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Context: The Unified Model of Information Systems Continuance (UMISC) is a metamodel for the evaluation of clinical information systems (CISs) that integrates constructs from five models that have previously been published in the literature. UMISC was developed at the Georges Pompidou University Hospital (HEGP) in Paris and was partially validated at the Saint Joseph Hospital Group (HPSJ), another acute care institution using the same CIS as HEGP., Objective: The aim of this replication study was twofold: (1) to perform an external validation of UMISC in two different hospitals and country contexts: the Italian Hospital of Buenos Aires (HIBA) in Argentina and the Hospital Sirio Libanes in Sao Paulo, Brazil (HSL); (2) to compare, using the same evaluation model, the determinants of satisfaction, use, and continuance intention observed at HIBA and HSL with those previously observed at HEGP and HPSJ., Methods: The UMISC evaluation questionnaires were translated from their original languages (English and French) to Brazilian Portuguese and Spanish following the translation/back-translation method. These questionnaires were then applied at each target site. The 21 UMISC-associated hypotheses were tested using structural equation modeling (SEM)., Results: A total of 3020 users, 1079 at HIBA and 1941 at the HSL, were included in the analysis. The respondents included 1406 medical staff and 1001 nursing staff. The average profession-adjusted use, overall satisfaction and continuance intention were significantly higher at HIBA than at HSL in the medical and nursing groups. In SEM analysis, UMISC explained 23% and 11% of the CIS use dimension, 72% and 85% of health professionals' satisfaction, and 41% and 60% of continuance intention at HIBA and HSL, respectively. Twenty of the 21 UMISC-related hypotheses were validated in at least one of the four evaluation sites, and 16 were validated in two or more sites., Conclusion: The UMISC evaluation metamodel appears to be a robust comparison and explanatory model of satisfaction, use and continuance intention for CISs in late post adoption situations., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Context: The deployment and long-term acceptance of clinical information systems (CISs) are faced with multiple difficulties. They include insufficient quality of the systems in place and resistance to the multiple changes they induce in care processes. Permanent evaluation of deployed solutions is a prerequisite to their continuous improvement., Objective: The purpose of this study was twofold: (1) To validate the post-adoption unified model of information systems continuance (UMISC) progressively developed at the Georges Pompidou University Hospital (HEGP) in Paris (internal validation); and (2) To compare, using the same evaluation model, the results observed at HEGP with those of the Saint-Joseph Hospital Group (HPSJ), another Paris acute care institution (external validation)., Methods: The UMISC post-adoption model is built around nine dimensions: end-user characteristics, social norm (SN), IS quality (ISQ), facilitating conditions (FC), perceived usefulness (PU), confirmation of expectations (CE), profession-adjusted use (PAU), satisfaction (SAT), and continuance intention (CI). Two semi-quantitative evaluation surveys were performed at HEGP in 2014 and 2015, and one at HPSJ in 2015. Statistical analysis included multiple regression analysis and structural equation modeling (SEM)., Results: The analysis concerned 459 responders, 264 at HEGP and 195 at HPSJ. UMISC indicators, with the exception of SN, are superior at HEGP than at HPSJ, which had a shorter CIS anteriority than HEGP. In SEM analysis, the UMISC model explained 25% and 40% of the CIS use, 92% and 93% of health professionals' satisfaction, and 72% and 71% of continuance intention at HEGP and HPSJ, respectively. Seventeen of the 21 tested UMISC hypotheses were supported in at least one of the two sites., Conclusion: The UMISC evaluation model can be used as a comparison and explanatory model of CIS use, satisfaction and continuance intention in post-CIS adoption situations that become prevalent in current electronic hospitals., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Clinical information systems (CISs) in some hospitals streamline the data management from data warehouses. These warehouses contain heterogeneous information from all medical specialties that offer patient care services. It is increasingly difficult to manage large volumes of data in a specific clinical context such as quality coding of medical services. The document-based Not Only SQL (NO-SQL) model can provide an accessible, extensive and robust coding data management framework while maintaining certain flexibility. This paper focus on the design and implementation of a big data-coding warehouse, it also defines the rules to convert a conceptual model of coding into a document-oriented logical model. Using that model, we implemented, analyzed a big data-coding warehouse via the Mongodb database, and evaluated it using data research mono- and multi-criteria and then calculated the precision of our model.

