Using Real-Time Data to Accelerate Improvement in Maternal Outcomes 

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 C-section Collaborative Hero
Case Study

Using Real-Time Data to Accelerate Improvement in Maternal Outcomes 

From 2025-2026, IHI, with support from Merck for Mothers, partnered with state Perinatal Quality Collaboratives (PQCs) in Alabama and Iowa to test the use of a real-time, automated data platform. When paired with quality improvement (QI) coaching and support, access to this data allowed teams to accelerate improvement and achieve success in reducing NTSV (nulliparous, term, singleton, vertex) C-section rates.  

Impact at a Glance: Reducing Unnecessary C-Sections

69%

of participating hospitals reduced NTSV C-section rates within one year

55%

of delivering providers improved their individual C-section rates

46%

of participating hospitals achieved the Healthy People 2030 target of 23.6%

27.1% → 25.2%

Reduction in the aggregate average NTSV C-section rate across participating hospitals in one year

IHI's role:

  • Led the development of the Collaborative change package and measurement plan
  • Conducted the execution of the 12-month Collaborative
  • Supported hospital teams with data review and analysis to guide decision-making
  • Led monthly action period webinars and Collaborative Learning Sessions
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Nichole Shockley

RNC-OB, BSN, Director of Labor & Delivery, Huntsville Hospital for Women & Children

RNC-OB, BSN, Director of Labor & Delivery, Huntsville Hospital for Women & Children

We were able to actually define and present the supporting data to stakeholders, instead of going off of assumptions.

– Jennifer Mewes

RN, OB Navigator, Iowa Specialty Hospitals and Clinics

RN, OB Navigator, Iowa Specialty Hospitals and Clinics

Providers are more willing to accept the data in this format. They are more engaged and asking questions.

Amanda Doering

BSN, RN, Quality Improvement RN, Obstetric Initiatives, Alabama Perinatal Quality Collaborative

BSN, RN, Quality Improvement RN, Obstetric Initiatives, Alabama Perinatal Quality Collaborative

As a new PQC coach, I gained a wealth of knowledge on how to use data analysis tools. IHI’s education and support has aided me in creating run charts, translating data into measurable action, and using graphed metrics to report on quality improvement progress.

The Challenge 

State PQCs are the main avenue through which birthing hospitals engage with QI initiatives focused on improving maternal and infant outcomes. However, PQCs struggle to obtain accurate and timely data from their participating hospitals, which hinders their ability to provide focused, meaningful coaching and to understand if improvement initiatives are successful. Hospitals participating in state-led initiatives often struggle to collect and analyze data, slowing down their improvement efforts. Manual data collection and analysis take meaningful time away from testing and implementing best practices that could improve care delivery and outcomes.

The Goal

The goal of the Collaborative was for participating hospitals to reduce their NTSV C-section rates to the Healthy People 2030 goal of 23.6% by September 2026. 

 Additionally, the Collaborative aimed to demonstrate:  

  • The ability of hospitals to accelerate improvement and more rapidly achieve results when they have access to real-time data  

  • The impact of an automated data dashboard on alleviating the burden of manual data collection for hospitals and PQCs 

  • The ability of this tool to support the PQCs in providing more focused coaching to hospital teams 

The Approach

The PQCs in Alabama and Iowa partnered with IHI to support the testing and implementation of evidence-based interventions with a high degree of belief from the AIM Safe Reduction of Primary C-section change package. Hospitals ranging from large academic medical centers to small, critical access rural hospitals participated in a 12-month BTS Collaborative and used a real-time data tool called AdaptX to track key metrics. AdaptX connects to the hospital's electronic medical record (EMR) to automatically pull data into a real-time dashboard using control charts. Participants attended monthly calls and three Learning Sessions over the course of the year as part of the Collaborative. IHI and PQC coaches provided monthly coaching around data analysis and using QI tools to test evidence-based changes based on learning from the data. 

