The Hidden Cost of Obstetric Care and How AI Can Mitigate It
Last Updated: April 2, 2025
Author: Sam Hessami, MD, MHA, FACOG, FACHE
For many expectant parents, the cost of childbirth remains a mystery until the hospital bill arrives. The hidden costs of obstetric care—ranging from global payments with built-in financial limitations to inefficiencies in charge capture—create a healthcare system where hospitals are often underpaid, patients are left with unexpected bills, and insurers struggle to align costs with quality outcomes.
As the U.S. healthcare system shifts toward value-based care, hospitals and payers must find ways to improve efficiency, reduce waste, and ensure fair reimbursement for maternal health services. Artificial Intelligence (AI) is emerging as a powerful tool to help optimize financial processes, improve pricing transparency, and ensure that hospitals receive accurate reimbursement for the essential services they provide.
Global Payment for Obstetrics: A One-Size-Fits-All Model with Limitations
Most obstetric care in the U.S. is reimbursed through a global payment model, where insurers provide a single, bundled payment to cover prenatal care, labor and delivery, and postpartum visits. While this model simplifies billing and encourages providers to manage costs effectively, it has significant drawbacks:
Limitations of Global Payments in Obstetrics:
Does not reflect the true complexity of care – A high-risk pregnancy requiring additional monitoring, specialist consultations, or a NICU stay is reimbursed at the same rate as a low-risk, uncomplicated birth.
Fails to account for unexpected complications – Obstetric emergencies such as preterm labor, postpartum hemorrhage, or C-section complications drive up hospital costs, yet the global payment remains fixed.
Encourages cost-cutting rather than care optimization – Some hospitals may reduce services or avoid high-risk patients to remain profitable under a fixed-payment system.
How AI Can Help:
AI-driven risk stratification can predict which pregnancies are likely to require additional interventions, helping hospitals negotiate adjusted payments based on patient complexity rather than a flat fee.
AI-powered clinical documentation automation ensures that every aspect of maternal care is accurately recorded, allowing for better justification of additional reimbursement when complications arise.
Value-Based Care in Obstetrics: What It Means for Patients and Payers
The transition from fee-for-service to value-based care (VBC) in maternity care aims to reward providers for quality outcomes rather than the number of services provided. This shift impacts both patients and payers in several ways:
For Patients:
1. More comprehensive prenatal and postpartum care – Value-based models incentivize hospitals to invest in preventive care and reduce adverse maternal outcomes like hemorrhage or sepsis.
2. Lower out-of-pocket costs – As unnecessary interventions decrease and efficiency improves, patients may see fewer surprise bills and better cost predictability.
3. Enhanced maternal health equity – VBC models focus on reducing disparities in care by addressing social determinants of health that contribute to poor outcomes.
For Payers (Insurance Companies & Government Programs):
1. Lower long-term costs – Preventing maternal complications reduces expensive hospital stays, readmissions, and NICU utilization.
2. Data-driven reimbursement – AI can analyze maternal health trends to determine which interventions truly improve outcomes, ensuring payment models reward quality over quantity.
3. Fewer unnecessary interventions – Hospitals are incentivized to use evidence-based protocols, reducing costs associated with unnecessary C-sections and prolonged hospital stays.
How AI Can Help:
AI-driven predictive analytics can identify patients at high risk for complications, allowing for targeted interventions that improve outcomes and reduce costs.
AI-powered remote patient monitoring (RPM) can track maternal health outside the hospital, ensuring early detection of complications before they escalate into expensive emergencies.
The Lack of Price Transparency in Obstetric and Maternity Care
One of the biggest financial challenges in obstetrics is the lack of price transparency. Many patients do not know the cost of prenatal care, delivery, or postpartum care until they receive a bill.
Why is Pricing Opaque?
Hospitals and insurers negotiate complex, variable rates – The same procedure may have vastly different costs depending on the hospital, provider, and insurance contract.
Unbundled services create confusion – While global payments cover the basics, additional charges for epidurals, C-sections, NICU stays, and postpartum complications are often billed separately.
No standardized pricing model – Unlike elective procedures, maternity care pricing fluctuates based on factors beyond the patient’s control (e.g., emergency interventions).
How AI Can Help:
AI-powered pricing transparency tools can analyze historical claims data to provide patients with accurate cost estimates before delivery.
AI-driven billing automation can help hospitals ensure accurate charge capture, reducing unexpected patient bills and improving reimbursement efficiency.
Charge Capture Inefficiencies: A Hidden Cause of Hospital Underpayment
A major financial issue facing hospitals is inefficiencies in charge capture—the process of documenting and billing for all services provided. Obstetric care is particularly affected by missed charges, leading to underpayment from insurers.
Why is Charge Capture Inefficient in Labor and Delivery?
1. Unbilled services: Some procedures, such as emergency interventions during labor, are performed but not properly documented, leading to lost revenue.
2. Failure to link complications to billing codes: If complications like postpartum hemorrhage or sepsis are not coded correctly, hospitals may receive only base-level reimbursement instead of adjusted payments.
3. Delayed documentation: In busy L&D units, providers often enter medical records after care has been delivered, increasing the risk of missed or inaccurate billing.
How AI Can Help:
AI-driven natural language processing (NLP) tools can scan medical records in real-time, identifying services that should be billed but may have been overlooked.
AI-powered automated charge capture systems can detect missing charges and ensure appropriate billing codes are applied, preventing revenue loss.
AI can predict potential denials from payers by analyzing past claims, allowing hospitals to proactively correct billing issues before submission.
Conclusion: AI is Reshaping the Financial Future of Obstetrics
The hidden costs of obstetric care are placing a financial strain on hospitals, insurers, and patients alike. The limitations of global payments, inefficiencies in charge capture, lack of pricing transparency, and the shift to value-based care are all challenges that demand innovative solutions.
AI-driven financial management tools can ensure hospitals are fairly reimbursed for maternity care.
Predictive analytics can improve patient outcomes, reducing costly complications.
Automated billing and documentation tools can enhance charge capture, preventing underpayment.
Price transparency AI tools can empower patients with cost estimates before they give birth.
As AI continues to evolve, it has the potential to redefine the economics of maternal healthcare, ensuring that hospitals remain financially sustainable while delivering high-quality, accessible, and equitable care for all mothers.
Would you like to see how AI can be implemented in your hospital or healthcare system? The future of affordable, transparent, and efficient maternity care starts today.
Contact us today for a demo and discover how the Birth Model can empower your team while enhancing patient safety and satisfaction!
