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Safety and Health for Medical Workers
Published by PT Inovasi Analisis Data
ISSN : 30479460     EISSN : 30483786     DOI : https://doi.org/10.69725/shmw.v2i4
Core Subject : Health,
Health Professions Medicine & Pharmacology Nursing Public Health
AAt Safety and Health for Medical Workers (SHMW; P-ISSN: 3048-3786, E-ISSN: 3047-9460), we measure the value of research not by indexation alone, but by credible novelty, methodological rigor, and demonstrable benefit to frontline practice. High indexing can amplify dissemination, yet it is secondary to evidence that reduces exposure, strengthens infection prevention, improves ergonomics, and supports psychosocial well-being across healthcare settings. We therefore prioritize manuscripts that propose bold, testable ideas; report transparent methods and reproducible analyses; and translate findings into implementable solutions for workers, institutions, and policymakers. We welcome implementation studies, mixed-methods designs, replications, and well-documented null or negative results, alongside open data/code and stakeholder co-design. Our commitment is simple: if research does not meaningfully improve safety and health at work, it remains incomplete regardless of ranking. We invite authors who share this purpose to advance actionable science with SHMW.
Arjuna Subject : Profesi Kesehatan - Profesi Kesehatan (Lain-Lain)
Articles 5 Documents
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Search results for , issue "Vol. 1 No. 2 (2024): July" : 5 Documents clear
Nurse View on Improving Occupational Safety and Health in the Hospital Environment Sefinez Muzena; Ozvitruk Mitoulaf
Safety and Health for Medical Workers Vol. 1 No. 2 (2024): July
Publisher : Inovasi Analisis Data

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69725/shmw.v1i2.115

Abstract

Objective: This study aimed to identify the specific risks experienced by nurses, the safety measures in place and how they perceived its effectiveness at preventing falls from taking place which helped to identify areas for improvement when enhancing healthcare workers welfare. Methods: A structured questionnaire was administered to collect data on socio-demographics, specific sector employment types, safety practices and occupational risks. Trends were explored using percent distributions, means and chi-squared tests for independence where appropriate.Findings: The study found that OHS conditions in a University teaching hospital are noticeably different from a private hospital. Nurses in private sector hospitals had better working conditions also with the improved safety standards, comprehensive safety training and ergonomic design which was accredited by JCI. On the other side hospital nurses encountered poor safety leads, ergonomic deficiencies, and high rates of occupational diseases and injuries. University hospitals had more psychological stress, burnout, and job dissatisfaction than private hospitals; however, in terms of infection control they fared better compared to private hospitals who, although carrying out consistent monitoring programmes for PPE, were hindered with shift fatigue and stress.Novelty: This study offers a comparison of OHS conditions for nurses in private and public health care facilities and highlights the potential role of international accreditation for safer working environments. This has shone light on a long-neglected safety issue in academic hospitals.Research Implications: The study findings are expected to help policy amendments, labor protection policies for civil servants in university hospitals, NABH accreditation processes and monitoring of safety training and ergonomic improvements in both private sector hospital environments and public healthcare establishments.
Radiation to Chemicals Unpacking Occupational Safety Hazards in Educational Hospital through the HOSHRA Lens Kavi Magsoudhi; Abbasi Haghighat
Safety and Health for Medical Workers Vol. 1 No. 2 (2024): July
Publisher : Inovasi Analisis Data

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69725/shmw.v1i2.116

Abstract

Objective: The current study evaluates occupational safety and health risks in educational hospitals using the Hoshra index by concentrating on the detection and control of frequent hazards.Methods: Using a structured approach, the HOSHRA index classifies risks in to physical, chemical, biological, ergonomic and psychological domains. The framework supports targeted risk scoring, improving the efficiency with which hospitals can allocate resourcesFindings: The analysis uncovers important types of healthcare worker hazards. Biological and psychological risks appear to be particularly suboptimal, emphasizing the importance of effective infection control interventions, as well as psychological care. The study underscores the need to have a culture of safety that supports hazard reporting and management.Novelty: This is one of the first to use the HOSHRA index in many educational hospital, introducing new methods for risk analysis and assessment beyond traditional classic styles.Research Implications: The results highlight the need for adapted and risk based strategies in healthcare settings. Healthcare organizations can improve the well-being of staff and, by extension, patient care outcomes, by aligning safety protocols with the unique features of wards.
Assessment of Occupational Health and Safety Management System Implementation in General Hospital Hastiti Lestari; Lutfi Nasrifah
Safety and Health for Medical Workers Vol. 1 No. 2 (2024): July
Publisher : Inovasi Analisis Data

