A new paper explores the resources consumed by the complicated billing process in health care and the process’ impact on patients’ access to care.
Health insurance contracts account for 13 percent of US gross domestic product and impose many different administrative burdens on physicians, payers, and patients. Before delivering care, providers and insurers need to negotiate contracts to construct networks and establish payment rules. Insurers write and update policies determining which care each plan covers and under what conditions. Physicians and hospitals need to understand these rules to ensure they will be paid for the care they provide. Patients and their providers also need to monitor a separate prescription insurance plan to determine the costs and coverage for drugs the patient is prescribed.
But perhaps the most complicated part is billing for care: After a patient receives treatment, the provider prepares a bill, submits it to the insurance company, and the insurer processes the bill. All of these problems are challenging to measure, since measurement requires data, and data require administrative capacity.
In a recent BFI working paper, my co-authors and I used rich new data on the billing process to uncover the costs of complex insurance payments. We study two significant costs: the resources consumed by the billing process itself, and the process’ impact on patients’ access to care.
Doctors and insurers often have trouble determining exactly what treatments and procedures a patient’s insurance covers, and at what prices, until after the physician provides treatment. This ambiguity leads to costly billing and bargaining processes after care is provided, which we call the costs of incomplete payments (CIP). We estimate these costs across insurers and states and show that CIP have a major impact on Medicaid patients’ access to medical care.
Our data come from nearly 90 million patient visits from 2013 through 2015. Each visit generates one or more claims that the physician submits to an insurer, and the data include the details of each claim and the insurer’s response. This granular information on each interaction between the physician and insurer allows us to estimate a model to determine the costs of the process. By assuming physicians make rational decisions about whether to resubmit a denied claim, in light of the costs of that claim, we can estimate the costs of the billing process. We find that payment frictions are particularly large when treating Medicaid patients.
Medicaid is a key part of the US social safety net, but rarely provides an equal quality of care as other types of insurance. Medicaid patients often have trouble finding physicians willing to treat them. Medicaid plans often restrict the services they cover, and frequent changes in patients’ eligibility make it hard to establish regular patterns of care. They have limited provider networks, which has generally been attributed to the plans’ low payment rates.
We show that the payment complexity is at least as important as payment rates themselves. We find that 25 percent of Medicaid claims have payment denied for at least one service upon doctors’ initial claim submission. Denials are less frequent for Medicare (7.3 percent) and commercial insurers (4.8 percent).
How do these denials affect physician revenues? CIP incorporates two concepts: foregone revenues, which are directly measured in the remittance data; and the estimated billing costs that providers accumulate during the back-and-forth negotiations with payers. Putting these together, we estimate that CIP average 17.4 percent of the contractual value of a typical visit in Medicaid, 5 percent in Medicare, and 2.8 percent in commercial insurance. These are significant losses, especially considering the relatively low reimbursement rates Medicaid offers in the first place.
If an insurance scheme has low reimbursement rates and obtaining payment requires a great deal of effort, it won’t be attractive to doctors. Since CIP reduce the share of expected revenue doctors collect, they are analogous to a tax: a ten percentage point increase in CIP affects a doctor’s bottom line just like a tax increase of ten percentage points.
We study whether CIP affect doctors’ willingness to treat Medicaid patients. To do this, we examine physicians who move across states. An implicit tax increase of ten percentage points reduces physicians’ probability of accepting Medicaid patients by 1 percentage point. This effect is even larger across states within a physician group. Each standard deviation increase in CIP reduces Medicaid acceptance by 2 percentage points.
In short, our work reveals the importance of well-functioning business operations in the provision of health care. The key insight, that difficulty with payment collection compounds the effect of low payment rates to deter physicians from treating publicly insured patients, should give policymakers pause.
That said, our work does not mean that insurers or Medicaid programs are the only source of problems in the billing process. There are many valid reasons to deny claims: insurers must combat fraud and ensure that care is appropriate. But the costs that this billing process imposes on the health care system are large in magnitude and consequential for patients. The health care system must strive to achieve these goals while reducing the administrative burden on patients, providers, and insurers.
Editor’s note: A version of this article appeared as a BFI Research Finding.
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