Category: Hospitals

When Blue Cross Blue Shield recently published research suggesting that hospitals use artificial intelligence tools to extract more money from insurers without providing additional care, people were mad. Amid growing concerns about AI, one glimmer of hope has been its potential to improve health — and yet, here it was: inflating health care costs without yielding any benefits.

As a doctor who has used the kinds of tools being criticized, I’m frustrated, too: We can document honestly and still wind up inflating hospital bills. This is because comorbidities function as an on-off switch with respect to billing, even though they affect patient care in nuanced ways.

Although the problem warrants a systemic fix, the best short-term solution is for hospitals to create more nuanced documentation tools, and for clinicians to exercise judgment when using them.

What did the research show?

BCBS suggested hospitals are using automated tools to document secondary diagnoses — like anemia, malnutrition, and low sodium — which allow them to charge more for caring for these patients.

For instance, a patient might be admitted for diverticulitis (primary diagnosis), but found on post-op labs to have acute blood-loss anemia (secondary diagnosis). Hospitals can use these secondary diagnoses to label a patient as having a comorbidity or a complication, allowing them to bill more for the hospitalization, whether or not they treated the patient’s anemia. These “bump codes” have cost BCBS hundreds of millions of dollars over the past two years, and these costs are presumably passed along to patients in the form of higher premiums.

BCBS claims that bump coding has become more widespread because hospitals are using AI tools to identify secondary diagnoses. Automated tools can skim a patient’s chart and prompt physicians to document that the patient is, for instance, anemic, and what they are doing about it.

Are doctors to blame?

A few weeks after I started medical residency, I began getting emails from hospital administrators I had never met, whose signatures said they were risk adjustment specialists. The emails were generic and polite, advising me to review clinical documentation integrity (CDI) queries on inpatients I was caring for. If I didn’t respond quickly, the request would be forwarded to the attending physician supervising me. A typical CDI query would point out that my note hadn’t commented on, say, a patient’s low sodium level, and would ask me to document that they had low sodium and what (if anything) we were doing about it.

Like most residents, I was already spending far more time on my computer than I was with my patients. Soon, CDI queries streamed into my inbox with such regularity that I turned to a more senior doctor to ask how I might stave them off. That doctor showed me an automated tool that I could include in my notes. This tool would assess a patient’s lab results, automatically detect any additional diagnoses a patient had (like anemia, malnutrition, or low sodium), and prompt me to specify whether we were monitoring, evaluating, or treating.

I assumed it was lucrative to the hospital for me to document these diagnoses (why else would they be paying risk adjustment specialists to email me about them?), but we almost always were at least monitoring the secondary diagnosis in question, and I accurately documented as much.

Including this tool’s outputs in my notes kept the risk adjustment specialists from hounding me and won me back several minutes of each day — enough time to poke my head into a patient’s room before I went home, or call a patient’s family member to give a quick update. I always answered the questions included in my tool honestly, but in the back of my mind, I wondered whether I was doing my patients a disservice: Was I inflating the cost of their hospitalizations without actually improving their care?

Where bump codes come from

In general, hospitals are reimbursed for hospitalizing patients on the basis of diagnosis-related groups, or DRGs. DRG payments are set by the Centers for Medicare and Medicaid Services by analyzing claims data. (Medicare uses DRGs to set payments, while many commercial insurers, including BCBS, use the DRG system to negotiate reimbursement rates with hospitals.) Let’s say a patient is admitted with diverticulitis requiring surgery (typically billed as DRG 331 if there are no complications). CMS has estimated how much it usually costs to care for one of these patients and insurers prospectively pay hospitals on that basis; a hospital generally won’t get reimbursed more for keeping the patient longer, administering more drugs, placing more IVs, and so on.

However, some hospitals care for sicker patients than others. The typical diverticulitis patient at a tertiary medical center in a poor area will require more support than a diverticulitis patient at a community hospital in an affluent area. The government does not want to penalize hospitals that see more complex patients, and so it allows hospitals to seek additional reimbursement forcomorbidities or complications that increase the cost of their care.

This is where bump codes come from: Hospitals can bill more complex diverticulitis admissions as DRG 330, which is reimbursed at a higher rate. Not all comorbidities or complications count: In 2007, the last time DRGs were substantially changed, CMS analyzed claims data and used this analysis to decide which conditions qualify and set reimbursement rates. CMS pays hospitals more for patients with conditions like low sodium because it has found that it costs hospitals more to care for these patients (perhaps because they tend to be hospitalized longer and more often require ICU admissions).

