麻豆果冻传媒影音

Denials of insurance claims for preventive care were disproportionately more common among at-risk patient populations, including low-income patients, those with a high school degree or less, and patients from minoritized racial and ethnic groups, according to a cohort study in .

In this exclusive video interview, study author Alexander Hoagland, PhD, of the Institute of Health Policy, Management, and Evaluation at the University of Toronto, offers potential solutions for these observed disparities.

The following is a transcript of his remarks:

This study's objective was to understand the reasons behind which preventive care is often denied by private insurers in the United States, and how these denials affect different population groups.

Preventive care, including wellness visits, cancer screening, and contraceptive care, is exempt from cost-sharing under the Affordable Care Act. However, significant cost burdens still fall on patients when those services are either incorrectly billed or processed by insurers, leading to unexpected bills for patients. This project wanted to understand what drove those denials and which patient groups were affected the most.

In this study, we used rich healthcare claims data linked with demographic information from electronic health records and self-reports to identify who experienced a denial for preventive care and potential inequities in those denials.

Overall, we found that the denial rate for preventive services was a little under 1.5%, which still affected thousands of patients in our sample. Of these denials, a little more than half stemmed from insurers denying specific benefits; so, for example, a particular contraceptive device that wasn't covered by an insurer. Most of the remainder were driven by billing errors -- so, clinicians who submitted a claim for a preventive service, but without the appropriate modifiers or with incorrect diagnostic information included.

Importantly though, both of these types of denials differed considerably across patient groups. When we looked at differences across patient household income and education and patient race and ethnicity, we consistently found that more at-risk patient groups experienced higher rates of denials.

The lowest-income patients, patients making less than $30,000 a year, were 43% more likely to have their claims denied than households making over $100,000 a year. Similarly, patients who had a high school education or less were more than 57% more likely to have a denial compared to patients with college degrees. And perhaps most surprisingly, denial rates for racial and ethnic minorities, including Asian patients, non-Hispanic Black, and Hispanic patients, were roughly twice as common as denials for non-Hispanic white patients.

This study is important because it points to these systematic differences in how the cost-sharing exemption for the Affordable Care Act is applied across patient groups, as well as across physicians, clinics, insurers, and patient geography. The ACA never actually specified in law which services need to be cost-sharing-exempt or at what frequency or how the billing insurer approval process should work.

This means that every patient visit may be differentially at risk for a bill depending on who they see, what kind of services they receive, where they live, and who their insurer is. Our study is the first that we know of to document the type of heterogeneity that exists across these patient groups in the incidence of claims denials, particularly for preventive care.

Importantly, these differences meaningfully impact patients in two ways. First, very few denied claims are resubmitted to insurers. So this means that patients who face a denial are very likely to have to pay for a service that they expected should be free to them. Second, we show that when the bills come, they're actually 10% to 15% higher for marginalized patient groups. These patients are both more likely to experience a denial and have a bill arrive, and then they're more likely to have a larger bill when that bill does come.

There are important steps that we can take based on these results to move forward. On the policy side, this could be standardizing what actually constitutes preventive care under the Affordable Care Act or how it's billed, but there are also different possible next steps across all of the different agents involved in these interactions -- insurers, providers, and patients.

Insurers who are increasingly using artificial intelligence models to routinely deny some types of care run the risk of further entrenching these inequities that we've discovered in our analysis. This could be one major drawback to using these kinds of data-driven models to try to reduce administrative costs among insurers.

On the other hand, providers and clinics also need to be mindful of appropriate billing techniques to avoid billing errors, and also work together with patients to improve health literacy and address billing errors such as denials when they come, so that patients know where to advocate for themselves and aren't just left on the hook for this high-value preventive care.

Just one really important piece to this puzzle that we're still working out is the process that patients and providers follow after a denial to advocate for the proper payment from an insurer. Sometimes this process is as simple as just swapping the order of the diagnostic codes in a claim and resubmitting it to an insurer. But even that simple process requires that the patient know that that's the issue and have the time to facilitate that correction. So, if that advocacy itself happens at differential rates across these patient groups, then the inequities we observed here in the denials data may only be the beginning of the disparities.

We have more work on this coming out soon, so stay tuned. But providers and patients should be well informed about their rights in the face of insurer denials and be able to act accordingly.

Comment