Modeling Electronic Discharge Summaries as a Simple Temporal Constraint Satisfaction Problem
- Affiliations of the authors: Department of Biomedical Informatics, Columbia University, New York, NY (GH, LZ, SBJ); Department of Computer and Information Science, Brooklyn College, Brooklyn, NY (SP); Department of Psychiatry, Columbia University, New York, NY (AKD). Dr. Das is currently with Stanford Medical Informatics, Stanford University, Stanford, CA
- Correspondence and reprints: George Hripcsak, MD, MS, Department of Medical Informatics, Columbia University, 622 West 168th Street, VC5, New York, NY 10032; e-mail: <hripcsak{at}columbia.edu>
- Received 24 May 2004
- Accepted 8 September 2004
Abstract
Objective To model the temporal information contained in medical narrative reports as a simple temporal constraint satisfaction problem.
Design 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.
Measurements Instances of temporal disjunction and contradiction and distribution of temporal constraints were used.
Results 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. Abstractions 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).
Conclusion 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.
Footnotes
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Abstract presented at the meeting of Intelligent Data Analysis in Medicine and Pharmacology, Stanford University, Palo Alto, CA, September 2004.
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Supported by National Library of Medicine grants R01 LM06910, “Discovering and Applying Knowledge in Clinical Databases”; R01 LM07659, “Capturing and Linking Genomic and Clinical Information”; and R01 LM07268, “Using Narrative Data to Enrich the Online Medical Record.”
