Ross Jessica, Tu Samson, Carini Simona, Sim Ida
Dept of Psychiatry, Veteran's Administration Medical Center, San Francisco, CA;
Summit Transl Bioinform. 2010 Mar 1;2010:46-50.
Formal, computer-interpretable representations of eligibility criteria would allow computers to better support key clinical research and care use cases such as eligibility determination. To inform the development of such formal representations for eligibility criteria, we conducted this study to characterize and quantify the complexity present in 1000 eligibility criteria randomly selected from studies in ClinicalTrials.gov. We classified the criteria by their complexity, semantic patterns, clinical content, and data sources. Our analyses revealed significant semantic and clinical content variability. We found that 93% of criteria were comprehensible, with 85% of these criteria having significant semantic complexity, including 40% relying on temporal data. We also identified several domains of clinical content. Using the findings of the study as requirements for computer-interpretable representations of eligibility, we discuss the challenges for creating such representations for use in clinical research and practice.
合格标准的形式化、计算机可解释表示将使计算机能够更好地支持关键的临床研究和医疗用例，如合格性判定。为了为合格标准的此类形式化表示的开发提供信息，我们开展了本研究，以描述和量化从ClinicalTrials.gov上的研究中随机选取的1000条合格标准中存在的复杂性。我们根据标准的复杂性、语义模式、临床内容和数据来源对其进行了分类。我们的分析揭示了显著的语义和临床内容变异性。我们发现93%的标准是可理解的，其中85%的标准具有显著的语义复杂性，包括40%依赖时间数据。我们还确定了几个临床内容领域。利用该研究的结果作为合格性计算机可解释表示的要求，我们讨论了创建此类表示以用于临床研究和实践所面临的挑战。
