Indonesian Journal of Medicine, Health and Nursing

The Role of Nurses in Occupational Health Services within Federal Government Institutions: A Review of Policy and Practice

Ajesha Musa Paul — Sun, 01 Mar 2026 00:00:00 +0700

Occupational health services (OHS) play a significant role in protecting the physical, psychological, and even social health of people who work in federal government institutions. The nurses take center stage in the provision of these services, but their roles, policy frameworks, and practice dilemmas are under-researched, especially in resource-constrained areas such as in Nigeria. This scoping review conducted with the help of PRISMA synthesized information about peer-reviewed studies, policy reports, and official reports that were published during the period of 2016-2025 to evaluate the roles of nurses in federal occupational health services. Results show that occupational health nurses are involved in multidimensional roles such as health promotion, disease prevention, monitoring hazards, risk assessment, emergency response, compliance with regulations, and psychosocial support. Although policy frameworks like the National Occupational Health Policy (2016) and the WHO guidelines (2022) offer an organized structure of roles, gaps in implementation can still be noticed because of the resources, workforce limitations, and insufficient institutional support. The paper identifies the increasing demands of broader preventive and leadership functions, the introduction of digital health solutions, and active participation in the emerging occupational issues, such as psychosocial stressors and ergonomic hazards. Practical implications focus on the importance of capacity building, professional development, and organizational support in order to maximize nurse-led interventions. Some of the policy recommendations are improving the enforcement mechanisms, defining the duties of the nurses, and synchronizing the institutional structures with international best practices. The review highlights that workforce health, organizational sustainability, and sustainable service delivery to federal institutions depend on the role of occupational health nursing. To address the policy-practice gap and capitalize on a culture of both preventive and holistic occupational health care, nurse-led OHS must be improved with specific policies, training, and infrastructure investment.

Integrating Bioinformatics Coding Labs into Medical and Public Health Facilities

Moses Adeolu AGOI, Samuel Olayiwola AJAGA, Oluwanifemi Opeyemi AGOI — Thu, 12 Mar 2026 00:00:00 +0700

The blistering development of genomic medicine, digital health systems and data-driven public health surveillance has left an immediate requirement of computational literacy in healthcare settings. The idea of bioinformatics has become central in the current clinical research, disease surveillance, and precision medicine but most institutions do not have the practical training infrastructures needed to use the tools efficiently. This paper examines how to incorporate bioinformatics coding laboratories in medical and public health institutions as a way of improving the capacity to analyse and conduct translational research. The study provides the literature review of 2009-2024, which means that directly practical project-oriented learning and Python and R code exercises enhance the interpretation of biological data significantly. Results indicate embedded laboratories can cut the pathogen analysis time by 33 percent and better prediction of outbreaks by 28 percent. Moreover, these centres lead to interdisciplinary teamwork, and the institutions indicate that there is a 42 percent rise in the number of joint projects. The paper offers a conceptual framework on how to create such labs and stresses the importance of having high-performance computing, cloud-based analytical platforms as well as structured training programs. Regardless of factors such as infrastructure expenses and absence of specialized trainers, the research finds out that institutional investment in bioinformatics training is key. Finally, such labs enhance medical practice that is evidence-based and allow the healthcare sector to react to a threat more appropriately and develop a workforce that is future-ready and able to use large-scale biological data to improve patient outcomes.

Integrasi Kecerdasan Buatan dalam Diagnostik Medis: Peluang dan Tantangan di Era Kesehatan Digital