Results

We found that access to real-time automated data paired with QI coaching and training could remove barriers, allow for more focused QI efforts, and accelerate improvement. Hospitals more easily identified the root causes of C-sections occurring in their facilities and tailored tests of change to address those challenges. The AdaptX platform allowed data to be stratified by demographic categories and by delivering provider, further highlighting areas of improvement for specific groups and individuals.  

At the end of the Collaborative, 9 out of 12 participating teams (1 hospital dropped out due to L&D unit closure) had reduced their NTSV C-section rate. 6 of the 12 hospitals lowered their rates to below the Healthy People 2030 goal (23.6%), with 3 additional hospitals each a few percentage points away from the target (25%-27%). In addition, 48 out of 88 (55%) delivering providers at participating hospitals achieved measurable improvements in their individual C-section rates. In the aggregate, the Collaborative was able to collectively lower the average NTSV C-section rate from 27.1% at the beginning of the Collaborative to 25.2% at the end of 12 months.  

We estimate that this reduction resulted in approximately 96 fewer C-sections across participating hospitals over 1 year. Lower C-section rates have an impact across the system, including:  

  • Patient outcomes: C-sections carry roughly three times the risk of severe maternal morbidity due to the risk of infection and bleeding, and impact future pregnancies resulting in higher rates of placenta accreta.  

  • Financial implications: C-section delivery is estimated to cost the health system about $13,300 more than a vaginal delivery. Using this calculation, 96 fewer C-sections would save the health system approximately $1.3M. There are also downstream savings for health systems resulting from fewer surgical site infections, transfusions, and 30-day readmissions.  

  • Staffing and capacity implications: We estimate that 96 fewer C-sections would result in approximately 140 bed days returned to postpartum units, as a C-section delivery increases postpartum stays by about 1.5 days per birth. A reduction in C-sections also impacts operating room availability, anesthesia staffing, and nursing hours needed for recovery.  

Aggregate Data

Average NTSV C-Section rate for all Participating Hospitals  

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Aggregate Collaborative: Line chart showing a slight overall decline in NTSV C-section rates, approaching the 23.6% goal.

Individual Hospital Data 

Methodist Jennie Edmundson Hospital  

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Methodist Jennie Edmundson: Line chart showing variable NTSV C-section rates, averaging 25.25%, with recent improvement.

Iowa Specialty Hospital  

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Iowa Specialty Hospital: Line chart showing fluctuating NTSV C-section rates, averaging 32.02%, with recent improvement below the 23.6% goal.

DCH Regional Hospital  

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DCH Regional Hospital: Line chart showing fluctuating NTSV C-section rates, averaging 31.3%, above the 23.6% goal.

Learnings 

The Collaborative was successful because of several core elements that were part of our design: 

  • Belief in the data: because data came from a reputable 3rd party source, providers felt the data was more reliable and were less likely to refute or deny it  
  • Data accessibility: data was easily accessible and did not require chart reviews or audits; teams could then design tests of change and specific projects based on the data  
  • Coaching: Teams received 1:1 coaching from IHI on how to interpret their data and use QI methods to test changes
  • Structure: the BTS Collaborative guided teams, provided a framework, and created accountability  
  • Content: an evidence-based change package that had been validated and used across multiple settings led to high degree of belief in the changes   

Partners

This initiative was a partnership between IHI and three other organizations who each provided critical support and knowledge to the project:  

  • AdaptX: data platform, support for platform implementation, coaching and training for hospital teams on using the platform and viewing data 

  • National Institute for Children’s Health Quality (NICHQ): support for PQC recruitment and application process, development of the Collaborative online portal, project evaluation leadership 

  • Alabama PQC (ALPQC) and Iowa Perinatal Quality Care Collaborative (IPQCC): hospital recruitment, engagement, and coaching  

This project was supported by funding from Merck, through Merck for Mothers, the company’s global initiative to help create a world where no woman has to die while giving life. Merck for Mothers is known as MSD for Mothers outside the United States and Canada.