Artificial Intelligence (AI) is changing many fields, including healthcare. In the United States, obstetric care has seen some changes due to AI. Medical practice leaders, owners, and IT managers need to understand how AI affects clinical decisions, patient outcomes, and workflow to plan well. This article looks at recent research and how AI is used in obstetrics and gynecology (OB-GYN). It also talks about how AI affects clinical work and patient care.
Artificial Intelligence helps healthcare workers make clinical decisions by quickly analyzing large amounts of data accurately. In obstetrics, people often call AI “augmented intelligence” because it supports healthcare providers rather than replaces them.
One important study is the PERFORM Study by Canio Martinelli MD, Antonio Giordano MD, and others. They compared how well AI large language models (LLMs) like ChatGPT-01-preview, GPT4o, and Claude Sonnet 3.5 diagnosed cases versus OB-GYN residents. They used 60 clinical cases in English and Italian. AI was more accurate than residents—73.75% versus 65.35%. The best AI models reached 88.33% accuracy, and language differences did not affect results much.
AI performed better under stress, such as when time was limited, while residents’ accuracy dropped from 73.2% without time pressure to 56.5% under pressure. Early-career residents got the most help from AI, with a nearly 30% boost in accuracy. This shows AI can help newer doctors make better diagnoses and reduce mistakes caused by tiredness or heavy workloads.
For administrators and IT managers, these results suggest that adding AI tools can help make diagnoses more consistent and reduce staff stress. This is very important in busy hospitals and clinics where quick and correct decisions affect mothers and babies.
AI is used for more than just decision support. It helps with several clinical tasks that affect patient care directly.
These uses of AI match recommendations by the American College of Obstetricians and Gynecologists (ACOG). ACOG suggests adding new data to electronic health records (EHRs), like anxiety, depression checks, and breastfeeding plans. They see AI as a way to improve care quality and fairness for many patients.
Adding AI to obstetric care has challenges. A study on moral distress among clinicians using AI decision tools showed ethical worries. Clinicians felt uneasy when AI advice clashed with their own judgment. Some feared AI might miss important patient details.
This moral distress comes from three main reasons:
Researchers suggest AI developers work closely with clinicians in designing these tools. This makes sure AI fits clinical work, respects culture, and meets ethical rules. Tools designed this way are easier to accept and trust, which is important for safe use.
AI is also used to automate workflows in obstetric care. This helps with managing practices, administrative jobs, and boosts efficiency, which is useful for administrators and IT staff.
Practice leaders should know that adding AI means changing not just technology but also the culture of the team. Training and support are needed to make sure staff can use AI tools well and safely.
Healthcare managers and clinic owners see clear benefits from AI in obstetric care.
Along with these benefits, it is important to know AI’s limits and ethical issues. Administrators must balance spending on AI with good staff training, protecting patient privacy, and ongoing checking of how well AI tools work.
Obstetric care in the United States is changing as AI grows. Hospitals and clinics that add AI carefully can improve clinical decisions and patient care while solving operational issues. AI tools that help doctors and handle administrative jobs offer ways to increase quality, speed, and access to care for mothers and babies nationwide.
Health information technology (HIT) refers to electronic systems health care professionals use for processing, storing, retrieving, and sharing health information, including electronic health records (EHRs), imaging tools, decision support systems, telemedicine, and AI.
HIT enhances patient care through improved direct engagement via patient portals, remote monitoring, telehealth services, and mobile apps that enable tracking of health and fetal development, ultimately improving health outcomes.
AI assists in clinical decision-making, personalized medicine, improving maternal and fetal outcomes, and reducing administrative burdens, thereby enhancing diagnostic accuracy and patient health outcomes.
AI improves diagnostic accuracy in ultrasound and MRI, helping detect congenital abnormalities and distinguishing various fetal brain conditions, thus facilitating early and accurate diagnosis.
AI analyzes real-time data from cardiotocographs to monitor fetal heart rate and contractions, helping health care professionals identify patterns and deviations, and providing insights into fetal health.
AI evaluates vital signs and lab tests to detect early signs of complications like preeclampsia and gestational diabetes, enabling timely interventions through real-time monitoring and trend analysis.
AI models analyze biological markers and imaging data to identify high-risk pregnancies and predict complications like preterm birth, providing actionable insights for health care practitioners.
AI algorithms enhance the identification of cancerous cells, reduce diagnostic errors, and support personalized treatment plans, improving early detection and tailored therapies for cancer patients.
ACOG monitors AI’s impact on practice management and administrative burdens while collaborating with the AMA on regulatory discussions to ensure effective integration into clinical practice guidelines.
ACOG recommends adding new data elements, such as anxiety and depression screening and breastfeeding intention, to obstetric EHRs to enhance care quality and promote maternal health research.
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