Background and aim: Health workforce productivity is one of the key determinants of efficiency, quality, and sustainability in healthcare systems. The present study aimed to analyze thematic clusters, identify temporal trends, and explore emerging research areas in studies related to health workforce productivity.
Materials and methods: All articles published in the field of health workforce productivity and indexed in the Scopus database up to May 13, 2025, were identified through advanced search using a predefined search strategy. Bibliographic data, including titles, abstracts, and keywords, were extracted. The extracted files from Scopus were imported into VOSviewer in a compatible format for data collection and analysis. Data analysis was performed using VOSviewer software, employing a keyword co-occurrence approach. Keywords with a minimum occurrence of 15 times were included. After data cleaning, 145 keywords and 5,465 links were analyzed across six clusters using scientometric visualization maps, including density, network, and overlay visualizations.
Findings: The findings demonstrated that the concepts related to health workforce productivity were mainly concentrated in four major thematic clusters: mental health and job performance, organizational-managerial dimensions, education and empowerment, and economic-financial factors. Temporal trend also revealed a shift from traditional managerial and structural approaches toward greater emphasis on job satisfaction, burnout, quality of work life, and workforce support in recent years.
Conclusion: Health workforce productivity is a multidimensional phenomenon that arises from the interplay of several key factors, including employee mental well-being, effective management practices, professional training and capacity building, and economic support mechanisms. Therefore, interventions aimed at reducing burnout, increasing job satisfaction, and optimizing the work environment may serve as essential strategies for enhancing the productivity of healthcare personnel.
Type of Study:
Orginal |
Subject:
Scientometrics Received: 2026/02/24 | Revised: 2026/09/1 | Accepted: 2026/09/6 | ePublished: 2026/09/13