By: Victoria Brazil (@SocraticEM)
Let’s talk about simulation. (again 😊)
Not the kind where mannequins lie pristine in an air-conditioned skills lab while facilitators tweak scenario scripts over coffee. But integrated simulation – at the frontline of maternity care in rural Tanzania. The kind that doesn’t stop when the debrief is over, because the actual system is still broken. The kind that is embedded in healthcare quality improvement (QI), not adjacent to it.
Enter the Safer Births Bundle of Care.
Recently published in the New England Journal of Medicine, this massive, multi-year program in Tanzania demonstrates how simulation – when deeply embedded in a multifaceted QI strategy – can drive real, measurable outcomes: a nearly 20% reduction in perinatal mortality across 30 facilities and five regions, with over 280,000 births included. That’s not a typo. This is simulation doing the work.
So, what can we learn from it?
- Simulation as More Than Education
The Safer Births Bundle is a four-pronged approach:
- Innovative simulation-based training
- Continuous data-driven quality improvement
- Clinical tools for better monitoring and response
- Scalability and sustainability strategies
What’s striking is that simulation wasn’t a “module” or an “intervention”—it was the connective tissue. Simulation was the mechanism for skill acquisition, but also for team communication, systems learning, data interpretation, and cultural change.
Training used NeoNatalie Live and MamaNatalie simulators and redesigned clinical devices from Laerdal Global Health – not just as one-off workshops but for frequent, in situ drills, facilitated by local champions. Team simulations weren’t a “refresher”; they were how staff learned to link fetal heart monitoring anomalies to actionable change, how they rehearsed managing postpartum hemorrhage in the absence of fancy tech or ideal staffing. This was low-cost, high-frequency, high-functioning simulation.
- Closing the Gap Between Data and Action
Every week, facility teams received clinical outcome data—referrals, Apgars, PPH rates—and training participation metrics. Simulation sessions were then tailored to address those specific gaps.
This is what many of us dream about when we talk “learning health systems.” Imagine your simulation content changing dynamically based on real-time outcomes. That’s what they did. When data flagged that neonatal deaths weren’t declining in Tabora, facilitators dug deeper into late referrals and shifted training priorities. When teams noticed gaps in foetal monitoring uptake, simulation scenarios drilled into device usage under pressure.
This is the Circle of Learning in action: data → training → care → data. Simulation wasn’t the intervention; it was the operating system.
- Local Leadership, Not Outsider Expertise
Facilitators were trained through “SimBegin”—a basic but effective facilitator development course. Then, local champions took the reins. They didn’t just “run sim.” They coached peers, analyzed data, advocated for system fixes, and adjusted training content. They were agentic, not administrative.
Too often, we fly in well intentioned international educators to teach “resuscitation” and then leave without addressing the oxygen supply or the broken suction. Here, the simulation team was the QI team was the clinical team. That’s the integration we talk about in conferences but rarely achieve.
- Outcomes that Actually Matter
The numbers are compelling:
- Perinatal mortality fell from 15.3 to 12.5 per 1000 births
- Neonatal death within 24 hours dropped by almost 40%
- Maternal mortality fell from 240 to 60 per 100,000 births ( a 75% reduction!)
And no, not all metrics improved. Intrapartum stillbirths didn’t change—highlighting areas where simulation can’t fix structural gaps like delayed decision-to-delivery intervals or limited access to C-sections. But that’s also a lesson: simulation can spotlight system failures, not just train around them.
So What Does This Mean for Us?
For clinician educators and sim enthusiasts: this is our call to embed, not decorate.
Simulation shouldn’t be a fly-in, fly-out activity. It should be tied to local QI agendas, adapted to data trends, and facilitated by people embedded in the system. If we’re serious about outcomes – especially in low-resource or high-pressure settings – then simulation has to be part of a continuous learning loop, not an educational sidebar.
Not all of us can achieve these kinds of outcomes, but let’s keep asking:
- How might our simulation change a clinical outcome?
- How can we use data from our own system?
- Will we run it again next week, and the week after, until it’s no longer needed?
The Safer Births Bundle of Care didn’t just improve outcomes. It redefined what it means for simulation to be truly integrated into health systems improvement.
Victoria
Note – Stylised version of neonatal resuscitation using upright BVM and NeoBeat. Image generated by ChatGPT
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