We propose a method utilizing a derived social security number with the same reliability as the social security number. We show the anonymity techniques classically based on unidirectional hash functions (such as the secure hash algorithm (SHA-2) function that can guarantee the security, quality, and reliability of information if these techniques are applied to the Social Security Number). Hashing produces a strictly anonymous code that is always the same for a given individual, and thus enables patient data to be linked. Different solutions are developed and proposed in this article. Hashing the social security number will make it possible to link the information in the personal medical file to other national health information sources with the aim of completing or validating the personal medical record or conducting epidemiological and clinical research. This data linkage would meet the anonymous data requirements of the European directive on data protection.
We propose to design and test an information-processing model to participate in appraising the quality and the consistency of the coding, for billing, of Standardized Discharge Summaries (SDSs). We designed a model using both symbolic knowledge extracted from the NLM's UMLS and statistical knowledge. The aim is to retrieve from the ICD-10 terms recorded in a SDS the Principal Diagnosis (PD) at the time of coding. In 90% of cases the PD was retrieved 1st or 2nd in SDS including three ICD-10 codes or more. This model could contribute as part of an automated quality control process in a hospital information system by checking consistency in coded SDSs and improve the income of the hospital.
OBJECTIVES: The aim of this study is to provide to indexers MeSH terms to be considered as major ones in a list of terms automatically extracted from a document.
MATERIAL AND METHODS: We propose a method combining symbolic knowledge - the UMLS Metathesaurus and Semantic Network - and statistical knowledge drawn from co-occurrences of terms in the CISMeF database (a French-language quality-controlled health gateway) using data mining measures. The method was tested on CISMeF corpus of 293 resources.
RESULTS: There was a proportion of 0.37+/-0.26 major terms in the processed records. The method produced lists of terms with a proportion of terms initially pointed out as major of 0.54+/-0.31.
DISCUSSION: The method we propose reduces the number of terms, which seem not useful for content description of resources, such as "check tags", but retains the most descriptive ones. Discarding these terms is accounted for by: 1) the removal by using semantic knowledge of associations of concepts bearing no real medical significance, 2) the removal by using statistical knowledge of nonstatistically significant associations of terms.
CONCLUSION: This method can assist effectively indexers in their daily work and will be soon applied in the CISMeF system.
The multiplication of the requests of the patients for a direct access to their Medical Record (MR), the development of Personal Medical Record (PMR) supervised by the patients themselves, the increasing development of the patients' electronic medical records (EMRs) and the world wide internet utilization will lead to envisage an access by using technical automatic and scientific way. It will require the addition of different conditions: a unique patient identifier which could base on a familial component in order to get access to the right record anywhere in Europe, very strict identity checks using cryptographic techniques such as those for the electronic signature, which will ensure the authentication of the requests sender and the integrity of the file but also the protection of the confidentiality and the access follow up. The electronic medical record must also be electronically signed by the practitioner in order to get evidence that he has given his agreement and taken the liability for that. This electronic signature also avoids any kind of post-transmission falsification. This will become extremely important, especially in France where patients will have the possibility to mask information that, they do not want to appear in their personal medical record. Currently, the idea of every citizen having electronic signatures available appears positively Utopian. But this is yet the case in eGovernment, eHealth and eShopping, world-wide. The same was thought about smart cards before they became generally available and useful when banks issued them.
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.