Content and structure of clinical problem lists: a corpus analysis.
Information Storage and Retrieval
Medical History Taking
Medical Records Systems, Computerized
Medical Records, Problem-Oriented
Natural Language Processing
Pattern Recognition, Automated
In the interest of designing an automated high-level, longitudinal clinical summary of a patient record, we analyze traditional ways in which medical problems pertaining to the patient are summarized in the electronic health record. The patient problem list has become a commonly used proxy for a summary of patient history and automated methods have been proposed to generate it. However, little research has been conducted on how to structure the problem list in a manner most effective for supporting clinical care. This study analyzes the structure and content of the Past Medical History (PMH) sections of a large corpus of clinical notes, as a proxy for problem lists. Findings show that when listing patients history, physicians convey several semantic types of information, not only problems. Furthermore, they often group related concepts in a single line of the PMH. In contrast, traditional problem lists allow only a simple enumeration of coded terms. Content analysis goes on to reiterate the value of more complex representations as well as provide valuable data and guidelines for automated generation of a clinical summary.