Bibliometric Analysis and ChatGPT-Assisted Identification of Key Strategies for Improving Primary Maternity Care Based on a Decade of Collective Research
Sidik Maulana, Muhammad Iqhrammullah, Rovy Pratama, Sydney Tjandra, Intan Chaharunia Mulya, Hartiah Haroen
Abstract
Maternity care within primary health facility settings is critical for reducing maternal and neonatal mortality in Indonesia. The aim of this study was to analyze research trends over the past decade to identify key strategies for improving maternity care in primary health care facilities in Indonesia. A bibliometric analysis was conducted using data from the Scopus database to map the research landscape and identify latent research topics in maternal health care. The analysis included keyword co-occurrence and network visualization, with assistance from ChatGPT-4.0 for enhanced identification and categorization of keywords. The identified research trends were used as surrogate variables representing the main concerns among researchers, experts, and funders. These variables were used to build strategies, which were then analyzed using SWOT (Strengths, Weaknesses, Opportunities, and Threats) by reflecting on the Indonesian context. The results revealed that key topics in maternity care included midwifery roles, pandemic resilience, and telemedicine. Based on SWOT analysis, most of the constructed strategies were found to have high external opportunities but low internal capabilities, indicating the need to strengthen internal resources. In conclusion, Indonesia must enhance its internal capabilities, particularly human resources and infrastructure, to effectively utilize external opportunities and improve maternal health outcomes.