THE ROLE OF TECHNOLOGY IN NURSING DOCUMENTATION: A CHRONOLOGICAL REVIEW

Mohd Safri Kiprawi — Sun, 07 Jun 2026 00:00:00 +0800

This temporal literature review of The Role of Technology in Nursing Documentation aims to synthesise the trends and evolution of the digital integration in health. Although the use of technology, such as electronic health records, has been embraced, inconsistencies in their use, effectiveness, and fit with nursing processes suggest a need for a temporal perspective. To address this challenge, a thorough and sophisticated search was conducted in the Scopus database using keywords Electronic Health Records, Nursing Documentation, Digital Records, and Technology. A total of 114 primary studies were identified after reviewing the literature. The outcomes were clustered into four time periods to represent the trends in research activity and emphasis: (1) the Nascent and Exploratory Phase (2004-2008) that showed initial adoption and feasibility of the system; (2) the Initial Growth and Conceptual Expansion phase (2009-2013) that showed increasing interest and theoretical framework development; (3) the Consolidation and Fluctuating Maturity phase (2014-2022) that showed a steady state in publication output with variable effectiveness of the system and user adaptation; and (4) the Renewed Acceleration and Digital Transformation Phase (2024-2026) that showed an increase in innovation through digital transformation and integration of new technologies. The descriptive analysis of the temporal distribution of the studies shows an increasing trend in research activity, with the highest percentage in the recent phase. Overall, the review shows a dynamic trend in technology integration in nursing documentation with improvements and setbacks. The research concludes that although digital systems have greatly improved documentation, further development, user-friendly design, and policy support are needed to ensure they are being used to their full potential.

THE USE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN FINANCIAL SECTOR. A DECISION-MAKING FRAMEWORK

Sadia Asif, Shatina Saad — Sun, 07 Jun 2026 00:00:00 +0800

This study provides an overall review on current state of Artificial Intelligence (AI) and Machine Learning (ML) adoption in financial sector as well as explores a framework for identification of potential tasks for automation using AI and ML. The study utilizes a qualitative research methodology grounded in Dynamic Capabilities Theory. The research examines existing processes automated in financial institutions. The overall approach comprised review of existing literature, obtaining primary data through semi-structured interviews and performing thematic analysis. Analysis of data identified that AI & ML models are used for predictive analytics, fraud detection, credit risk assessment, investment portfolio, auditing, compliance monitoring, and customer services across the financial sector. Common criteria for selecting tasks were identified during primary data collection are also explored in this study. The study also discusses concerns shared by participants while they are selecting processes for automation. The research work also assisted in development of a framework to support the process for tasks automation for AI/ML.

JOURNAL INFORMATION AND TECHNOLOGY MANAGEMENT (JISTM)

THE ROLE OF TECHNOLOGY IN NURSING DOCUMENTATION: A CHRONOLOGICAL REVIEW

THE USE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN FINANCIAL SECTOR. A DECISION-MAKING FRAMEWORK