多学科医院脑卒中患者放射诊断服务优化

Gulzhan Adenova, Galina Kausova, Timur Saliev, Yevgeniy Zhukov, Dinara Ospanova, Zaure Dushimova, Anel Ibrayeva, Ildar Fakhradiyev
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引用次数: 0

摘要

背景:在多学科医院,有效的放射诊断服务对于脑卒中的及时准确诊断和治疗至关重要。然而,这些服务的效率可能受到多学科医院设置中存在的各种后勤和业务挑战的阻碍。目的:探讨优化多学科医院脑卒中管理的途径,探讨其优势、面临的挑战和未来前景。方法:本综述采用PubMed、Scopus和Web of Science等电子数据库。对多学科医院卒中患者放射诊断服务的组织和功能方面的研究进行了分析。结果:本综述深入探讨了多种可用于增强放射诊断服务的策略,从而更好地为多学科医院设置的脑卒中患者服务。阐明了当前优化冲程管理的障碍,并对其进行了详细的讨论。本文还探讨了流程映射在医院卒中管理流程化工作流程中的应用和意义,提供了其益处、挑战和未来影响的见解。此外,还分析和讨论了人工智能(AI)和机器学习(ML)在细化冲程管理过程中的潜力。结论:探索优化组织放射诊断服务在多学科医院揭示了一个多管齐下的途径。它召唤着技术创新、操作技巧和多学科友爱的和谐融合。建议逐步实施已确定的优化策略,并持续评估其对患者护理和操作效率的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of Radiology Diagnostic Services for Patients with Stroke in Multidisciplinary Hospitals.

Background: Effective radiology diagnostic services are crucial for the timely and precise diagnosis and treatment of stroke, a medical emergency, in multidisciplinary hospitals. However, the efficiency of these services might be impeded by various logistical and operational challenges present in a multidisciplinary hospital setup.

Objective: This review endeavours to explore the ways for optimizing stroke management in multi-disciplinary hospitals, delving into its benefits, current challenges, and future prospects.

Methods: Electronic databases, namely PubMed, Scopus, and Web of Science, were utilized for this review. Studies that focus on the organizational and functional aspects of radiology diagnostic services in multidisciplinary hospitals for stroke patients were analysed.

Results: This review delves into a variety of strategies that could be harnessed to enhance radiology diagnostic services, thereby better-serving stroke patients in multidisciplinary hospital settings. It sheds light on the current hurdles in the optimization of stroke management, discussing them in detail. This article also explores the application and significance of Process Mapping in streamlining workflow for stroke management in hospitals, providing insights into its benefits, challenges, and future implications. Furthermore, the potential of Artificial Intelligence (AI) and Machine Learning (ML) in refining stroke management processes is also analysed and discussed.

Conclusion: The quest for optimizing the organization of radiology diagnostic services in multidisciplinary hospitals unveils a multi-pronged pathway. It beckons a harmonious blend of technological innovation, operational finesse, and multidisciplinary camaraderie. stepwise implementation of the identified optimization strategies, coupled with a continual assessment of their impact on patient care and operational efficiency, is recommended.

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