The Role of Clinical Decision Support Systems in Optimizing Anemia Management: A Systematic Review
DOI:
https://doi.org/10.64149/J.Ver.8.7s.282-297Keywords:
Anemia, Artificial Intelligence, CDSS, Clinical Decision Support Systems, Diagnostic Accuracy, Management.Abstract
Background: One of the most potential methods to close the gap between the evidence and practice is through the use of Clinical Decision Support Systems (CDSS) for the patient suggestions for anemia identification and treatment. This study aims to identify, synthesize, and map systematic review of the effectiveness of Clinical Decision Support Systems (CDSS) for optimal anemia management.
Methods: This systematical assessment adhered to PRISMA regulations to investigate how efficient CDSS are in the management of anemia through the optimization of various healthcare settings. Numerous databased were navigated from May 2021 to December 2025 to find relevant studies. Study included 9 studies (randomized controlled trials, quasi, experimental, and observational studies) that met the criteria for inclusion.
Results: A total of 3517 articles were identified; following screening, 241 reviews underwent full‐text screening, and 9 articles met the inclusion criteria and were included in this review. The analyzed studies revealed that CDSS involve in reflexive algorithms, guideline, based order sets, and AI models, have the potential to greatly raise the proper management of anemia, related laboratory test requests, lower the redundant testing and expenses, and increase the diagnostic accuracy.
Conclusion: CDSS is effective in achieving efficient anemia management through the provision of support for evidence, based decision making, facilitation of test appropriateness, and reduction in resource utilization. Integrating CDSS into a workflow is effortless and choosing strategies that will result in proper engagement of clinicians in appropriate anemia management.
