Repeat after me: the C-section rate is not a measure of quality


“The operation was a success but the patient died.”

It’s an old joke, but there’s an element of truth to it. Technical prowess in providing medical care is meaningless if the patient does not survive and get better. In medicine outcome is far more important than process.

That’s why efforts to reduce C-section rates are terribly misguided. C-section is a process and measuring rates tell us nothing about the quality of obstetric care. If we want to measure the quality of the care we need to look at perinatal and maternal mortality (outcomes), but that’s hard. So insurers and public health authorities have made a much easier (and potentially lethal) decision. They’re going to measure the C-section rate, then punish hospitals and providers who don’t meet an optimal rate.

According to Southern California Public Radio:

[pullquote align=”right” cite=”” link=”” color=”#FF111E” class=”” size=””]Soon we’ll be able to say, “The vaginal birth was a success but the baby died.”[/pullquote]

California’s health insurance exchange will use the threat of exclusion from its approved provider networks as a way to motivate hospitals and doctors to reduce the number of medically unnecessary Cesarean sections.

Beginning in 2019, insurance companies that contract with Covered California must either exclude from their networks any hospitals that don’t meet the federal government’s 2020 target C-section rate or explain why they aren’t, according to the new contract approved by the exchange’s board last week…

“This is going to catch people’s attention and focus the considerable quality improvement activities of hospitals on this area,” says Dr. Elliott Main, medical director of the California Maternal Quality Care Collaborative.

But there is a very large, indeed a deadly problem with this approach. The C-section rate is NOT and has never been a measure of quality.

In other words, we’re soon going to be able to say, ‘The vaginal birth was a success, but the baby died.’

Medicine is practiced one on one. A health care provider cares for each individual patient with her specific history, symptoms, physical examination and laboratory values in mind.

How do we know if the provider gave the best possible care?

Did the patient survive? Did she get well? If not, the people caring for her failed. Perhaps no one could have done better, but it is a failure nonetheless.

We can measure healthcare quality in the aggregate, of course. We can look at mortality rates and morbidity rates in response to specific treatments, but that tells us nothing about whether each patient got the treatment she needed and no one got treatment that they didn’t need.

Medicine is both art and science.

It is firmly grounded in science, of course, but there are large gaps in our knowledge (what causes cancer? what causes pre-eclampsia? what causes schizophrenia?) and those gaps are bridged by the art of medical care.

I learned that practicing obstetrics. One incident in particular is burned into my memory. I was on call one evening when a patient phoned to say that she was 25 weeks pregnant and had noticed pain running up the inside of her leg for the past two days. I advised her to meet me at the hospital for an exam because I wanted to make sure that she didn’t have a blood clot in her leg (deep venous thrombosis or DVT).

Pregnancy is a hypercoagulable state, meaning that pregnant women are more prone than average to develop blood clots. Blood clots in the leg are not dangerous in themselves, but pieces can break off and get stuck in the lung circulation. That’s known as a pulmonary embolus and it has a very high death rate.

The patient came in and I examined her leg; she had none of the many potential signs associated with DVT, but when I asked her to point out where she felt the pain, she traced the exact path followed by the vein on its way from her foot to her thigh. I was suspicious despite very little clinical evidence so I asked the radiologist to scan her leg … and he refused!


He explained that the insurance company was trying to reduce the incidence of emergency DVT scans to “improve quality” and he would not get reimbursed for a negative scan. We argued and I ultimately threatened to write in the chart that he was refusing a scan that I thought necessary and if the patient died, he should be held responsible.

He gave in and he found that she had a blood clot so extensive that it extended from her ankle to deep in her pelvis. It almost certainly would have killed her had it not been immediately treated with blood thinners.

A measure designed to improve “quality” inevitably led to poor quality care, because measuring process is not a substitute for measuring outcome.

That’s especially true for C-sections. Except in rare instances (massive hemorrhaging, for example) we have literally NO WAY to determine in advance whether a woman is going to need a C-section. We have NO WAY to predict if her baby is definitely suffering from oxygen deprivation. We have NO WAY to predict if a breech baby is going to die if delivered vaginally. We have NO WAY to tell if a woman with a previous C-section will rupture her uterus (potentially killing her baby) if she tries for a vaginal delivery in a subsequent pregnancy.

What’s the optimal C-section rate? We don’t know.

For years the World Health Organization recommended an “optimal” C-section rate of 10-15% despite the fact that the countries with low perinatal and maternal mortality rates had an average C-section rate of 22% and rates as high as 42% were consistent with excellent outcomes.

A recent study found the a minimum C-section rate of 19% is necessary to ensure low rates of perinatal and maternal mortality. There is precious little evidence that higher rates are dangerous.

That hasn’t stopped public health officials from pretending that they know the optimal C-section rate. In the case of low risk pregnancies:

The federal government has set a goal of reducing C-sections in these low-risk situations to 23.9 percent by 2020. The national rate was 26.9 percent in 2013, according to the Centers for Disease Control and Prevention.

Such specificity ought to mean that public health officials can tell us IN ADVANCE exactly which C-sections made up the 3% difference, but they have literally no idea.

And if they can’t tell in advance, how will obstetricians be able to tell?

They won’t.

Obstetricians will have to guess, risking the lives of individual babies and mothers, leading inevitably to preventable deaths.


Repeat after me: the C-section rate is not a measure of quality!