Standards Data Warehouse has been implemented in many hospitals. It has enormous potential to improve performance measurement and health care quality. Accessing, organizing, and using these data to optimize clinical coding are evolving challenges for hospital systems. This paper describes development of a coding data warehouse based Entities-Attribute-Value (EAV) that we created by importing data from the clinical data warehouse (CDW) of public hospital. In particular, it focuses on design, implementation, and evaluation of the warehouse. Moreover, it defines the rules to convert a conceptual model of coding into an EAV logical model and his implementation using integrating biology and the bedside (i2b2). We evaluate it using data research mono and multi-criteria and then calculate the precision of our model. The result shows that, the coding data warehouse provides with good accuracy, an association of diagnostic code and medical act closer the patient's clinical landscape. Doctors without knowledge of coding rules could use this information to optimize and improve the diagnostic coding.

Background: When developed jointly with clinical information systems, clinical data warehouses (CDWs) facilitate the reuse of healthcare data and leverage clinical research., Objective: To describe both data access and use for clinical research, epidemiology and health service research of the "Hôpital Européen Georges Pompidou" (HEGP) CDW., Methods: The CDW has been developed since 2008 using an i2b2 platform. It was made available to health professionals and researchers in October 2010. Procedures to access data have been implemented and different access levels have been distinguished according to the nature of queries., Results: As of July 2016, the CDW contained the consolidated data of over 860,000 patients followed since the opening of the HEGP hospital in July 2000. These data correspond to more than 122 million clinical item values, 124 million biological item values, and 3.7 million free text reports. The ethics committee of the hospital evaluates all CDW projects that generate secondary data marts. Characteristics of the 74 research projects validated between January 2011 and December 2015 are described., Conclusion: The use of HEGP CDWs is a key facilitator for clinical research studies. It required however important methodological and organizational support efforts from a biomedical informatics department., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Context: Clinical information systems (CIS) are developed with the aim of improving both the efficiency and the quality of care., Objective: This position paper is based on the hypothesis that such vision is partly a utopian view of the emerging eSociety., Methods: Examples are drawn from 15 years of experience with the fully integrated Georges Pompidou University Hospital (HEGP) CIS and temporal data series extracted from the data warehouses of Assistance Publique - Hôpitaux de Paris (AP-HP) acute care hospitals which share the same administrative organization as HEGP. Three main virtuous circles are considered: user satisfaction vs. system use, system use vs. cost efficiency, and system use vs quality of care., Results: In structural equation models (SEM), the positive bidirectional relationship between user satisfaction and use was only observed in the early HEGP CIS deployment phase (first four years) but disappeared in late post-adoption (≥8 years). From 2009 to 2013, financial efficiency of 20 AP-HP hospitals evaluated with stochastic frontier analysis (SFA) models diminished by 0.5% per year. The lower decrease of efficiency observed between the three hospitals equipped with a more mature CIS and the 17 other hospitals was of the same order of magnitude than the difference observed between pediatric and non-pediatric hospitals. Outcome quality benefits that would bring evidence to the system use vs. quality loop are unlikely to be obtained in a near future since they require integration with population-based outcome measures including mortality, morbidity, and quality of life that may not be easily available., Conclusion: Barriers to making the transformation of the utopian part of the CIS virtuous circles happen should be overcome to actually benefit the emerging eSociety.

Context: Meaningful use and end-user satisfaction are two major components of the success of a clinical information system (CIS). The purpose of this study was to longitudinally measure and analyze the CIS use and satisfaction determinants in a multi-professional group at the Georges Pompidou university hospital (HEGP) in Paris., Methods: From the different evaluation surveys performed at HEGP, three periods were considered corresponding to 4, 8 and over 10 years after the first CIS deployment in 2000, respectively. Six acceptance dimensions were considered: CIS quality (CISQ), facilitating conditions (FC), perceived usefulness (PU), confirmation of expectations (CE), use, and global satisfaction (GS). Relationships between these constructs were tested through multiple regressions analysis and structural equation modeling (SEM)., Results: Responses were obtained from 298, 332, and 448 users for the three periods considered. CIS acceptance dimensions progressively and significantly increased over time. Significant differences between professions were observed with an initial low PU among medical staff. In the early deployment phase, GS appeared to be determined by CIS use, CISQ and PU (R(2)=.53 in SEM). In the very late post-adoption phase, GS was strongly determined by CISQ, CE, and PU (R(2)=.86 in SEM) and was no longer associated with CIS use., Conclusion: Acceptance models should be adapted to the phase of deployment of a CIS and integrate end-users' individual characteristics. Progressive reduction over time of the positive relationships between CIS use and satisfaction could possibly be considered as a maturity indicator of CIS deployment. These observations validate the introduction in post-adoption models of a continuance intention dimension., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

