Preparation and Challenges in Developing a Big Data Analysis Framework in Occupational Medicine in Indonesia

Research output: Contribution to journalReview articlepeer-review

Abstract

This mini review explores the transformative potential of big data analysis and artificial intelligence (AI) in reforming occupational medicine in Indonesia. Emphasizing the preconditions, case studies, and benefits, it underscores the role of big data in enhancing worker well-being. The review highlights the importance of informative health big data, especially in high-risk industries, with examples of case studies of AI implementation in occupational medicine during the COVID-19 pandemic and other relevant scenarios. While acknowledging the challenges of AI implementation, the essay identifies the role of academic and professional organizations as pioneers in big data utilization. Six potential benefits that are identified, including improved patient care and efficient resource allocation, demonstrate the transformative impact of big data analysis. The proposed pathway of preparation underscores the need for awareness, skill enhancement, and collaboration, addressing challenges in data management and stakeholder engagement. The conclusion emphasizes continuous assessment, feasibility studies, and commitment as essential steps in advancing occupational medicine through big data analysis.

Original languageEnglish
Pages (from-to)113-118
Number of pages6
JournalJournal of UOEH
Volume46
Issue number1
DOIs
Publication statusPublished - 2024

Keywords

  • big data analysis
  • indonesia
  • occupational medicine

Fingerprint

Dive into the research topics of 'Preparation and Challenges in Developing a Big Data Analysis Framework in Occupational Medicine in Indonesia'. Together they form a unique fingerprint.

Cite this