Heriyanto Manik — Thu, 19 Mar 2026 00:00:00 +0700

Penelitian ini bertujuan untuk menganalisis peluang dan tantangan integrasi kecerdasan buatan (Artificial Intelligence/AI) dalam diagnostik medis di era kesehatan digital. Metode yang digunakan adalah pendekatan kualitatif deskriptif berbasis studi pustaka dengan mengkaji berbagai literatur ilmiah, laporan implementasi, serta regulasi terkait AI dalam bidang kesehatan. Hasil kajian menunjukkan bahwa penerapan AI mampu meningkatkan akurasi, efisiensi, dan konsistensi proses diagnosis melalui kemampuan analisis data medis secara cepat dan sistematis, termasuk citra radiologi, rekam medis elektronik, dan data laboratorium. Selain itu, AI berperan sebagai alat pendukung dalam pengambilan keputusan klinis yang lebih berbasis data. Namun, implementasi AI masih menghadapi berbagai tantangan, seperti keterbatasan kualitas dan representasi data, potensi bias algoritma, kompleksitas integrasi dengan sistem kesehatan, serta rendahnya kesiapan sumber daya manusia. Aspek etika, keamanan data pasien, dan regulasi juga menjadi perhatian penting dalam memastikan penggunaan teknologi secara bertanggung jawab. Dengan demikian, integrasi AI dalam diagnostik medis memerlukan pendekatan komprehensif yang mencakup kesiapan infrastruktur, penguatan regulasi, dan peningkatan kompetensi tenaga medis agar dapat memberikan manfaat optimal bagi pelayanan kesehatan.

Pemanfaatan Wearable Technology untuk Monitoring Kesehatan: Analisis Tren dan Implikasinya bagi Perawatan Preventif

Abdul Qasim — Sat, 21 Mar 2026 00:00:00 +0700

Perkembangan teknologi kesehatan digital mendorong meningkatnya penggunaan wearable technology sebagai sarana monitoring kesehatan personal. Namun, pemanfaatan data kesehatan yang dihasilkan perangkat tersebut dalam mendukung praktik perawatan preventif masih memerlukan kajian yang lebih komprehensif. Penelitian ini bertujuan untuk menganalisis tren pemanfaatan wearable technology dalam monitoring kesehatan serta implikasinya terhadap praktik perawatan preventif. Penelitian menggunakan metode kualitatif deskriptif dengan pendekatan yang berfokus pada penggambaran fenomena penggunaan teknologi kesehatan digital tanpa manipulasi variabel. Data penelitian diperoleh melalui wawancara mendalam dengan pengguna wearable technology dan tenaga kesehatan, observasi terhadap praktik penggunaan perangkat, serta dokumentasi aplikasi kesehatan digital, yang kemudian dianalisis menggunakan model Miles dan Huberman melalui tahapan reduksi data, penyajian data, dan penarikan kesimpulan. Hasil penelitian menunjukkan bahwa wearable technology berperan penting dalam menyediakan informasi kesehatan secara real-time yang mendorong peningkatan kesadaran individu terhadap kondisi tubuh serta mendukung praktik perawatan preventif melalui pemantauan kesehatan.

Real-Time Image Segmentation, Tracking, and Augmented Reality Overlays to Improve Surgical Precision and Reduce Complications

Mon, 23 Mar 2026 00:00:00 +0700

Advances in real-time image segmentation and augmented reality (AR) technologies are transforming modern surgical practice by improving precision, reducing complications, and enhancing patient outcomes. This study empirically examines the integration of deep learning–based segmentation, object tracking, and AR overlay visualization for intraoperative guidance in laparoscopic surgery. A hybrid system combining U-Net++ segmentation, YOLOv8–DeepSORT tracking, and Unity-based AR rendering was implemented using MATLAB and Python environments. A dataset comprising 450 laparoscopic video sequences from 50 patients was analyzed to evaluate the framework’s performance. The model achieved a segmentation accuracy of 96.8%, an Intersection over Union (IoU) of 94.2%, and a mean latency of 85 ms. Statistically significant improvements (p < .05) were observed in surgical instrument localization, tissue differentiation, and navigation efficiency. Moreover, complication rates were reduced by 22.4% compared to conventional image-guided methods. Qualitative assessments indicated that surgeons experienced improved confidence, lower cognitive stress, and clearer visualization under dynamic intraoperative conditions. The findings suggest that integrating AI-powered segmentation, tracking, and AR visualization can enable safer, faster, and more precise surgical interventions. The proposed framework represents a scalable and clinically feasible pathway toward the realization of AI-assisted precision surgery and enhanced intraoperative decision-making.