Short-stay MSO (Medicine, Surgery, Obstetrics) hospitalization activities in public and private hospitals providing public services are funded through charges for the services provided (T2A in French). Coding must be well matched to the severity of the patient's condition, to ensure that appropriate funding is provided to the hospital. We propose the use of an autocompletion process and multidimensional matrix, to help physicians to improve the expression of information and to optimize clinical coding. With this approach, physicians without knowledge of the encoding rules begin from a rough concept, which is gradually refined through semantic proximity and uses information on the associated codes stemming of optimized knowledge bases of diagnosis code.

The rise of personalized medicine and the availability of high-throughput molecular analyses in the context of clinical care have increased the need for adequate tools for translational researchers to manage and explore these data. We reviewed the biomedical literature for translational platforms allowing the management and exploration of clinical and omics data, and identified seven platforms: BRISK, caTRIP, cBio Cancer Portal, G-DOC, iCOD, iDASH and tranSMART. We analyzed these platforms along seven major axes. (1) The community axis regrouped information regarding initiators and funders of the project, as well as availability status and references. (2) We regrouped under the information content axis the nature of the clinical and omics data handled by each system. (3) The privacy management environment axis encompassed functionalities allowing control over data privacy. (4) In the analysis support axis, we detailed the analytical and statistical tools provided by the platforms. We also explored (5) interoperability support and (6) system requirements. The final axis (7) platform support listed the availability of documentation and installation procedures. A large heterogeneity was observed in regard to the capability to manage phenotype information in addition to omics data, their security and interoperability features. The analytical and visualization features strongly depend on the considered platform. Similarly, the availability of the systems is variable. This review aims at providing the reader with the background to choose the platform best suited to their needs. To conclude, we discuss the desiderata for optimal translational research platforms, in terms of privacy, interoperability and technical features., (© The Author 2014. Published by Oxford University Press.)

Purpose: Efficient and adequate coding is essential for all hospitals to optimize funding, follow activity, and perform epidemiological studies., Objective: We propose an autocompletion method for optimizing diagnostic coding in acute care hospitals., Methods: Using a terminology snowflake model integrating SNOMED 3.5 and ICD-10 codes, autocompletion algorithms generate a list of diagnostic expressions from partial input concepts., Results: A general autocompletion component has been developed and tested on a set of inpatient summary reports. Concepts expressed as strings of three or four characters return a noisy list of diagnostic labels or codes. Concepts expressed as groups of strings return lists that are semantically close to the labels present in hospital reports. The most pertinent information lies in the length of the expressions entered., Conclusion: Autocompletion can be a complementary tool to existing coding support systems.

Purpose: The evaluation of end-user satisfaction is an essential part of any clinical information system (CIS) project. The purpose of this study is to evaluate the determinants of CIS continuance intention in a late post-adoption phase at the Georges Pompidou University Hospital (HEGP) in Paris., Methods: We designed an electronic survey instrument based on an IT post-adoption model (ITPAM) developed from three previous models, i.e., the Delone and McLean Information Success Model, the Davis TAM model and the Bhattacherjee information system continuance intention model., Results: 419 questionnaires were collected from CIS users directly involved in patient care. The perceived CIS quality, usefulness and user satisfaction are significantly lower for medical professions than other professional groups. Continuance intention is very high within all professional subgroups. In a multiple regression analysis, the global satisfaction (R(2) = .780) was positively and significantly correlated with CIS quality, confirmation of expectations and perceived CIS usefulness. The continuance intention (R(2) = .392) was positively and significantly correlated with perceived CIS usefulness, confirmation of expectations and global satisfaction., Conclusion: In a late post-adoption CIS deployment phase, continuance intention does not significantly depend on individual end user characteristics but is significantly associated with the perceived CIS usefulness, confirmation of expectations and global satisfaction.

