Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Impact Analysis of Diagnostic Errors on Healthcare Delivery: A Systematic Review
0
Zitationen
4
Autoren
2025
Jahr
Abstract
Background: There is need to collate the evidences on the prevalence of diagnostic errors and their influence on hazardous outcomes to affect efficiency, cost and safety in healthcare delivery. Objectives: This review addressed diagnostic errors in terms of epidemiology, hazards, impacts, challenges to suggest holistic recommendations to all the stakeholders, researchers and administrators. Methods: Electronic public domains viz. PubMed, SCOPUS, GoogleScholar, ResearchGate. and manual search on diagnostic errors and interventions implemented by clinician in clinical environment, searched for literatures published between January 2005 and June 2025 for common errors concerning the diagnosis in the practice directed towards the patient, direct and indirect repercussions on health and financial and operational aspects of healthcare, challenges, research and interventions to improve patient safety by checklists using PRISMA reporting guidelines. Results: A total of 291 articles were screened of which 28 studies met inclusion criteria of our review. Data extraction was done by two groups, each group comprising two independent investigators from Review (n=20), Cohort study (n=2), Cross-sectional, (n=3), Controlled intervention (n=2), Invited Commentary (n=1). WHO check list, digitalization and AI are showing potential solution for error reduction amid ethical, legal, quality assurance issues. Conclusions: Our analyses revealed evidence on prevalence, risk correlates and interventions to limit DEs being feasible in clinical settings across High Income Countries (HICs) and Low and Middle Income Countries (LMICs). A comprehensive approach is needed to ensure safety by quality of care at every patient interface, capacity building and systems approach to enhance accuracy and ensure updating.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.287 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.140 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.534 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.450 Zit.