OBJECTIVES: To develop and evaluate an information processing method based on terminologies, in order to index medical documents in any given documentary context.
METHODS: We designed a model using both symbolic general knowledge extracted from the Unified Medical Language System (UMLS) and statistical knowledge extracted from a domain of application. Using statistical knowledge allowed us to contextualize the general knowledge for every particular situation. For each document studied, the extracted terms are ranked to highlight the most significant ones. The model was tested on a set of 17,079 French standardized discharge summaries (SDSs).
RESULTS: The most important ICD-10 term of each SDS was ranked 1st or 2nd by the method in nearly 90% of the cases.
CONCLUSIONS: The use of several terminologies leads to more precise indexing. The improvement achieved in the models implementation performances as a result of using semantic relationships is encouraging.
The French ministry of Health is setting up the Personal Medical Record (PMR). This innovative tool has long been expected by French Health Authorities, Associations of Patients, other Health's associations, those defending Individual Liberties and the French National Data Protection Authority. The PMR will lead to improvements in many areas such as Diagnosis (Research and monitoring) Healthcare (Management of emergencies, urgent situations, Temporal health monitoring and evaluation), Therapy (Cohorts of patients for Clinical trials and epidemiological studies). The PMR will foster safe healthcare management, clinical research and epidemiological studies. Nevertheless, it raises many important questions regarding duplicates and the quality, precision and coherence of the linkage with other health data coming from different sources. The currently planned identifying process raises many questions with regard to its ability to deal with potential duplicates and to perform data linkage with other health data sources. Through this article, using the electronic health records, we develop and propose an identification process to improve the French PMR. Our proposed unique patient identifier will guarantee the security, confidentiality and privacy of the personal data, and will prove to be particularly useful for health planning, health policies and research as well as clinical and epidemiological studies. Finally, it will certainly be interoperable with other European health information systems. We propose here an alternative identification procedure that would allow France to broaden the scope of its PMR project by making it possible to contribute to public health research and policy while increasing interoperability with European health information systems and preserving the confidentiality of the data.