Common data elements for secondary use of electronic health record data for clinical trial execution and serious adverse event reporting

Background: Data capture is one of the most expensive phases during the conduct of a clinical trial and the increasing use of electronic health records (EHR) offers significant savings to clinical research. To facilitate these secondary uses of routinely collected patient data, it is beneficial to know what data elements are captured in clinical trials. Therefore our aim here is to determine the most commonly used data elements in clinical trials and their availability in hospital EHR systems.Methods: Case report forms for 23 clinical trials in differing disease areas were analyzed. Through an iterative and consensus-based process of medical informatics professionals from academia and trial experts from the European pharmaceutical industry, data elements were compiled for all disease areas and with special focus on the reporting of adverse events. Afterwards, data elements were identified and statistics acquired from hospital sites providing data to the EHR4CR project.Results: The analysis identified 133 unique data elements. Fifty elements were congruent with a published data inventory for patient recruitment and 83 new elements were identified for clinical trial execution, including adverse event reporting. Demographic and laboratory elements lead the list of available elements in hospitals EHR systems. For the reporting of serious adverse events only very few elements could be identified in the patient records.Conclusions: Common data elements in clinical trials have been identified and their availability in hospital systems elucidated. Several elements, often those related to reimbursement, are frequently available whereas more specialized elements are ranked at the bottom of the data inventory list. Hospitals that want to obtain the benefits of reusing data for research from their EHR are now able to prioritize their efforts based on this common data element list.</p

Effects of automated alerts on unnecessarily repeated serology tests in a cardiovascular surgery department: a time series analysis

<p>Abstract</p> <p>Background</p> <p>Laboratory testing is frequently unnecessary, particularly repetitive testing. Among the interventions proposed to reduce unnecessary testing, Computerized Decision Support Systems (CDSS) have been shown to be effective, but their impact depends on their technical characteristics. The objective of the study was to evaluate the impact of a Serology-CDSS providing point of care reminders of previous existing serology results, embedded in a Computerized Physician Order Entry at a university teaching hospital in Paris, France.</p> <p>Methods</p> <p>A CDSS was implemented in the Cardiovascular Surgery department of the hospital in order to decrease inappropriate repetitions of viral serology tests (HBV).</p> <p>A time series analysis was performed to assess the impact of the alert on physicians' practices. The study took place between January 2004 and December 2007. The primary outcome was the proportion of unnecessarily repeated HBs antigen tests over the periods of the study. A test was considered unnecessary when it was ordered within 90 days after a previous test for the same patient. A secondary outcome was the proportion of potentially unnecessary HBs antigen test orders cancelled after an alert display.</p> <p>Results</p> <p>In the pre-intervention period, 3,480 viral serology tests were ordered, of which 538 (15.5%) were unnecessarily repeated. During the intervention period, of the 2,095 HBs antigen tests performed, 330 unnecessary repetitions (15.8%) were observed. Before the intervention, the mean proportion of unnecessarily repeated HBs antigen tests increased by 0.4% per month (absolute increase, 95% CI 0.2% to 0.6%, <it>p </it>< 0.001). After the intervention, a significant trend change occurred, with a monthly difference estimated at -0.4% (95% CI -0.7% to -0.1%, <it>p </it>= 0.02) resulting in a stable proportion of unnecessarily repeated HBs antigen tests. A total of 380 unnecessary tests were ordered among 500 alerts displayed (compliance rate 24%).</p> <p>Conclusions</p> <p>The proportion of unnecessarily repeated tests immediately dropped after CDSS implementation and remained stable, contrasting with the significant continuous increase observed before. The compliance rate confirmed the effect of the alerts. It is necessary to continue experimentation with dedicated systems in order to improve understanding of the diversity of CDSS and their impact on clinical practice.</p

