Background: For healthcare delivery to be optimally effective, health systems must possess adequate levels and we must ensure a fair distribution of human resources aimed at healthcare facilities. We conducted a scoping review to map the current state of human resources for health (HRH) in India and the reasons behind its shortage.
Methods: A systematic search was conducted in various electronic databases, from the earliest available date till February 2024. We applied a uniform analytical framework to all the primary research reports and adopted the "descriptive-analytical" method from the narrative paradigm. Inductive thematic analysis was conducted to arrange the retrieved data into categories based on related themes after creating a chart of HRH problems.
Results: A total of 9675 articles were retrieved for this review. 88 full texts were included for the final data analysis. The shortage was addressed in 30.6% studies (n = 27) whereas 69.3% of studies (n = 61) addressed reasons for the shortage. The thematic analysis of data regarding reasons for the shortage yielded five kinds of HRH-related problems such as inadequate HRH production, job dissatisfaction, brain drain, regulatory issues, and lack of training, monitoring, and evaluation that were causing a scarcity of HRH in India.
Conclusion: There has been a persistent shortage and inequitable distribution of human resources in India with the rural expert cadres experiencing the most severe shortage. The health department needs to establish a productive recruitment system if long-term solutions are to be achieved. It is important to address the slow and sporadic nature of the recruitment system and the issue of job insecurity among medical officers, which in turn affects their other employment benefits, such as salary, pension, and recognition for the years of service.
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http://dx.doi.org/10.1186/s12889-024-18850-x | DOI Listing |
BMC Oral Health
January 2025
Departments of Community Oral Health, School of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Background: Different countries have varying dental specialities, shaped by diverse factors. The determinants influencing the development of these specialities differ between developed and developing countries. This study aimed to explore the factors contributing to the establishment of dental specialities in Iran, a developing country with a wide range of recognised dental specialities.
View Article and Find Full Text PDFBMC Med Educ
January 2025
Research Center for Environmental Determinants of Health, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Aims: This study evaluates both financial and non-financial preferences of nursing students to choose a hospital for work in future.
Background: In Iran's healthcare system, the persistent shortage and uneven distribution of nurses have been significant challenges. Addressing such issues requires attention to nurses' preferences, which can be instrumental in designing effective interventions.
BMC Health Serv Res
January 2025
School of Library and Information Management, Emporia State University, Emporia, KS, USA.
Background And Purpose: Despite the increasing integration of information technologies in healthcare settings, limited attention has been given to understanding technostress among health practitioners in hospitals. This study aims to assess the prevalence of technostress creators among health practitioners and explore potential factors contributing to its occurrence, with the ultimate goal of informing strategies to mitigate its impact.
Method: Data were collected through a validated questionnaire administered to health practitioners at Tehran Apadana Hospital in Iran.
BMC Neurol
January 2025
Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, School of Medicine, College of Medicine, National Sun Yat-Sen University, No. 123 Ta-Pei Road, Niao-Sung Dist, Kaohsiung, 83305, Taiwan.
Background And Purpose: White matter hyperintensities in brain MRI are key indicators of various neurological conditions, and their accurate segmentation is essential for assessing disease progression. This study aims to evaluate the performance of a 3D convolutional neural network and a 3D Transformer-based model for white matter hyperintensities segmentation, focusing on their efficacy with limited datasets and similar computational resources.
Materials And Methods: We implemented a convolution-based model (3D ResNet-50 U-Net with spatial and channel squeeze & excitation) and a Transformer-based model (3D Swin Transformer with a convolutional stem).
Nat Med
January 2025
Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, WA, USA.
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