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Diagnostic Challenges and Patient Safety: The Critical Role of Accuracy – A Systematic Review

2025·20 Zitationen·Journal of Multidisciplinary HealthcareOpen Access
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20

Zitationen

5

Autoren

2025

Jahr

Abstract

Background: Accurate diagnosis is critical for patient safety, guiding treatment and preventing harm. Diagnostic errors remain prevalent, contributing to avoidable harm, increased healthcare costs, and morbidity. Understanding diagnostic accuracy is essential to improving clinical outcomes. Objective: This review aims to systematically explore the impact of accurate diagnosis on patient safety, identifying challenges in current diagnostic practices and strategies for improvement. Methods: A comprehensive search of PubMed, CINAHL, the Cochrane Library, and Google Scholar was conducted from 2010-2024. Initial screening yielded 579 records, using keywords like "accurate diagnosis", "diagnostic errors", and "patient safety." A full-text review of 125 studies was conducted after duplicates were eliminated and titles and abstracts were screened for relevancy. Exclusion criteria excluded studies with inadequate data, non-English publications, and opinion pieces, while inclusion criteria mandated that studies concentrate on patient safety and diagnostic accuracy in acute care settings. Ultimately, 26 studies were found to meet the final eligibility requirements and were added to the review. Retrospective cohort studies and randomized controlled trials were among the study designs. Results: Accurate diagnosis was found to improve treatment efficacy, enhances patient safety, and reduces unnecessary procedures. Challenges include cognitive biases, insufficient diagnostic tools, and fragmented care. Technological advancements, including artificial intelligence (AI) and machine learning, were found to significantly enhance diagnostic precision. Despite these benefits, variability in clinical skills and systemic barriers remain substantial obstacles. Conclusion: Accurate diagnosis is essential to enhancing patient safety. The results of this review indicate that using AI tools, improving clinician training, and creating standardized diagnostic procedures may help reduce diagnostic errors; however, because of the small dataset and lack of meta-analysis, the findings should be interpreted cautiously. To further evaluate the effect of diagnostic accuracy on patient safety, future research should concentrate on carrying out larger-scale studies and statistical validations.

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Themen

Clinical Reasoning and Diagnostic SkillsArtificial Intelligence in Healthcare and EducationClinical Laboratory Practices and Quality Control
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