Outcome of Suit Against Department of Labor Could Boost Skimpy Employer Health Plans
The case was brought by a marketing company that wants to define as employees people who download an app and agree to have their internet activity tracked so they can buy into its employee health plan. Such plans are generally exempt from some state and Affordable Care Act rules.
A lawsuit challenging the definition of an employee for access to work-based health plans has the potential to significantly impact employer health coverage. The outcome of the case, which involves the Department of Labor, could lead to increased availability of lower-cost but potentially less comprehensive health coverage, possibly without certain consumer protections. Settlement negotiations are reportedly underway, although the specifics remain undisclosed.
The case stems from Data Marketing Partnership, which filed the suit in 2019 during the first Trump administration. The plaintiff seeks recognition as an employer to allow limited partners to participate in job-based health insurance plans exempt from state insurance rules and ACA requirements. The key issue is whether these partners can be considered employees.
If the court rules in favor of the plaintiff, it could lead to a surge in aggressively marketed insurance plans with limited consumer recourse, as they would be exempt from state oversight. This could potentially create a proliferation of unregulated insurance companies. Currently, the Department of Labor maintains its stance that individuals who download software to capture data from internet browsing are not employees.
Meanwhile, insurers are anticipating another round of premium increases next year due to declining enrollment, with the trend likely to continue as more individuals shift to alternative coverage options. State insurance commissioners have already taken action against purveyors of limited-partner policies, citing insufficient coverage and potential unpaid medical bills.
Written by urgent.news from KFF Health News's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
