malpractice Archives - The Imaging Wire

We all know it happens – medical imaging scans of questionable clinical value, performed not to improve patient diagnosis but to defend clinicians in the event of malpractice litigation. A new study in AJR supports the idea that defensive medicine is driving up imaging use by finding a link between malpractice reform and lower emergency imaging utilization.

The proliferation of imaging technology throughout the healthcare enterprise – and especially in the emergency setting – gives clinicians a powerful tool that’s just too tempting not to use.

Head CT scans can quickly rule out patients who might have a hemorrhagic stroke, for example, while cardiac CT angiography is showing its value for working up patients with chest pain.

But with great power comes great responsibility. Unnecessary imaging not only drives up healthcare costs but can expose patients to additional radiation as well as complications from working up suspicious findings.

Medical-legal experts speculate that malpractice reform through tools such as damage caps could tamp down defensive medicine by limiting physicians’ legal exposure to lawsuits in the event they make a mistake.

In the new study, researchers from the ACR’s Harvey L. Neiman Health Policy Institute tested the idea by analyzing 630k Medicaid encounters for patients with headache presenting to the emergency department in 2019.

They then correlated head and neck imaging volume to various factors that could influence utilization, including whether states had implemented tort reform.

Their analysis discovered that emergency imaging utilization was less likely to occur…

In states with laws on “several liability” (in which parties are only responsible for their own share of damages) (OR = 0.68).
In states with malpractice damage caps (OR = 0.79).
In states with greater mean malpractice payment (although the effect size was minimal; OR = 0.99).

A couple other interesting findings included…

Referring physicians other than emergency medicine were far more likely to order more imaging (OR = 8.45).
Facilities with fewer than 100 beds were less likely to order imaging (OR = 0.65).

The Takeaway

The new findings linking malpractice reforms with lower emergency imaging use confirm what many of us have already suspected. Whether they lead to health policy reforms remains to be seen.

What impact will artificial intelligence have on the legal liability of the radiologists who use it? A new study in NEJM AI suggests that medical malpractice juries may pass harsher judgment on radiologists when they make mistakes that disagree with AI findings.

AI is viewed as a technology that can save radiologists time while also helping them make more accurate diagnoses.

But there’s a dark side to AI as well – what happens when AI findings aren’t correct, or when radiologists disagree with AI only to discover it was right all along?

In the new study, a research team led by Michael Bernstein, PhD, of Brown University queried 1.3k U.S. adults on their attitudes toward radiologists’ legal liability in two clinical use cases for AI – identifying brain bleeds and detecting lung cancers.

Participants were asked if they felt radiologists met their duty of care to patients across different scenarios, such as whether the AI and the radiologist agreed or disagreed on the original diagnosis.

Responses were compared to a “no AI” control scenario in which respondents assessed legal liability if radiologists hadn’t used AI at all, with researchers finding …

If radiologists disagreed with AI, more respondents found radiologists liable …
- Brain bleeds: 73% found radiologist liable (vs. 50% with no AI)
- Lung cancer: 79% found radiologist liable (vs. 64% with no AI)

If both radiologists and AI missed the diagnosis, there was no statistically significant difference …
- Brain bleeds: (50% vs. 56% with no AI, p=0.33)
- Lung cancer: (64% vs. 65% with no AI, p=0.77)

Respondents were less likely to side with plaintiffs when given information about standard AI error rates …
- When AI agreed with the radiologist diagnosis:
  - Brain bleeds: (73% plaintiff agreement fell to 49%)
  - Lung cancer: (79% fell to 73%)
- When AI disagreed with the radiologist diagnosis:
  - Brain bleeds: (50% plaintiff agreement fell to 34%)
  - Lung cancer: (64% fell to 56%)

The Takeaway

The new study offers a fascinating look at AI’s future in radiology from a medico-legal perspective. But there’s one question the researchers didn’t address: If AI-supported image interpretation eventually becomes the standard of care, will radiologists be found liable for not using it at all? Stay tuned.

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