Dear Editor,
Clinical informationists have evolved into indispensable mediators between cutting-edge information technologies and frontline healthcare delivery, establishing themselves as critical stakeholders in modern healthcare ecosystems.[1,2,3,4] These professionals serve as the crucial neural network connecting health information systems with clinical practice, demonstrating measurable impacts across three key dimensions: quality improvement,[5] patient safety enhancement,[6] and systemic efficiency optimization.[7] As integral members of multidisciplinary clinical teams, they bring specialized competencies spanning four domains: 1) advanced scientific information retrieval using systematic review methodologies,[2] 2) knowledge management through ontologies and taxonomies,[8] 3) rigorous evidence appraisal,[2] and 4) tailored information literacy programs for healthcare professionals.[2] Beyond advancing organizational health information literacy, their consultative role in clinical decision-making committees and institutional review boards ensures appropriate translation of research evidence into practice, while their technical capabilities enable delivery of sophisticated information services, including living systematic reviews, real-time evidence alerts, customized clinical decision support tools, and competency-based training programs for precision medicine implementation.[2,3,4,9,10]
The advent of artificial intelligence is one of the most significant paradigm shifts in healthcare technology since the introduction of electronic health records[11] but A lack of mastery in artificial intelligence can lead to biased models and patient privacy violations.[12,13] Therefore, clinical informaticians equipped with expertise in AI and data ethics can prevent these outcomes by implementing robust monitoring mechanisms and by identifying and mitigating bias in training data. Meta-analytic evidence demonstrates AI’s capacity to enhance healthcare delivery through three primary mechanisms: 1) accelerating data accessibility, 2) improving diagnostic accuracy, and 3) optimizing resource allocation.[11,14,15] These three mechanisms can improve advanced AI services in healthcare such as online evidence-based decision-making by leveraging CI’s mastery of the field, which blends traditional data science with emerging AI techniques to position CI as crucial integrators within multidisciplinary teams.
The evolving technological landscape necessitates dual competency development for clinical informationist. They must preserve core information science competencies while acquiring four emerging skill sets: 1) AI conceptual foundations including neural networks and large language models, 2) clinical data mining techniques, 3) analytical methods for model validation, and 4) implementation science principles.[16]
To realize using an artificial intelligence as a transformative tool for empowering clinical informationists in healthcare systems, we recommend implementing structured training programs in health data analytics, AI applications, and ethical frameworks. These initiatives will equip informationists with the necessary skills to harness advanced technologies, ultimately optimizing health information services and patient outcomes in the AI-driven era.
Sincerely,
Conflicts of interest
There are no conflicts of interest.
Funding Statement
Nil.
References
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