However, although CMS adjusts DRG payments from year to year, the list of bump codes hasn’t been overhauled in nearly two decades.

Bump codes can help identify complex patients and ensure hospitals are paid more for caring for them. These are good things, in part because they reduce hospitals’ incentive to seek out healthier, more advantaged patients. While BCBS claims that hospitals are increasingly using these codes to bill more without actually providing more care, hospitals would presumably counter that they were being insufficiently reimbursed before, and that their coding is accurate. After all, the BCBS study does not claim that hospitals are engaging in fraud; the question is just whether the lab abnormalities hospitals are billing for warrant higher reimbursements.

So who’s right?

This issue boils down to the following question: How much more does it cost to care for a patient with a secondary condition, and do current coding rules accurately reflect this?

The answer is that it depends. For instance, not all low sodium levels are created equal. If a patient briefly has a sodium level that falls below the normal range, but their sodium immediately corrects once they’re able to eat again, they probably don’t require any additional resources, and hospitals shouldn’t be reimbursed more for caring for them.

By contrast, a patient with dangerously low sodium levels requiring an ICU stay, frequent lab checks, and carefully titrated IV fluids undoubtedly does use more resources.

This leaves doctors in a tough spot: Risk adjustment specialists ask us to document real diagnoses that we know could increase the cost of a patient’s bill, but we have no idea by how much. Moreover, there’s no medical school module on how much any of these comorbidities affects the true cost of the hospitalization. Against this backdrop, it makes sense that doctors try to just tell the truth: yes, this patient has low sodium, and we are monitoring it, even though this probably allows hospitals to code some patients as being more resource-intensive than they truly are.

What we can agree on

This entire enterprise — risk adjustment specialists spamming doctors, who are already nose-deep in documentation burden, to document diagnoses that often do not affect patient care, while insurers publish reports that fail to capture the nuance of the issue, leaving the public angry and confused — highlights a more general problem with respect to how the U.S. health care system works.

By design, hospitals and insurers are meant to compete with each other, with hospitals trying to collect as much money as they can for providing care, and insurers trying to pay as little as possible. Hospitals bolster their side by hiring risk adjustment specialists and employing AI tools, while health insurers hire payment integrity specialists and employ different AI tools.

Patients lose out because the administrative bloat inflates the cost of medical care, while making costs less transparent and harder to contest. Ultimately, the fix should be structural: At a minimum, we need to overhaul the list of secondary conditions that are eligible for bump coding. CMS attempted to do this in 2019, when it proposed downgrading or eliminating many bump codes based on new data showing they were not associated with increased costs. But hospitals pushed back, and the effort eventually stalled.

What should we do in the meantime?

Secondary diagnoses are supposed to be billed only when they are clinically significant — for instance, when they require further evaluation, treatment, diagnostic procedures, or monitoring. But in practice, the bar for clinical significance is probably lower than it should be. (Even rechecking a lab may qualify as monitoring.) Accordingly, I suspect the BCBS study is tracking a real problem, and that much of the documentation of secondary diagnoses isn’t linked to patient complexity.

Early in residency, I was caring for an immunosuppressed patient who kept spiking fevers. My colleagues and I wondered whether he might have an indolent infection lurking somewhere and ordered an echocardiogram to rule out endocarditis. His heart valves showed no signs of bacterial growth, but trace backflow was detected across one of his valves, a finding present in most people.

Soon, I received a CDI query inviting me to document his valve dysfunction in my note. I did not do this, because his incidental valve finding was irrelevant to his hospitalization. Instead, I typed out a response indicating as much. However, it would have been easier and quicker to click through the check boxes, and, despite answering them honestly, potentially inflate the patient’s bill.

At least some CDI tools built into electronic medical records — including the one I have used — default to including secondary diagnoses in ways that are likely to lead to bump coding. One way to improve the status quo would be to ensure that such tools give physicians the option to document whether a secondary diagnosis is clinically significant or not, rather than simply asking them how they are addressing it (on the presumption that it is clinically significant).

Hospitals should build such tools, and regulators should ensure they do. In the meantime, I’ll exercise clinical judgment when using my CDI tool — if the low sodium seems important, I’ll document it, and if it doesn’t, I’ll politely decline when a risk adjustment specialist invariably asks me to.

Leah Pierson is a resident physician.