Abstract
Background: Industry 4.0 (I4.0) technologies have improved operations in health care facilities by optimizing processes, leading
to efficient systems and tools to assist health care personnel and patients.
Objective: This study investigates the current implementation and impact of I4.0 technologies within maternal health care,
explicitly focusing on transforming care processes, treatment methods, and automated pregnancy monitoring. Additionally, it
conducts a thematic landscape mapping, offering a nuanced understanding of this emerging field. Building on this analysis, a
future research agenda is proposed, highlighting critical areas for future investigations.
Methods: A bibliometric analysis of publications retrieved from the Scopus database was conducted to examine how the research
into I4.0 technologies in maternal health care evolved from 1985 to 2022. A search strategy was used to screen the eligible
publications using the abstract and full-text reading. The most productive and influential journals; authors’, institutions’, and
countries’ influence on maternal health care; and current trends and thematic evolution were computed using the Bibliometrix R
package (R Core Team).
Results: A total of 1003 unique papers in English were retrieved using the search string, and 136 papers were retained after the
inclusion and exclusion criteria were implemented, covering 37 years from 1985 to 2022. The annual growth rate of publications
was 9.53%, with 88.9% (n=121) of the publications observed in 2016-2022. In the thematic analysis, 4 clusters were
identified—artificial neural networks, data mining, machine learning, and the Internet of Things. Artificial intelligence, deep
learning, risk prediction, digital health, telemedicine, wearable devices, mobile health care, and cloud computing remained the
dominant research themes in 2016-2022.
Conclusions: This bibliometric analysis reviews the state of the art in the evolution and structure of I4.0 technologies in maternal
health care and how they may be used to optimize the operational processes. A conceptual framework with 4 performance
factors—risk prediction, hospital care, health record management, and self-care—is suggested for process improvement. a research
agenda is also proposed for governance, adoption, infrastructure, privacy, and security.