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Population health management (PHM) has emerged as a pivotal strategy in healthcare, aiming to address the health needs of communities while enhancing care quality and outcomes. Recent years have witnessed a surge in research at the intersection of data analytics and public health interventions within the realm of PHM. This paper presents a comprehensive bibliometric analysis of the literature on data analytics and public health interventions in the context of population health management. Through systematic data collection from reputable scholarly databases and rigorous analysis, this study aims to map out the trends, key contributors, and emerging themes shaping the discourse in this domain. The analysis encompasses publication trends, authorship patterns, citation metrics, and network visualizations to provide insights into the landscape of literature. Notable findings include a high citation rate per paper and author, indicative of scholarly interest and collaboration within the research community. Key themes identified include outcomes, interventions, population health improvement, determinants, and health disparities. Additionally, temporal analysis reveals a shift towards non-communicable diseases and the increasing role of data in patient care. The author collaboration network highlights a core cluster of researchers with extensive collaborative ties, alongside peripheral authors and topics representing specialized or nascent areas. The density visualization map identifies potential areas for future research, including health disparities, women's health issues, and geographic-specific studies.
Judijanto et al. (Tue,) studied this question.