfairly as “dangerous” is a major topic in the news. What happens if you apply the lens of big data to this policy?

See also: Industry’s Biggest Data Blind Spot

Causal Paths vs. Assumption-Based Decisions

With the increased availability of data, we are able to better understand the causal paths between data generation and an event. The more direct the causal path, the better predictions of future events (based on data) will perform.

Imagine having something as trivial as GPS location data from a smartphone on a suspected terrorist. Variables such as having frequent cell phone conversations with known terrorists or being located within five miles of the last 10 known terrorist attacks will allow us to move away from crude, unjust and discriminatory practices and toward a more just and rational future.

Ahmad Khan Rahami, who placed bombs in New York and New Jersey, was flagged in the FBI’s Guardian system two years earlier. The agency found there weren’t grounds to pursue an investigation — a failure that may have been averted if the FBI had better data capture and analysis capabilities. Rahami purchased bomb-making materials on eBay and had linked to terrorist-related videos online before his attempted attack. Dylann Roof’s activities showed similar patterns in the months leading up to his attack on the Emanuel AME Church in Charleston, SC.

The causal path between a hate-crime or terrorist attack and the actions of Dylann Roof and Ahmad Khan Rahami is much more direct than factors such as religion, race or skin color. Yet we naturally gravitate toward making blanket assumptions, particularly if we don’t understand how data provides a better, more just approach.

Today, this problem is more acute than ever. Discrimination is rampant — and the Trump administration’s ban on travel is unacceptable and unnecessary in the era of big data. For those unmoved by the moral argument, you should also know policies like the ban are hopelessly outdated. If we don’t begin to use data to make informed, intelligent decisions, we will not only continue to see backlash from discriminatory policies, but our decision making will be systematically compromised.

The Privacy Red Herring

Of course, if data falls into the wrong hands, harm could be done. However, modern techniques for analyzing and protecting data mitigate most of this risk. In our terrorism example, there is no need for a human to ever view GPS data. Instead, this data is collected, passed to a database and assessed using a machine learning algorithm. The output of the algorithm would then direct an individual’s screening process, all without the interference of a human. In this manner, we remove biased decision making from the process and the need for a “spy” to review the data.

See also: Why Data Analytics Are Like Interest  

This definitely provides a challenge for the U.S. intelligence community, but it is an imperative one to meet. If used responsibly, analytics can provide insights based on controllable and causal variables. The privacy risk is no longer a valid excuse to delay the implementation of technologies that can solve these problems in a manner that is consistent with our values.

This world can be made a much better and safer place through data. And we don’t have to sacrifice our privacy; we can have a fair world, a safe world and a world that preserves individual liberties. Let’s not make the mistake of believing we are stuck with an outdated and unjust choice.

An Open Letter to the Trump Administration

As your transition team morphs into your operations group, I thought I would take a moment to give my thoughts on ACA as a seasoned consultant to this industry. While I hear the blustering about repeal and replace, it is my strong belief that any successful bi-partisan remake of healthcare will need to build from the success of President Obama’s signature legislation.

In building consensus, President-elect Trump may wish to throw a bone and acknowledge that reducing the ranks of the uninsured was a win, and it was not the only one. Here is my scorecard for the ACA:

High marks:

Facilitating the shift from fee-for-service to fee-for-value healthcare by supporting the Accountable Care model is important. Comparative effectiveness research, which creates national models for best practices in care delivery, has moved the cost of care, albeit too slowly, in the right direction. For example, a recent study in the Annals of Internal Medicine establishes that reimbursement penalties for hospital readmissions have reduced these by 77 out of 10,000 admissions.

Eliminating pre-existing conditions, benefit maximums and coverage rescissions is a critical change effected by ACA that must be retained. If coverage is purchased under the rules as developed, it is unconscionable that an insurance policy can simply no longer respond.

See also: What Trump Means for Health System  

Average grades:

Coverage for all children to age 26 added coverage for millions of our healthiest population. Uniform coverage for children who have yet to be established as adults is important. But to what extent? Should employers also have to cover the non-dependent adult children of their workers? The extended coverage is a generally good idea, but a small tweak would move it to the high marks section: require that the child be a tax-qualified dependent no older than 26.

We should have a coverage mandate; however, to make this effective it should have teeth. In Australia, the penalty for not having coverage is significant enough that younger adults wouldn’t consider the risk/reward tradeoff of “rolling the dice” to be a viable option. We should do the same and also provide age-banded rates that are not as punitive to the younger insured. Everyone has to be in the system because opting out has a backstop, too. Even prior to ACA, Americans had a coverage stopgap. If one was sick enough and needed care, pre-ACA, it would have been dispensed in the hospital.

Medicaid expansion is an excellent way to bring basic benefits to Americans who simply can’t afford healthcare. However, any new healthcare initiative has to find a way to mandate national standards for providing care for the indigent. Providing coverage for those with income at 18% of the federal poverty level or less is absurd, yet is a standard in two states for eligibility. Someone at that level can’t even afford food – there is no way they would pay into a healthcare system. Care should be basic and should have individual accountability built in – even the poor need to help control healthcare expenditures.

Employers should have to provide coverage meeting minimum standards, but the convoluted state-mandated benefits should be simplified and national standards should be established. This would also facilitate selling coverage across state lines and increase competition.

Failing grades:

Community rating makes sense in the small group marketplace. Standardized plans and rates simplify this market. But eligibility leakage such as association plans and PEOs (professional employer organizations), which are allowed to underwrite risk, “cherry-pick” the risk pool and ultimately create an insurance death-spiral.

The Cadillac Tax is a stupid way to finance healthcare change. Instead, the plans should have an actuarial value threshold that sets deductibility limits. If a business wishes to provide a higher level of benefits it should be able to, but the deduction would be disallowed. There is no reason an employer should be taxed for older demographics or a sicker work force that might increase premiums above the “Cadillac” premium limit.

The administrative complexity of ACA has to go. The exchanges are a bureaucratic nightmare. The reporting structure consumes needless resources for very little benefit. Policing the new system would be simple. The states would determine Medicaid eligibility, and the tax reporting system would capture those individuals without coverage.

See also: What Trump Means for Healthcare Reform

Other suggestions:

Establish price controls on brand name drugs that take into account financial incentives for inventiveness. A single drug available to treat a medical condition is like a monopoly, and it is against public policy for a monopoly to set rates (for example water or electric rates), so why should a drug company set an unconscionable price for a drug that cures hepatitis C or cancer? If one has that condition, he will pay anything to cure it. But it is the employer or the insurance carrier that bears the bigger financial burden. Perhaps there should be a separate award for that inventiveness not paid by the direct users — instead, a drug and medical innovation tax on insurance policies.

Drug price transparency should be immediately introduced. Drug rebates that obfuscate the true cost of medicine and either hide pharma profits or shift money back to the employer or plan administrator are ridiculous. Get rid of them.

It is an incredible time to be in healthcare!