Synthesizing Efficiency Tools in Radiotherapy to Increase Patient Flow: A Comprehensive Literature Review.

The promise of novel technologies to increase access to radiotherapy in low- and middle-income countries (LMICs) is crucial, given that the cost of equipping new radiotherapy centres or upgrading existing machinery remains a major obstacle to expanding access to cancer treatment. The study aims to p...

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Publicado en:Clinical Medicine Insights: Oncology pp. 1 - 18
Autores principales: Ramiah, Duvern, Mmereki, Daniel
Formato: research systematic review tables/charts Journal Article
Publicado: Sage Publications Inc. 12/13/2024
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 12/13/2024
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      pub: Sage Publications Inc.
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        atl: Synthesizing Efficiency Tools in Radiotherapy to Increase Patient Flow: A Comprehensive Literature Review.
      aug:
        au:
          Ramiah, Duvern
          Mmereki, Daniel
        affil: Division of Radiation Oncology, Department of Radiation Sciences, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
      sug:
        subj:
          Neoplasms Radiotherapy
          Oncologic Care Methods
          Organizational Efficiency Methods
          Artificial Intelligence
          Workflow
          Radiotherapy, Computer-Assisted Methods
          Human
          Male
          Female
          Adult
          Literature Review
          Technology, Medical
          Cancer Patients
          PubMed
          Planning Techniques
          Disease Progression Risk Factors
          Workload
          Health Resource Utilization
          Patient Safety
          Patient Care
          Radiation Oncology
          Adult: 19-44 years
          Male
          Female
      ab: The promise of novel technologies to increase access to radiotherapy in low- and middle-income countries (LMICs) is crucial, given that the cost of equipping new radiotherapy centres or upgrading existing machinery remains a major obstacle to expanding access to cancer treatment. The study aims to provide a thorough analysis overview of how technological advancement may revolutionize radiotherapy (RT) to improve level of care provided to cancer patients. A comprehensive literature review following some steps of systematic review (SLR) was performed using the Web of Science (WoS), PubMed, and Scopus databases. The study findings are classified into different technologies. Artificial intelligence (AI), knowledge-based planning, remote planning, radiotherapy, and scripting are all ways to increase patient flow across radiation oncology, including initial consultation, treatment planning, delivery, verification, and patient follow-up. This review found that these technologies improve delineation of organ at risks (OARs) and considerably reduce waiting times when compared with conventional treatment planning in RT. In this review, AI, knowledge-based planning, remote radiotherapy treatment planning, and scripting reduced waiting times and improved organ at-risk delineation compared with conventional RT treatment planning. A combination of these technologies may lower cancer patients' risk of disease progression due to reduced workload, quality of therapy, and individualized treatment. Efficiency tools, such as the application of AI, knowledge-based planning, remote radiotherapy planning, and scripting, are urgently needed to reduce waiting times and improve OAR delineation accuracy in cancer treatment compared with traditional treatment planning methods. The study's contribution is to present the potential of technological advancement to optimize RT planning process, thereby improving patient care and resource utilization. The study may be extended in the future to include digital integration and technology's impact on patient safety, outcomes, and risk. Therefore, in radiotherapy, research on more efficient tools pioneers the development and implementation of high-precision radiotherapy for cancer patients.
      pubtype: Academic Journal
      doctype:
        research
        systematic review
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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