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Impact Of Incidental Findings on Radiology

ElChiwy, M.M.S. (2023) Impact Of Incidental Findings on Radiology.

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Abstract:Motivation & Objective: The increasing demand for the healthcare system to minimize spending and provide the same quality of care (if not better) has forced stakeholders to develop ideas and plans to make their operations more efficient. The Leiden University Medical Center (LUMC) board aims to cut its costs by making projects on hospital broad themes. One of those themes is Diagnostics, with the Radiology department, which our project focuses on, being one of them. The radiology department is a place where innovation is increasing on almost a daily basis, however, this increases the outcomes and therefore the costs. Several factors increase the frequency of imaging tests, including Incidental Findings (IFs). IFs refer to unexpected and unintended findings unrelated to the primary reason for the imaging study (Pham et al., 2014). IFs were also talked about by medical staff in a diverse way, making it more difficult to grasp their frequency and impact. To know the significance of the impact of IFs on radiology is the objective of this research. Reaching such an objective would help us understand the causes of IFs and the influence and costs of IFs on radiology. With such knowledge, we can move forward and start making proposals to mitigate the impact of IFs. Moreover, to specifically see the effects of IFs at the LUMC and as a proof of principle, we examine Breast Cancer (BC) patients at the LUMC to see how IFs impact the rate of imaging testing. Approach: We start with literature research and interviews with medical experts to gather knowledge about IFs and how it impacts radiology. The aim is to identify the causes of IFs by getting insights into the processes of detecting an IF, the types of IFs, and their frequency and severity. Then, we examine the literature on how IFs impact radiology by knowing the most common follow-ups after detecting an IF and the costs of IFs. We then search for ways to minimize the impact of IFs on radiology. Finally, we research the influence of IFs on BC and transform that into the basis of analyzing the data given by the LUMC to assess the impact IFs have on the medical imaging of BC patients. Results: In the literature study, we found out that there are six steps involved in detecting IFs in radiology. Based on various studies, we found that the detection rate for IFs ranges from 3% to 40% and is highly influenced by the modality used and the primary diagnosis. In the same studies, we found out that CT and PET scans are the modalities with the most IFs, most PET/CT tests are used to look for metastases, and in most cases, IFs are not clinically significant. In different studies, we found that IFs significantly impact patients, medical staff, and capacity, which leads to extra costs. We also found three strategies to minimize the rate of IFs, The NLP algorithm, the ACR project, and guidelines for radiologists. In the data analysis of BC patients in the LUMC, seven relationships between imaging modalities were studied to assess the influence IFs have on those relationships (See Table 1 – Confidential). We first examined if there was a yearly correlation. If there was a yearly correlation, a monthly correlation was examined. If there was a monthly correlation, an analysis of this correlation was examined to see how much it is due to IFs, based on radiologists’ reports. Conclusion: Value for Science : This research contributes to the scientific community in various ways. First, it helps advance knowledge regarding IFs, as it gives new insights, challenges existing theories, and analyzes existing literature and data, thereby pushing the boundaries of knowledge. Second, it has a methodological contribution and data analysis approaches, which allow others to build upon or replicate the methods used. Third, it allows the dissemination of findings, as most of this research will be publicly available, allowing other researchers to access, cite, and build upon the work. Value for Practice: There are two ways in which this research contributes value to practice. First, it offers practical insights, innovative approaches, and recommendations that can be applied in the LUMC. Second, it guides practitioners in making informed choices, developing policies, or implementing changes based on a solid foundation of research evidence.
Item Type:Essay (Bachelor)
Faculty:BMS: Behavioural, Management and Social Sciences
Programme:Industrial Engineering and Management BSc (56994)
Link to this item:https://purl.utwente.nl/essays/96755
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