Gillian Chowassociate professor of management and organizations at the Kellogg School, and Carlos Inoue of the University of Illinois at Urbana–Champaign used real-world data to show how one strategy—creating a formal, specialized role—can help address this task-sharing challenge.
Chown and Inoue based their research on real-world data collected from hospitals—an environment that has long interested Chown. She and Inoue realized they could access a wealth of healthcare data from Brazil, where Inoue grew up.
They focused on maternity wards in Brazilian hospitals, where the creation of a new, specialized role—the obstetric nurse—has led to significant changes in the way hospitals assign patients to health care providers. The researchers found that this new role helped hospitals match patients with health care providers whose expertise matched the patients’ level of medical risk. Improved matching, in turn, was associated with better outcomes for mothers and newborns.
The lesson is that simply having the right expertise on your team isn’t necessarily enough, according to Chown. “You have to pay attention to how that expertise is used,” he says. “How do we ensure tasks are allocated to the right person in the right way?”
Reforms in maternal care
More than two million babies are born in Brazil each year and, historically, many of these children have been delivered by caesarean section. Between 2007 and 2012, for example, about 50 percent of all births were by caesarean section. “There is a lot of controversy about what right The caesarean section rate is, but most would agree that [Brazil’s] it’s higher than you might expect,” Chown says.
In a national effort to reduce the rate of caesarean sections, Brazil’s public health care system has introduced the role of the specialist obstetrician-nurse in some (though not all) of its hospitals over the past two decades. Midwives were formally trained and certified specialists who could manage vaginal deliveries without a doctor, although they were not allowed to perform C-sections.
Prior to this effort, all births in Brazilian public hospitals, whether vaginal or caesarean, were performed by physicians. The specific physician assigned to a patient, however, depended on who was on staff when the patient arrived. But this process changed when midwifery nurses were added to the degree. While doctors in hospitals with obstetric nurses still managed some vaginal deliveries, they no longer managed all of them. Instead, when an expectant mother came, the hospital would assign the patient to either a doctor or an obstetrical nurse.
Learning this new nurse-midwife role encouraged Chown and Inoue to study the broader implications of this specialization. While many people had previously studied specialization in the context of coordination challenges (such as how to get specialists to work well on tasks together), Chown says, “nobody had really talked about this idea that task-allocation The problem also becomes more difficult.”
They realized that the challenge hospitals now face in deciding which patients should see doctors versus obstetricians—and whether patients ultimately end up with providers whose expertise matches their needs, an outcome the researchers call the “professional-client match”—would give them the perfect opportunity to study this process themselves.
15 million births
Chown and Inoue’s dataset represented more than 15 million births between 2012 and 2022 and included detailed information on mothers, health care providers and hospitals.
To understand how well patients were matched with providers, researchers divided patients into three levels (low, medium, or high) based on how risky their deliveries were. They then assigned the doctors and midwives to different groups (low-risk specialists, generalists or high-risk specialists) based on the types of cases they had done in the past. Since vaginal deliveries tended to be more common for lower-risk pregnancies, obstetric nurses tended to see more lower-risk patients, but still ended up with patients across the spectrum.
Because Chown and Inoue could see which patients ended up with which doctors or nurses, they could determine, for example, whether low-risk patients were paired with low- or high-risk specialists—and how those pairings changed over time. They were also able to run a control simulation that randomly assigned each day’s patients to the providers who were actually on shift that day, giving them a baseline against which to compare real-world results.
Shocking results
The researchers found that before the introduction of midwifery nurses, patient assignment was basically as good as random.
“That was shocking,” says Chown. “Even though they had doctors who specialized in lower-risk births or specialized in high-risk births, they weren’t using it effectively. The expertise was there, but it was kind of invisible.”
But with the addition of the new specialized role, things changed. With providers officially divided into two visible categories, matching improved by 9.6 percentage points, representing a 30 percent increase from the average. Chown notes that about 60 percent of that increase reflects the changed mix of providers and patients in the pool — the mechanical effect of adding a new role. But the remaining 40 percent (about 3.9 percentage points) reflects something more: After adopting the new role, hospitals steered patients to appropriate providers better than luck, in a way they hadn’t before.
“What he did is he created a role that he was visible and explicitly focused on low-risk births,” says Chown. “So then that pathway became workable in a way that it wasn’t before.”
Chown and Inoue were particularly excited to find that this improvement in patient-provider matching was associated with better health outcomes for mothers and children, including fewer complications and shorter hospital stays. The magnitude of the effect is modest, but comparable to other obstetric care interventions studied by researchers, such as midwifery continuum of care models.
Ripe for further exploration
Moving forward, Chown is interested in seeing if she can find similar kinds of improvement in other medical specialties, such as cardiology, while learning more about the hospital’s triage process. “It would be ripe to dig more, go to the triage team at a hospital and understand how they actually make these decisions,” says Chown.
However, the researchers acknowledge that not every organization will benefit from creating specialized roles.
Predictable workflows also increased the impact of the specialized role. When hospitals could predict incoming cases, they could plan assignments in advance and match patients to specialties purposefully, rather than reactively assigning whoever happened to be available. Similarly, hospitals with more organizational experience, where health care providers were more familiar with established workflows or systems within the hospital, also showed stronger results at baseline, although this declined as hospitals with less experience reached time.
Collectively, these additional findings suggest that “you can’t just do an intervention, see that it works somewhere, and then decide it’s going to work for you,” Chown says. “You have to think about what characteristics of the organization or the environment are actually required to support this positive effect.”
