Health informatics has emerged as a pivotal tool in transforming mental health services, offering new possibilities for diagnostic precision, treatment planning, and patient engagement. This narrative review aimed to examine the role of health informatics in improving mental health outcomes, with a focus on Clinical Decision Support Systems (CDSS), mobile health applications, artificial intelligence (AI), and inclusive data practices. A systematic literature search was conducted across databases including Scopus, PubMed, Web of Science, and Google Scholar, using targeted keywords related to digital health and psychiatry. Studies were screened based on defined inclusion and exclusion criteria to ensure methodological rigor and relevance. The findings reveal that CDSS improves diagnostic accuracy and comorbidity detection, though disparities exist in adoption between developed and developing countries. Mobile health applications demonstrate effectiveness in suicide prevention and trauma management, particularly among youth, but adoption is uneven across demographic groups. AI and big data contribute to early detection and personalized care, yet raise significant concerns about bias, privacy, and transparency. Inclusive data practices, especially in collecting sexual orientation and gender identity information, are essential for reducing disparities and promoting equitable care. Discussion highlights the need for supportive policy frameworks, adequate funding, digital infrastructure, and clinician training, alongside participatory approaches that ensure cultural sensitivity. This review concludes that health informatics holds substantial promise for improving accessibility, quality, and equity in mental health services. Yet, overcoming systemic, infrastructural, and ethical barriers remains essential to fully addressing the global mental health burden.
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