This article presents the results of one of the stages of the user-centered evaluation conducted in a framework of the EU project Khresmoi. In a controlled environment, users were asked to perform health-related tasks using a search engine specifically developed for trustworthy online health information. Twenty seven participants from largely the Czech Republic and France took part in the evaluation. All reported overall a positive experience, while some features caused some criticism. Learning points are summed up regarding running such types of evaluations with the general public and specifically with patients.

Objective: The main objective of this study was to assess the diagnostic performances of an alert system integrated into the CPOE/EMR system for renally cleared drug dosing control. The generated alerts were compared with the daily routine practice of pharmacists as part of the analysis of medication orders., Materials and Methods: The pharmacists performed their analysis of medication orders as usual and were not aware of the alert system interventions that were not displayed for the purpose of the study neither to the physician nor to the pharmacist but kept with associate recommendations in a log file. A senior pharmacist analyzed the results of medication order analysis with and without the alert system. The unit of analysis was the drug prescription line. The primary study endpoints were the detection of drug dose prescription errors and inter-rater reliability (Kappa coefficient) between the alert system and the pharmacists in the detection of drug dose error., Results: The alert system fired alerts in 8.41% (421/5006) of cases: 5.65% (283/5006) "exceeds max daily dose" alerts and 2.76% (138/5006) "under-dose" alerts. The alert system and the pharmacists showed a relatively poor concordance: 0.106 (CI 95% [0.068-0.144]). According to the senior pharmacist review, the alert system fired more appropriate alerts than pharmacists, and made fewer errors than pharmacists in analyzing drug dose prescriptions: 143 for the alert system and 261 for the pharmacists. Unlike the alert system, most diagnostic errors made by the pharmacists were 'false negatives'. The pharmacists were not able to analyze a significant number (2097; 25.42%) of drug prescription lines because understaffing., Conclusion: This study strongly suggests that an alert system would be complementary to the pharmacists' activity and contribute to drug prescription safety., (Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.)

Phenome-Wide Association Studies (PheWAS) investigate whether genetic polymorphisms associated with a phenotype are also associated with other diagnoses. In this study, we have developed new methods to perform a PheWAS based on ICD-10 codes and biological test results, and to use a quantitative trait as the selection criterion. We tested our approach on thiopurine S-methyltransferase (TPMT) activity in patients treated by thiopurine drugs. We developed 2 aggregation methods for the ICD-10 codes: an ICD-10 hierarchy and a mapping to existing ICD-9-CM based PheWAS codes. Eleven biological test results were also analyzed using discretization algorithms. We applied these methods in patients having a TPMT activity assessment from the clinical data warehouse of a French academic hospital between January 2000 and July 2013. Data after initiation of thiopurine treatment were analyzed and patient groups were compared according to their TPMT activity level. A total of 442 patient records were analyzed representing 10,252 ICD-10 codes and 72,711 biological test results. The results from the ICD-9-CM based PheWAS codes and ICD-10 hierarchy codes were concordant. Cross-validation with the biological test results allowed us to validate the ICD phenotypes. Iron-deficiency anemia and diabetes mellitus were associated with a very high TPMT activity (p = 0.0004 and p = 0.0015, respectively). We describe here an original method to perform PheWAS on a quantitative trait using both ICD-10 diagnosis codes and biological test results to identify associated phenotypes. In the field of pharmacogenomics, PheWAS allow for the identification of new subgroups of patients who require personalized clinical and therapeutic management.

The objective of this case report is to evaluate the use of a clinical data warehouse coupled with a clinical information system to test and refine alerts for medication orders control before they were fully implemented. A clinical decision rule refinement process was used to assess alerts. The criteria assessed were the frequencies of alerts for initial prescriptions of 10 medications whose dosage levels depend on renal function thresholds. In the first iteration of the process, the frequency of the 'exceeds maximum daily dose' alerts was 7.10% (617/8692), while that of the 'under dose' alerts was 3.14% (273/8692). Indicators were presented to the experts. During the different iterations of the process, 45 (16.07%) decision rules were removed, 105 (37.5%) were changed and 136 new rules were introduced. Extensive retrospective analysis of physicians' medication orders stored in a clinical data warehouse facilitates alert optimization toward the goal of maximizing the safety of the patient and minimizing overridden alerts.

