The MaHTAS systematic review process is a critical component of evidence-based decision-making in healthcare, ensuring that interventions and technologies are rigorously evaluated for safety, effectiveness, and cost-efficiency.
Reducing errors in the systematic review process requires the use of structured protocols, standardized forms, and automation tools. For example, reference management software can help de-duplicate studies, AI-assisted screening tools can prioritize relevant articles, and structured data extraction templates reduce inconsistencies.
By minimizing these errors, the review becomes more accurate, reliable, and reproducible, ensuring that the conclusions drawn from the evidence are trustworthy. This ultimately strengthens the decision-making process for healthcare interventions and policies.
Systematic reviews involve multiple complex steps, such as literature searching, study selection, data extraction, and quality assessment. When performed manually, these steps are prone to human errors.