Hripcsak George, Zhou Li, Parsons Simon, Das Amar K, Johnson Stephen B
Department of Biomedical Informatics, Columbia University, 622 West 168th Street, VC5, New York, NY 10032, USA.
J Am Med Inform Assoc. 2005 Jan-Feb;12(1):55-63. doi: 10.1197/jamia.M1623. Epub 2004 Oct 18.
To model the temporal information contained in medical narrative reports as a simple temporal constraint satisfaction problem.
A constraint satisfaction problem is defined by time points and constraints (inequalities between points). A time interval comprises a pair of points and a constraint. Five complete electronic discharge summaries and paragraphs from 226 other discharge summaries were studied. Medical events were represented as intervals, and assertions about events were represented as constraints. Through a consensus process, a set of encoding procedures and a list of issues related to encoding were generated.
Instances of temporal disjunction and contradiction and distribution of temporal constraints were used.
An average of 95 medical events (range, 46-151) and 234 temporal assertions (range, 118-388) were identified per complete discharge summary. Nondefinitional assertions were explicit (36%) or implicit (64%) and absolute (17%), qualitative (72%), or metric (11%). Implicit assertions were based on domain knowledge and assumptions, e.g., the section of the report determined the ordering of events. Issues included linking events, intermittence, periodicity, granularity, vagueness, ambiguity, uncertainty, and plans. ions such as intermittence were not represented explicitly. The temporal network was sparse: Only 0.80% (range, 0.42%-1.38%) of possible constraints were instantiated. No instances of discontinuous temporal disjunction were found in the complete summaries or the 226 paragraphs. One instance of temporal contradiction was found (intrareport rate of 0.2 with a 95% confidence interval of 0.005-1.114).
A simple temporal constraint satisfaction problem appears sufficient to represent most temporal assertions in discharge summaries and may be useful for encoding electronic medical records.
将医学叙事报告中包含的时间信息建模为一个简单的时间约束满足问题。
一个约束满足问题由时间点和约束(点之间的不等式)定义。一个时间间隔由一对点和一个约束组成。研究了5份完整的电子出院小结以及来自其他226份出院小结的段落。医疗事件被表示为间隔,关于事件的断言被表示为约束。通过一个共识过程,生成了一组编码程序以及一份与编码相关的问题列表。
使用时间析取和矛盾的实例以及时间约束的分布。
每份完整的出院小结平均识别出95个医疗事件(范围为46 - 151)和234个时间断言(范围为118 - 388)。非定义性断言是明确的(36%)或隐含的(64%),以及绝对的(17%)、定性的(72%)或度量的(11%)。隐含断言基于领域知识和假设,例如报告的章节决定了事件的顺序。问题包括事件链接、间歇性、周期性、粒度、模糊性、歧义性、不确定性和计划。诸如间歇性等问题没有被明确表示。时间网络是稀疏的:仅0.80%(范围为0.42% - 1.38%)的可能约束被实例化。在完整小结或226个段落中未发现不连续时间析取的实例。发现了一个时间矛盾的实例(报告内发生率为0.2,95%置信区间为0.005 - 1.114)。
一个简单的时间约束满足问题似乎足以表示出院小结中的大多数时间断言,并且可能对电子病历编码有用。