In this paper we present an application of pharmaceutical validation of medication based on an OWL ontology and business rules or more specifically clinical decision rules. This application has been developed based on a prototype that enables business users to author, execute and manage their Business Rules over OWL Ontology. This prototype is based on the Business Rule Management System (BRMS) IBM WebSphere ILOG JRules.

Objectives: Several alert systems have been developed to improve the patient safety aspects of clinical information systems (CIS). Most studies have focused on the evaluation of these systems, with little information provided about the methodology leading to system implementation. We propose here an 'agile' business rule design framework (BRDF) supporting both the design of alerts for the validation of drug prescriptions and the incorporation of the end user into the design process., Methods: We analyzed the unified process (UP) design life cycle and defined the activities, subactivities, actors and UML artifacts that could be used to enhance the agility of the proposed framework. We then applied the proposed framework to two different sets of data in the context of the Georges Pompidou University Hospital (HEGP) CIS., Results: We introduced two new subactivities into UP: business rule specification and business rule instantiation activity. The pharmacist made an effective contribution to five of the eight BRDF design activities. Validation of the two new subactivities was effected in the context of drug dosage adaption to the patients' clinical and biological contexts. Pilot experiment shows that business rules modeled with BRDF and implemented as an alert system triggered an alert for 5824 of the 71,413 prescriptions considered (8.16%)., Conclusion: A business rule design framework approach meets one of the strategic objectives for decision support design by taking into account three important criteria posing a particular challenge to system designers: 1) business processes, 2) knowledge modeling of the context of application, and 3) the agility of the various design steps.

The evaluation of a clinical information system (CIS) at different stages of deployment and routine use is a key factor to improve acceptability and use by health professionals. This paper examines on an expectation-confirmation model (ITPAM) the relationships between the determinants of success of a CIS in a cross-sectional survey performed at the Georges Pompidou University Hospital (HEGP). Results for the groups of physicians and nurses that replied to the survey (n=312) suggest that health professional satisfaction (overall R(2)=0.60) is determined by the quality of user support (r=.21, p=<0001), ease of use (r=.19, p=<0001), confirmation of expectations (r=.15, p=.0037), usefulness (r=.12, p=.0068), and compatibility (r=.10, p=.0206). The best predictor of physician satisfaction (R(2)=0.71) was compatibility (r=.21, p=.0072) whereas for nurses (R(2)=0.52) it was user support (r=.22, p=<0001) and ease of use (r=.22, p=.0001). Confirmation of expectations had an impact on post-adoption expectation and user's satisfaction, and confirms its importance for CIS evaluation studies.

Objectives: Choosing and justifying the right amount of investment in healthcare information technologies (HITECH or HIT) in hospitals is an ever increasing challenge. Our objectives are to assess the financial impact of HIT on hospital outcome, and propose decision-helping tools that could be used to rationalize the distribution of hospital finances., Design: We used a production function and microeconomic tools on data of 21 Paris university hospitals recorded from 1998 to 2006 to compute the elasticity coefficients of HIT versus non-HIT capital and labor as regards to hospital financial outcome and optimize the distribution of investments according to the productivity associated with each input., Results: HIT inputs and non-HIT inputs both have a positive and significant impact on hospital production (elasticity coefficients respectively of 0.106 and 0.893; R(2) of 0.92). We forecast 2006 results from the 1998 to 2005 dataset with an accuracy of +0.61%. With the model used, the best proportion of HIT investments was estimated to be 10.6% of total input and this was predicted to lead to a total saving of 388 million Euros for the 2006 dataset., Conclusion: Considering HIT investment from the point of view of a global portfolio and applying econometric and microeconomic tools allow the required confidence level to be attained for choosing the right amount of HIT investments. It could also allow hospitals using these tools to make substantial savings, and help them forecast their choices for the following year for better HITECH governance in the current stimulation context., ((c) 2010 Elsevier Ireland Ltd. All rights reserved.)