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69725/shmw.v1i2.117

Abstract

Objective: This study aims to assess the application of Occupational Health and Safety Management System (OHSMS) in Kertosono Regional General Hospital by identifying the obstacles and strategies that exist, as well as successful system implementation for health sector.Methods: This study utilized a mixed-methods design to assess OHSMS effectiveness and employee perceptions before and after implementation.Findings: Results show a statistically significant decrease in incidents at work after implementation of an OHSMS, which confirms that the global safety performance of this plant is affected by the OHSMS. By contrast, though inadequate instruction, lack of continuous leadership dedication and investment were some major obstacles to successful operation of OHSMS.Novelty: The findings from this study suggest the importance of structured safety management systems designed for public healthcare workers, and provide practical suggestions to bolster the effectiveness of OHSMS in Indonesia.Research Implications: The results also emphasize the importance of ongoing education and training, strong leadership support, as well as providing sufficient resources to promote a culture of safety in healthcare settings. Future research might instead seek upper bounds benefit of an OHSMS for safety or examine how technology can be integrated to provide monitoring, training function on a continuous basis.
Leveraging Machine Learning to Enhance Occupational Safety and Health in Hospital Saydrine Conica; Nikova Browne; Robert Danyll
Safety and Health for Medical Workers Vol. 1 No. 2 (2024): July
Publisher : Inovasi Analisis Data

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69725/shmw.v1i2.150

Abstract

Objective: This study focuses on utilizing Machine Learning (ML) approaches to improve Occupational Safety and Health (OSH) performance, involving the prediction and prevention of risks based on data.Methods: Analysis of a dataset of 550 OSH incident reports from Metax Cancer Hospital (2019–2023) was conducted using descriptive and inferential statistics. Machine Learning algorithms including decision trees, random forests, and support vector machines were used for prediction and evaluation of OSH results. The models were evaluated using various performance metrics such as accuracy, precision, recall, and AUC.Findings: The analysis made key observations on both workplace environmental factors, safety protocols, and incident occurrence. The ML models demonstrated high prediction performance, with random forests achieving the best accuracy in terms of the correct classification of OSH events. These findings highlight the promise of ML to improve the safety performance of hospitals.Novelty: We propose an original contribution of an ML integration process towards OSH improvement in the hospital ecosystem also characterized with complex safety challenges for which predictive analytics can yield substantial risk mitigation.Research Implications: The study proposes a spillover framework for establishing hospital safety intelligence systems that combines data-driven techniques with traditional OSH management structures. It also highlights the role of real-time predictive analytics in improving OSH outcomes. The study demonstrates the ability of ML to facilitate predictive risk assessment and improve safety.
REDECA Framework Enhancing Occupational Safety and Health Through Artificial Intelligence Applications Sheila Michiel; Isabelle Moissact; Christopher Sean
Safety and Health for Medical Workers Vol. 1 No. 2 (2024): July
Publisher : Inovasi Analisis Data

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69725/shmw.v1i2.151

Abstract

Objective: This paper aims to show how REDECA Reengineering Delphi and Evaluation can be integrated with Artificial Intelligence (AI) in a way to increase the influence of AI on Occupational Safety and Health (OSH) by further advancing the risk identification process, the prevention of injuries, and the compliance with safety standards.Methods: A quantitative cross-sectional study method was used through multiple regressions analysis for the relationships between AI application, risk identification, injury reduction, safety culture, and compliance. Organizational safety culture was explored further as a moderator influencing the effectiveness of AI in OSH systems.Results: AI enhances the identification and prediction of risk, resulting in a significant reduction in workplace injuries and fatalities. AI-enabled applications ensure higher adherence to safety protocols and helped in building a time-tested safety culture. In fact, organizational safety culture improves the effectiveness of AI, serving as a vital moderating factor that facilitates lasting advancements in workplace safety practices. This points to the relationship between technological innovation and organizational influences on better OSH outcomes.Novelty: This study presents an original integration of AI-driven predictive safety mechanisms through the REDECA framework, highlighting the moderating role of safety culture. This serves as a bridge between technology adoption and organizational behavior to advance workplace safety strategies.Research Implication: The findings provide a roadmap to organizations to not just invest in AI-based safety systems but also to inculcate a strong safety culture to reap the rewards of technical advances. This research sends a message to the fostering of the AI integration as a transformative approach for OSH management, which aims for the sustainable improvements in workplace safety, risk mitigation and employed well-being for the policymakers and the industry leaders.

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