Technological Model to Optimize the Request for Radiological Studies

Inappropriate requests for imaging studies are a frequent problem in clinical practice, leading to diagnostic errors, unnecessary costs, and patient dissatisfaction. These errors often arise from insufficient dissemination of clinical guidelines, limited training of referring physicians, and variability in request formats. The result is delayed diagnoses, duplication of studies, increased radiation exposure, and inefficient use of healthcare resources. To address this issue, technological tools such as diagnostic algorithms have been proposed to support physicians in selecting the most appropriate imaging tests, especially in time-sensitive conditions. This study evaluated a diagnostic algorithm through a cross-sectional survey of 111 participants, including physicians, residents, interns, medical students, and dental professionals. The questionnaire explored perceptions of the algorithm's clinical utility, clarity, and feasibility of integration into daily workflows. Respondents consistently highlighted its capacity to improve diagnostic accuracy, expedite decision-making, and facilitate clearer communication between physicians and radiologists. Specific strengths included its applicability to abdominal emergencies and complex scenarios such as right upper quadrant pain, jaundice, pancreatitis, and trauma. At the same time, participants pointed out challenges, including difficulties in evaluating contrast safety, limited access to high-cost imaging, and the need for broader diagnostic coverage and personalization by age group. Despite these concerns, the algorithm was positively received overall and was recognized as a useful support tool for reducing inappropriate requests, enhancing diagnostic confidence, and ultimately improving patient care.

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Publication Details

Journal
Cureus
Published
2025-09-12
DOI
https://doi.org/10.7759/cureus.92135
Primary Topic
Radiology practices and education
Type
article
Field-Weighted Citation Impact
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article

Technological Model to Optimize the Request for Radiological Studies

Juan D Vásquez, David González, Carlos A Galeano Baquero, Catalina Posada Cuartas et al.
Cureus
Radiology practices and education
article

Technological Model to Optimize the Request for Radiological Studies

Juan D Vásquez, David González, Carlos A Galeano Baquero, Catalina Posada Cuartas, Simón Samuel Cadavid Barrios
article en

Abstract

Inappropriate requests for imaging studies are a frequent problem in clinical practice, leading to diagnostic errors, unnecessary costs, and patient dissatisfaction. These errors often arise from insufficient dissemination of clinical guidelines, limited training of referring physicians, and variability in request formats. The result is delayed diagnoses, duplication of studies, increased radiation exposure, and inefficient use of healthcare resources. To address this issue, technological tools such as diagnostic algorithms have been proposed to support physicians in selecting the most appropriate imaging tests, especially in time-sensitive conditions. This study evaluated a diagnostic algorithm through a cross-sectional survey of 111 participants, including physicians, residents, interns, medical students, and dental professionals. The questionnaire explored perceptions of the algorithm's clinical utility, clarity, and feasibility of integration into daily workflows. Respondents consistently highlighted its capacity to improve diagnostic accuracy, expedite decision-making, and facilitate clearer communication between physicians and radiologists. Specific strengths included its applicability to abdominal emergencies and complex scenarios such as right upper quadrant pain, jaundice, pancreatitis, and trauma. At the same time, participants pointed out challenges, including difficulties in evaluating contrast safety, limited access to high-cost imaging, and the need for broader diagnostic coverage and personalization by age group. Despite these concerns, the algorithm was positively received overall and was recognized as a useful support tool for reducing inappropriate requests, enhancing diagnostic confidence, and ultimately improving patient care.

CureusVol. 17(9)
Cytodiagnostics (Canada) (CA), Clínica Somer (CO), Clínica CES (CO), Universidad Autónoma Latinoamericana (CO)
Openalex Percentile: Top 63%
Radiology practices and education
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