Is Data-Driven Price Discrimination Ethical?

Insurers using digital health data to price services

 

Imagine Jane, a 23-year-old who grew up with type-1 diabetes, which puts her more at risk of developing other conditions later in adulthood compared to others without type-1 diabetes. While insurance companies are not allowed to discriminate against her against her based on her pre-existing conditions, would it be fair to discriminate her based on the conditions they believe that she can develop in the future? Let us further explore the ethical dilemma that this entails.

Shortcomings of Existing Safeguards

The Health Insurance Portability and Accountability Act of 1996 (HIPAA) governs the exchange of medical information between health care institutions such as health care providers (doctors, hospitals, clinics), health insurance companies, pharmacies, and any government entities involved, such as the Centers for Medicare and Medicaid Services (CMS), and state Medicaid offices. However, HIPAA only regulates the transfer of protected health information that is directly tied to 18 personal identifiers. These identifiers can include names, geographic identifiers, phone numbers, email addresses, social security numbers, health insurance information, IP addresses, biometric information, medical record numbers, etc.

What HIPAA does not cover is anonymized health data being sold by data brokers to health insurers and providers who can use the information to discriminate against individual consumers, or groups of consumers (i.e., certain demographics). Additionally, HIPAA does not protect data revealed on social media, emails, searches, or other online activities, especially on healthcare apps like Fitbit or MyFitnessPal, whose data can be sold to insurers (and others) without being de-identified. As such, health insurers and providers have been known to de-anonymize longitudinal patient records purchased from health data brokers by cross referencing the anonymized data with online browsing and purchase histories purchased from other sources.

While the Affordable Care Act of 2010 (ACA) prevents health insurers from denying coverage or charging more to consumers based on pre-existing conditions, the law does not prevent insurers from charging more for “expected conditions”. These are conditions insurers have reason to believe the patient will develop in the future, based on data analytics on medical history, online behavior, and purchasing history. This type of price discrimination can occur at the health provider level as well, where certain patients can be charged more for services based on the health data that the provider has on the individual.

Ethical Considerations

Is it ethical for health insurers and providers to purchase and use consumer data to price discriminate against their customers? The main issues at hand are fairness and harm. It is unfair to charge consumers higher prices for insurance coverage based on analytics that show that a particular customer has a higher chance of developing a certain condition in the future, when they are not certain of it actually occurring. It could very well be that certain patients will not actually end up costing more than the average patient, yet they end up paying more, or vice versa. It could also be that search histories and purchasing histories are not actually indicative of health risks for an individual, but rather could be part of general research, or purchases for others.

Arguably, it is also unfair to price discriminate certain customers based on obtained consumer information, because that would mean health insurers can only price discriminate against those who have information about them available, leaving those without an online footprint in a better position. Additionally, it is unfair for health providers to charge different prices for the same services rendered now, just because you expect the patient to cost more in the future.

In terms of harm, patients are obviously harmed financially by this practice, as we have seen healthcare costs and medical debt skyrocket in the US, both in absolute terms and as a proportion of real income. The number one rule in medicine is to do no harm, but by price discriminating, insurers are hurting many patients and their families financially.

There are a number of ethical tradeoffs in this situation. Of course, health insurers and most providers are for-profit entities that have the fiduciary responsibility to do what is most profitable for their company and their investors. However, while maximizing profit by price discriminating, insurers are ignoring patients’ rights to health privacy, which was the entire spirit of HIPAA (even though browsing data is not covered in the law). Additionally, they are violating the fairness and transparency principles by not treating their patients equally, and not telling the public about their discriminatory practices.

Concluding Thoughts

Before the ACA, health insurers were free to discriminate based on pre-existing conditions, so it seems that finding new ways to price discriminate has always been the norm of the health insurance industry. The individual mandate of the ACA was meant to counter this by creating large enough risk pools of low-cost healthy people to subsidize the costlier sick and elderly. But with the individual mandate being repealed in the recent GOP tax plan, it seems the only solution is regulation to prevent health insurers and providers from using data to price discriminate in all forms. Until then, we can only hope that insurers act ethically with patients in mind.

 

 

Shayan Hobbi is a second-year MBA and MS in Information Systems graduate student at the University of Maryland with over 3 years of full-time experience in healthcare research program management in the federal government. Before that, he graduated with a BA in Economics from the University of Maryland in 2013.

Shayan’s professional experience within healthcare research program management includes: budgeting, proposal review, grant/contract writing, contract negotiation, grant/contract compliance, IT strategy, information systems design and implementation, database design and management, business process analysis and re-engineering, as well as data analytics and visualization. Most recently, Shayan completed his MBA summer internship at Ernst and Young’s Federal Technology Transformation practice as a consulting intern, where he served the Centers for Medicare and Medicaid Services (CMS).

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