TrialCompass: Visual Analytics for Enhancing the Eligibility Criteria Design of Clinical Trials
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arXiv
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912486014320640 |
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| author | Sheng, Rui Wang, Xingbo Wang, Jiachen Jin, Xiaofu Sheng, Zhonghua Xu, Zhenxing Rajendran, Suraj Qu, Huamin Wang, Fei |
| author_facet | Sheng, Rui Wang, Xingbo Wang, Jiachen Jin, Xiaofu Sheng, Zhonghua Xu, Zhenxing Rajendran, Suraj Qu, Huamin Wang, Fei |
| contents | Eligibility criteria play a critical role in clinical trials by determining the target patient population, which significantly influences the outcomes of medical interventions. However, current approaches for designing eligibility criteria have limitations to support interactive exploration of the large space of eligibility criteria. They also ignore incorporating detailed characteristics from the original electronic health record (EHR) data for criteria refinement. To address these limitations, we proposed TrialCompass, a visual analytics system integrating a novel workflow, which can empower clinicians to iteratively explore the vast space of eligibility criteria through knowledge-driven and outcome-driven approaches. TrialCompass supports history-tracking to help clinicians trace the evolution of their adjustments and decisions when exploring various forms of data (i.e., eligibility criteria, outcome metrics, and detailed characteristics of original EHR data) through these two approaches. This feature can help clinicians comprehend the impact of eligibility criteria on outcome metrics and patient characteristics, which facilitates systematic refinement of eligibility criteria. Using a real-world dataset, we demonstrated the effectiveness of TrialCompass in providing insights into designing eligibility criteria for septic shock and sepsis-associated acute kidney injury. We also discussed the research prospects of applying visual analytics to clinical trials. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_12298 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | TrialCompass: Visual Analytics for Enhancing the Eligibility Criteria Design of Clinical Trials Sheng, Rui Wang, Xingbo Wang, Jiachen Jin, Xiaofu Sheng, Zhonghua Xu, Zhenxing Rajendran, Suraj Qu, Huamin Wang, Fei Human-Computer Interaction Eligibility criteria play a critical role in clinical trials by determining the target patient population, which significantly influences the outcomes of medical interventions. However, current approaches for designing eligibility criteria have limitations to support interactive exploration of the large space of eligibility criteria. They also ignore incorporating detailed characteristics from the original electronic health record (EHR) data for criteria refinement. To address these limitations, we proposed TrialCompass, a visual analytics system integrating a novel workflow, which can empower clinicians to iteratively explore the vast space of eligibility criteria through knowledge-driven and outcome-driven approaches. TrialCompass supports history-tracking to help clinicians trace the evolution of their adjustments and decisions when exploring various forms of data (i.e., eligibility criteria, outcome metrics, and detailed characteristics of original EHR data) through these two approaches. This feature can help clinicians comprehend the impact of eligibility criteria on outcome metrics and patient characteristics, which facilitates systematic refinement of eligibility criteria. Using a real-world dataset, we demonstrated the effectiveness of TrialCompass in providing insights into designing eligibility criteria for septic shock and sepsis-associated acute kidney injury. We also discussed the research prospects of applying visual analytics to clinical trials. |
| title | TrialCompass: Visual Analytics for Enhancing the Eligibility Criteria Design of Clinical Trials |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2507.12298 |