Clinical Data Warehouses (CDW) can complement current Clinical Information Systems (CIS) with functions that are not easily implemented by traditional operational database systems. Here, we describe the design and deployment strategy used at the Pompidou University Hospital in southwest Paris. Four realms are described: technological realm, data realm, restitution realm, and administration realm. The corresponding UML use cases and the mapping rules from the shared integrated electronic health records to the five axes of the i2b2 CDW star model are presented. Priority is given to the anonymization and security principles used for the 1.2 million patient records currently stored in the CDW. Exploitation of a CDW by clinicians and investigators can facilitate clinical research, quality evaluations and outcome studies. These indirect benefits are among the reasons for the continuous use of an integrated CIS.

The diffusion of information technology (IT) in healthcare systems to support clinical processes makes the evaluation of physician and nurse post-adoption an important challenge for clinical information systems (CIS). This paper examines the relationships between the determinants of success of a CIS based on an expectation-confirmation paradigm in a cross-sectional survey performed at the Sherbrooke University Hospital (CHUS). 32.2% (161) of physicians and 27.1% (352) of nurses responded to the survey questionnaires. Results suggested that physician and nurse satisfaction is determined differently according to post-adoption expectations: compatibility, confirmation of expectations, usefulness, ease of use, and support. The best predictor of physician satisfaction was perceived usefulness (r=.25, p=.0003) whereas for nurses it was ease of use (r=.18, p=.0003). Confirmation of expectations was strongly associated with each post-adoption expectation and positions its importance in CIS design and redesign. This study draws attention to the differences between physician and nurse perceptions of information technology and emphasizes post-adoption evaluation to measure CIS success. Physicians and nurses post-adoption expectations were key factors to warn again potential discontinuance.

Although clinical alarm systems are part of the knowledge management setting within healthcare organisations, modelling of business processes related to decision support and knowledge representation of decision rules are seldom described. We propose a customization of the Unified Process that takes into account user requirements for clinical alarm systems by introducing the Semantics of Business Vocabulary and Business Rules (SBVR). This methodology was applied to the design and implementation of a clinical alarm system for pharmaceutical validation at the European Hospital Georges Pompidou (HEGP). Rules were implemented using the IlogJRules Business Rule Management System. We produced 3 business rules patterns and 427 instances of rules. As SBVR is close to natural language, pharmacists were able to understand rules and participate to their design.

Objectives: To examine the different methods that can be used in the quantification of the added value of information technologies (IT) in the health care sector. This quantification represents a major issue for decision-makers and health care professionals when they have to plan an IT investment., Methods: Articles were chosen via Medline, internet and the University of Geneva bibliographic portal. Some of the papers were obtained directly from their authors. We examine the most current methods used to evaluate IT return on investment (ROI) in the general business and in the health care sector, drawing attention on methods traditionally used in macroeconomic studies that could reveal themselves disruptive for IT ROI impact evaluation in hospitals., Results: Financial and accounting methods can provide interesting data on a specific IT project but are usually incomplete for revealing the global IT investment influence. Econometric methods tend to demonstrate the positive impact of health care IT (HIT) on hospital production and productivity. Hospitals having higher levels of IT investment tend to deliver a higher level of clinical quality and show improved hospital cost performances., Conclusions: Information technologies are so intermingled with people and processes that the identification of specific IT benefit remains questionable. Using macroeconomic tools could be the best way to analyze and compute IT ROI in health care. Econometric tools take into account all types investments (inputs) and all the returns (outputs) enabling the precise measurement of IT investments impact, breakeven points, and possible threshold levels, thus providing helpful intelligence to reach the higher levels of IT governance in hospitals.

Integrating clinical research data entry with patient care data entry is a challenging issue. At the G. Pompidou European Hospital (HEGP), cardiovascular radiology reports are captured twice, first in the Electronic Health Record (EHR) and then in a national clinical research server. Informatics standards are different for EHR (HL7 CDA) and clinical research (CDISC ODM). The objective of this work is to feed both the EHR and a Clinical Research Data Management System (CDMS) from a single multipurpose form. We adopted and compared two approaches. First approach consists in implementing the single "care-research" form within the EHR and aligning XML structures of HL7 CDA document and CDISC ODM message to export relevant data from EHR to CDMS. Second approach consists in displaying a single "care-research" XForms form within the EHR and generating both HL7 CDA document and CDISC message to feed both EHR and CDMS. The solution based on XForms avoids overloading both EHR and CDMS with irrelevant information. Beyond syntactic interoperability, a perspective is to address the issue of semantic interoperability between both domains.

