Human resource management research in healthcare: a big data bibliometric study

Qin, Xiaoping; Huang, Yu-Ni; Hu, Zhiyuan; Chen, Kaiyan; Li, Lin; Wang, Richard Szewei; Wang, Bing-Long

doi:10.1186/s12960-023-00865-x

Cited by 5 publications

(2 citation statements)

References 32 publications

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“…By selecting individuals who fit the company's needs and values, organizations can increase the likelihood that employees will continue to contribute and develop in the long term (Yücel, 2022). Big Data is an effective tool for establishing the accuracy of employee selection and creating a solid foundation for the growth and sustainability of human resources in organizations (Qin et al, 2023). Companies can optimize the recruitment process thanks to big data.…”

Section: Accuracy Of Employee Selectionmentioning

confidence: 99%

Big Data Analysis in Human Resources Decision Making: Optimizing Workforce Management

Heliana,

Wahyuni

2024

jrmsi

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This research aims to conduct an in-depth analysis of the application of Big Data in human resource decision-making, focusing on optimizing workforce management. By measuring four main variables, namely recruitment efficiency, accuracy of employee selection, employee development, and organizational performance based on HR decision-making—Big Data analysis is expected to provide a deeper understanding of workforce dynamics. The research results show that applying Big Data can build recruitment efficiency, increase the accuracy of employee selection, support more appropriate employee development, and ultimately improve overall organizational performance. Big Data makes organizational performance based on HR decision-making by providing a solid foundation for more effective human resource management strategies. This research uses qualitative methods with the help of the NVivo 12 Plus tool to identify research results. Implementing Big Data in various aspects of human resource management is recognized as a catalyst for positive change in workforce management.

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Section: Accuracy Of Employee Selectionmentioning

confidence: 99%

Big Data Analysis in Human Resources Decision Making: Optimizing Workforce Management

Heliana,

Wahyuni

2024

jrmsi

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“…Health facilities, both public and private, are expected to improve the quantity, quality, and accessibility of the healthcare services they provide, while having to operate within limited financial resources [5]. Thus, one important issue to examine is the allocation of staff resources in health centers, as well as how they can be used more effectively to enhance patient outcomes [6]. Indeed, the impact of the structure of the hospital staffing on medical practices should be studied, in order to establish, if necessary, appropriate staffing standards for hospitals.…”

Section: Introductionmentioning

confidence: 99%

Staff Resources in Public and Private Hospitals and Their Implication for Medical Practice: A French Study of Caesareans

Zbiri,

Rozenberg,

Milcent

2024

Healthcare

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This study aimed to investigate the effect of hospital staffing resources on medical practice in public versus private hospitals. We used exhaustive delivery data from a French district of 11 hospitals over an 11-year period, from 2008 to 2018, including 168,120 observations. We performed multilevel logistic regression models with hospital fixed or random effects, while controlling for factors known to influence obstetric practice. We found that hospital staff ratios of obstetricians and that of midwives affected caesarean rates, but with different effects depending on the hospital sector. In public hospitals, the higher the ratio of obstetricians and that of midwives, the lower the probability of planned caesareans. In private hospitals, the higher the ratio of obstetricians, the greater the probability of planned caesareans. Indeed, in public hospitals, obstetricians and midwives, both salaried employees, do not have financial or organizational incentives to perform more caesareans. In private hospitals, obstetricians, who are independent doctors, may have such incentives. Our results underline the importance of having an adequate supply of health professionals in healthcare facilities to ensure appropriate care, with specific regard to the different characteristics of the public and private sectors.

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The impact of the scale and hierarchical structure of health human resources on the level of medical services-based on China’s four major economic regions

Chen,

Yang,

Zhu

et al. 2024

Int J Equity Health

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Background Ensuring that the scale and hierarchical structure of health human resources are rational, and that medical services are efficient and fair, is an important task of practical significance. On this basis, examining the impact of health human resources on the level of medical services presents a new and formidable challenge. This study aims to delve into how the scale and hierarchical structure of health human resources in China’s four major economic regions affect the fairness and efficiency of medical services, and to identify optimization strategies. Methods This study utilizes provincial panel data from China’s four major economic regions spanning the years 2009 to 2021. Initially, it provides a statistical description of the current state of health human resources and the level of medical services. Subsequently, it employs a fixed-effects model to analyze the impact of the scale and hierarchical structure of health human resources, as well as their interactive effects, on the fairness and efficiency of medical services, and discusses the interactive mechanisms between medical service fairness and medical service efficiency. Furthermore, after conducting a comprehensive evaluation of the level of medical services using the entropy weight method, it explores the regional heterogeneity and temporal dynamics in the influence of the scale and hierarchical structure of health human resources on the level of medical services. Finally, the study examines the scientific validity and rationality of the research findings through various robustness checks, including the substitution of research variables and models. Results The study found that the scale of health human resources has a promoting effect on the equity of medical services (β ≤ 0.643, p ≤ 0.01), but exhibits an inhibitory effect on the efficiency of medical services (β ≥ -0.079, p ≤ 0.1); the hierarchical structure of health human resources shows a positive impact on both the equity and efficiency of medical services (βequity ≤ 0.160, p ≤ 0.01; βefficiency ≤ 0.341, p ≤ 0.05); at the same time, the results indicate that the interactive effect of the scale and hierarchical structure of health human resources promotes equity in medical services (β = 0.067, p ≤ 0.01), but restricts the efficiency of medical services (β ≥ -0.039, p ≤ 0.01); the mechanism by which health human resources affect the level of medical services in China’s western and northeastern regions is more pronounced than in the central and eastern regions; after the implementation of the “Healthy China 2030” Planning Outline, the role of health human resources in the level of medical services has been strengthened; in the robustness tests, the model remains robust after replacing the core explanatory variables, with R2 maintained between 0.869 and 0.972, and the dynamic GMM model test shows a significant second-order lag in the level of medical services (βequity ≤ 0.149, p ≤ 0.01; βefficiency ≤ 0.461, p ≤ 0.01); the channel test results prove that managerial personnel and other technical personnel are key pathways in regulating the impact of medical staff on the level of medical services. Conclusion This study provides an in-depth analysis of the impact of health human resources on the level of medical services, revealing that both the scale and hierarchical structure of health human resources significantly affect the equity and efficiency of medical services. Furthermore, the influence of health human resources on the level of medical services exhibits regional heterogeneity and temporal characteristics. Robustness tests ensure the scientific validity and robustness of the research conclusions. This provides effective references for optimizing the allocation of health human resources and improving the level of medical services.

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Human resource management research in healthcare: a big data bibliometric study

Cited by 5 publications

References 32 publications

Big Data Analysis in Human Resources Decision Making: Optimizing Workforce Management

Big Data Analysis in Human Resources Decision Making: Optimizing Workforce Management

Staff Resources in Public and Private Hospitals and Their Implication for Medical Practice: A French Study of Caesareans

The impact of the scale and hierarchical structure of health human resources on the level of medical services-based on China’s four major economic regions

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