Obstetric ultrasound (OBUS) plays a pivotal role as part of antenatal care for pregnant individuals worldwide. A recent global survey aims to illuminate how OBUS is being utilized across low- and middle-income countries (LMIC) and assesses perceptions surrounding the promising development of artificial intelligence (AI)-assisted OBUS technologies. The study, involving 176 respondents from 34 countries, sheds light on the current state of OBUS and highlights priorities for enhancing maternal care through AI.
Conducted from November 27, 2023, to May 31, 2024, the survey attracted healthcare professionals, predominantly from LMIC regions, including physicians, nurses, midwives, and ultrasound technicians. It aimed to provide insights on OBUS training, access, and its applications, particularly focusing on how AI could facilitate improved outcomes for pregnant individuals. A significant 85% of respondents reported having access to ultrasound facilities within their clinical settings, underscoring its importance.
Despite the WHO recommending OBUS to assess gestational age and monitor fetal health, the implementation of these ultrasound services often faces challenges. The barriers to access stem from issues related to infrastructure, qualified personnel, and financial constraints. Most respondents expressed high confidence and expertise in their OBUS capabilities, with 77% reporting feeling confident about their ultrasound skills. OBUS was primarily used for assessing gestational age, fetal viability, and presentation, with these functions standing out as top priorities for AI assistance.
Importantly, 98% of survey participants agreed OBUS contributes significantly to improving quality of care. Access to ultrasound was recognized as critically important by 84% of the respondents, illustrating its role as not merely adjunctive but central to effective maternal healthcare.
While there remains enthusiasm for AI's role, with over half of the participants believing it would be frequently or always useful, reservations persist. Of those expressing concerns about AI-assisted OBUS, nearly three-quarters worried about healthcare providers potentially misunderstanding the technology. Other fears included misdiagnosis and associated costs. This highlights the necessity to address these apprehensions and manage the integration of AI responsibly and sustainably.
The findings of this survey are significantly encouraging, signaling the potential for AI to revolutionize OBUS practices even as they must be tempered with caution and thorough consideration of the healthcare environment. Enhancing access and training for healthcare workers remains key to successful integration, ensuring AI serves as a facilitator for improved maternal and fetal health rather than as a replacement for trained professionals.
Protective measures should also be prioritized to mitigate risks associated with integrating AI, such as data privacy concerns and technology misapplication. The urgency for research and development around AI-assisted OBUS products is apparent, and with careful targeting and engagement with stakeholders, significant strides could be made to bridge the gap between modern technology and clinical practice.
Conclusively, the study encapsulates both the promising applications of AI-assisted OBUS and the intrinsic challenges faced within the healthcare systems of LMICs. A concerted effort to overcome these challenges could pave the way for transformative improvements to obstetric care, reinforcing the commitment to ensuring every pregnant individual receives the quality care they deserve.