A Fast Healthcare Interoperability Resources (FHIR) layer implemented over i2b2

Abstract Background Standards and technical specifications have been developed to define how the information contained in Electronic Health Records (EHRs) should be structured, semantically described, and communicated. Current trends rely on differentiating the representation of data instances from the definition of clinical information models. The dual model approach, which combines a reference model (RM) and a clinical information model (CIM), sets in practice this software design pattern. The most recent initiative, proposed by HL7, is called Fast Health Interoperability Resources (FHIR). The aim of our study was to investigate the feasibility of applying the FHIR standard to modeling and exposing EHR data of the Georges Pompidou European Hospital (HEGP) integrating biology and the bedside (i2b2) clinical data warehouse (CDW). Results We implemented a FHIR server over i2b2 to expose EHR data in relation with five FHIR resources: DiagnosisReport, MedicationOrder, Patient, Encounter, and Medication. The architecture of the server combines a Data Access Object design pattern and FHIR resource providers, implemented using the Java HAPI FHIR API. Two types of queries were tested: query type #1 requests the server to display DiagnosticReport resources, for which the diagnosis code is equal to a given ICD-10 code. A total of 80 DiagnosticReport resources, corresponding to 36 patients, were displayed. Query type #2, requests the server to display MedicationOrder, for which the FHIR Medication identification code is equal to a given code expressed in a French coding system. A total of 503 MedicationOrder resources, corresponding to 290 patients, were displayed. Results were validated by manually comparing the results of each request to the results displayed by an ad-hoc SQL query. Conclusion We showed the feasibility of implementing a Java layer over the i2b2 database model to expose data of the CDW as a set of FHIR resources. An important part of this work was the structural and semantic mapping between the i2b2 model and the FHIR RM. To accomplish this, developers must manually browse the specifications of the FHIR standard. Our source code is freely available and can be adapted for use in other i2b2 sites

Un environnement collaboratif sur Internet pour l'aide au consensus en anatomie pathologie (la plateforme IDEM)

PARIS-BIUSJ-Thèses (751052125) / SudocPARIS-BIUSJ-Mathématiques rech (751052111) / SudocSudocFranceF

Mesures de similarité pour l'aide au consensus en anatomie pathologique

Le système IDEM (Images et Diagnostics par l'Exemple en Médecine) a pour objectif d'assister les experts dans la constitution de descriptions consensuelles de cas anatomopathologiques. Ce système s'appuie sur des mesures de similarités entre les termes de pathologie tumorale mammaire organisés en réseau sémantique. Afin de pouvoir comparer plusieurs mesures de similarités et pouvoir valider l'organisation des termes, des développements ont été effectués par l'extension d'un éditeur d'ontologie. Les résultats de l'évaluation sont présentés

Computation of semantic similarity within an ontology of breast pathology to assist inter-observer consensus

International audienceComputer-assisted consensus in medical imaging involves automatic comparison of morphological abnormalities observed by physicians in images. We built an ontology of morphological abnormalities in breast pathology to assist inter-observer consensus. Concepts of morphological abnormalities extracted from existing terminologies, published grading systems and medical reports were organized in an taxonomic hierarchy and furthermore linked by the relation “is a diagnostic criterion of” according to diagnostic meaning. We implemented position-based, content-based and mixed semantic similarity measures between concepts in this ontology and compared the results with experts’ judgment. The position-based similarity measure using both taxonomic and non-taxonomic relations performed as well as the other measures and was used for automatic comparison of morphological abnormalities within the IDEM computer-assisted consensus platform

Intégration de multiples ontologies en anatomie pathologique

National audienceLa variabilité diagnostique en anatomie pathologique est en partie liée à l'utilisation de systèmes de classification différents, pouvant être considérés comme des points de vue différents, pour décrire des lésions. Notre objectif est de représenter ces points de vue et de proposer une solution pour permettre leur interopérabilité. L'approche hybride décrite par Wache nous permet de développer un système multi ontologique en trois étapes 1) la représentation des points de vue au sein d'ontologies locales, 2) la construction d'un vocabulaire partagé et 3) le développement d'un outil de traduction. L'évaluation du travail, conduite sur 33 cas, a consisté à évaluer les ontologies locales grâce à un outil de validation sémantique de cas et à évaluer l'outil de traduction. Nos résultats montrent que les pathologistes produisent des descriptions qui ne suivent pas toujours les règles d'interprétation des systèmes de classification auxquels ils se réfèrent. Si 62.5% à 100% des concepts des ontologies locales sont traduisibles, nous avons constaté que la validité des cas n'était pas toujours conservée après traduction