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Objective: Data from electronic healthcare records (EHR) can be used to monitor drug safety, but in order to compare and pool data from different EHR databases, the extraction of potential adverse events must be harmonized. In this paper, we describe the procedure used for harmonizing the extraction from eight European EHR databases of five events of interest deemed to be important in pharmacovigilance: acute myocardial infarction (AMI); acute renal failure (ARF); anaphylactic shock (AS); bullous eruption (BE); and rhabdomyolysis (RHABD)., Design: The participating databases comprise general practitioners' medical records and claims for hospitalization and other healthcare services. Clinical information is collected using four different disease terminologies and free text in two different languages. The Unified Medical Language System was used to identify concepts and corresponding codes in each terminology. A common database model was used to share and pool data and verify the semantic basis of the event extraction queries. Feedback from the database holders was obtained at various stages to refine the extraction queries., Measurements: Standardized and age specific incidence rates (IRs) were calculated to facilitate benchmarking and harmonization of event data extraction across the databases. This was an iterative process., Results: The study population comprised overall 19 647 445 individuals with a follow-up of 59 929 690 person-years (PYs). Age adjusted IRs for the five events of interest across the databases were as follows: (1) AMI: 60-148/100 000 PYs; (2) ARF: 3-49/100 000 PYs; (3) AS: 2-12/100 000 PYs; (4) BE: 2-17/100 000 PYs; and (5) RHABD: 0.1-8/100 000 PYs., Conclusions: The iterative harmonization process enabled a more homogeneous identification of events across differently structured databases using different coding based algorithms. This workflow can facilitate transparent and reproducible event extractions and understanding of differences between databases.

Objectives: The aim of this study was to evaluate the interest taken by the health care providers in the electronic medical file and its use within the quality improvement process., Setting: Our institution is a 204-bed psychiatric hospital, employing 328 professionals and comprising three sectors: six units of complete hospitalisation (102 beds), one unit of week hospitalisation (15 beds), one unit of emergency (7 beds) and one unit of night hospitalisation (15 beds). Three extrahospital structures include the day hospitalisation (65 places), the medicopsychological centers (CMP) and the part-time therapeutic reception centers (CATTP) of the three sectors., Methods: We conducted face-to-face, semi-structured interviews with health care providers of a public psychiatric hospital. All the solicited people agreed to answer the investigation. The interviews were conducted until no new ideas emerged in the content analysis performed in real time, comprising 60 care providers: 10 psychiatrists, 42 nurses and eight paramedical professionals. Content analysis was performed by two members of the steering committee who were skilled in textual analysis. A descriptive analysis was also performed. The variables were described by proportions and means. The proportions were compared using the Chi-squared test or Fisher exact test where appropriate. A two-tailed P-value of greater than 0.05 was considered to indicate statistical significance. Statistical analyses were carried out using SPSS version 13.0., Results: Ninety-six percent of the interviewed subjects used the electronic medical file. The average number of daily use was seven (S.D.=5). Sixty-seven percent had a favorable opinion of the electronic medical file. Physicians had more frequent favorable opinions than nurses who considered that electronic medical files cannot capture real nursing activity. Health care providers considered that electronic medical file could be associated with improved quality of care, but two points should be taken into account: the increased documentation time (slow system response, multiple screens, the lack of computer knowledge, the absence of bedside documentation technology...) and dysfunctions in the information processing system. This could have an impact on documentation completeness, and quality and could also lead to a reduction of time devoted to care., Conclusion: This study proposes tracks of improvement in the use of the DPIP. In spite of this, a true debate must be initiated on these new information systems in psychiatry since their real objectives can be perceived as ambiguous, so that programs of clarification, education and reinsurance can be set-up.

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.

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.

Legal and technologic trends are making medical records progressively more patient-accessible. In the near future, information technology may make it even easier to provide patients a chance to review their records. One may wonder, however, about the practical use of this technology by patients. Understanding his/her own health record will certainly be one of the main concerns of patients. WRAPIN has been designed to provide patients and citizens with trusted health information. It will help to determine the reliability of documents by checking the ideas contained against established benchmarks, and enable users to determine the relevance of a given document from a page of search results. First, we present what is, in our opinion, the most original and important patient-centred WRAPIN characteristics and functionalities. Then, we compare these characteristics with those of representatives of two main trends in information retrieval: systems based on the popularity of web sites, and on the clustering of web sites. This comparison shows that, even though patients are tempted to use popular search engines, these are not sufficiently specialized in the medical domain to help them understand their own HER.. Finally, we discuss the complexity of medical readings over the Internet and the efforts that are still required in this domain.

Healthcare institutions are looking at ways to increase their efficiency by reducing costs while providing care services with a high level of safety. Thus, hospital information systems have to support quality improvement objectives. The elicitation of the requirements has to meet users' needs in relation to both the quality (efficacy, safety) and the monitoring of all health care activities (traceability). Information analysts need methods to conceptualise clinical information systems that provide actors with individual benefits and guide behavioural changes. A methodology is proposed to elicit and structure users' requirements using a process-oriented analysis, and it is applied to the blood transfusion process. An object-oriented data model of a process has been defined in order to organise the data dictionary. Although some aspects of activity, such as 'where', 'what else', and 'why' are poorly represented by the data model alone, this method of requirement elicitation fits the dynamic of data input for the process to be traced. A hierarchical representation of hospital activities has to be found for the processes to be interrelated, and for their characteristics to be shared, in order to avoid data redundancy and to fit the gathering of data with the provision of care.

Within a hospital, the moving of medical information systems from retrospective data-gathering methods to prospective clinical information systems raises the question of the confidentiality of patient data. A method of improving the traditional matrix model usually used to achieve access controls is described. The event-driven model refers to the way a security system ensures that a given user has a valid "need-to" relationship to a given patient. Events are defined as the occurrence of specific data that trigger the creation or the updating of the relationship between the identity of a user and the identity of a patient (e.g., admission, discharge, transfer, prescription, and report). The creation and the deletion of the relationships between users and patients are based on numerous repositories and working lists of patients. This implementation requires an organization of the hospital activities which is able to manage, in a real-time manner, those repositories as closely as possible to the steps occurring during the patient's care process. Although this approach seems to reasonably fit the dynamic of the care process, it adds significant organizational constraints.

As information databases we consider all the kinds of information repositories that are handled by computer systems. When querying very large information databases, the end-users are often faced with the problem to parse their questions efficiently into the query languages of the computer systems. Conceptual graphs were initially designed for natural language analysis and understanding. Due to their closeness to semantic networks, their expressiveness is powerful enough to be applied to knowledge representation and use by computer systems. This work demonstrates that conceptual graphs are a suitable means to model both the information in patient databases and the queries to these databases, and that operations on graphs can compute the pattern matching process needed to provide the answers. A prototype that exploits this model is presented. Experiments have been made with the material furnished by the Unified Medical Language System project (version 2, 1992) of the National Library of Medicine, USA.