Structured entry forms for clinical records should be updated to take into account the physicians' needs during consultation and advances in medical knowledge and practice. We updated the computerized medical record form of a hypertension clinic, based on its previous use and clinical guidelines. A statistical analysis of previously completed forms identified several unnecessary items rarely used by clinicians. A terminological analysis of guidelines and of free-text answers on completed forms identified several new topics relevant to current clinical practice. We therefore added new items to the form and some topics previously recorded as free text were itemized. We collaborated with clinicians in interpretation of the results of the statistical and terminological analyses used as the starting point and guide for this updating process.

MedDRA and WHO-ART are the terminologies used to encode drug safety reports. The standardisation achieved with these terminologies facilitates: 1) The sharing of safety databases; 2) Data mining for the continuous reassessment of benefit-risk ratio at national or international level or in the pharmaceutical industry. There is some debate about the capacity of these terminologies for retrieving case reports related to similar medical conditions. We have developed a resource that allows grouping similar medical conditions more effectively than WHO-ART and MedDRA. We describe here a software tool facilitating the use of this terminological resource thanks to an RDF framework with support for RDF Schema inferencing and querying. This tool eases coding and data retrieval in drug safety.

Objectives: The effectiveness of computerized clinical decision support systems (CDSS) depends on the quality of the knowledge they refer to. In this article, we are interested in the acquisition, modeling and representation of the knowledge embedded in the "national reference framework of drug-drug interaction" published by the French Health Products Safety Agency., Methods: A model of drug-drug interactions has been designed using bottom-up and top-down approaches. This model is the basis for the design of an XML format to represent and extract information on drug interactions from the reference framework., Results: A specific tool has been developed to extract the information from a corpus of 1053 drug monographs using a methodology similar to the one used by the GEM-Cutter tool to extract information from clinical guidelines. Strategies to integrate the XML files produced into CDDSSs are discussed., Discussion-Conclusion: Modeling and acquisition of drug-drug interaction knowledge from a corpus of drug monographs is a potential approach to foster the development of CDSS and improve their specificity.

The quantification of the added value of information technologies (IT) in the health sector is a major issue for decision-makers and health care professionals. This paper relates the application of an economic production function in hospitals with different integration levels of their clinical information systems (CIS). The study concerns 17 university hospitals within the Assistance Publique Hôpitaux de Paris group that were followed from 1998 to 2005. Using an extended Cobb-Douglas production function, yearly incomes (Y) were correlated with three inputs: capital (K), labor (L) and IT expenses (T). The results indicate that incomes are significantly and positively associated with the three input variables with elasticity coefficients: alpha, beta and gamma of 0.81, 0.17, and 0.09 that appear to be in the range of values found in secondary and tertiary sectors. The IT elasticity coefficient (gamma) is higher in the subgroup of 6 hospitals that integrate, or started to integrate, a complete CIS within the study period than in the 11 reference hospitals. In a general production function, hospital costs appear to be positively connected to the level of IT expenses, capital and labor. Calculations in two subgroups of AP-HP hospitals divided according to the importance of the IT integration level seem to indicate that the more the clinical information system is integrated, the more its influence is positive in hospital production. The results of this first survey are sufficiently encouraging to try to refine them (better granularity) and to spread them in time (over a longer period) and space (to other hospital structures).

Automated signal generation in pharmacovigilance implements unsupervised statistical machine learning techniques in order to discover unknown adverse drug reactions (ADR) in spontaneous reporting systems. The impact of the terminology used for coding ADRs has not been addressed previously. The Medical Dictionary for Regulatory Activities (MedDRA) used worldwide in pharmacovigilance cases does not provide formal definitions of terms. We have built an ontology of ADRs to describe semantics of MedDRA terms. Ontological subsumption and approximate matching inferences allow a better grouping of medically related conditions. Signal generation performances are significantly improved but time consumption related to modelization remains very important.

For medical decisions, healthcare professionals need that all required information is both correct and easily available. We address the issue of integrating anatomical pathology department to the healthcare enterprise. The pathology workflow from order to report, including specimen process and image acquisition was modeled. Corresponding integration profiles were addressed by expansion of the IHE (Integrating the Healthcare Enterprise) initiative. Implementation using respectively DICOM Structured Report (SR) and DICOM Slide-Coordinate Microscopy (SM) was tested. The two main integration profiles--pathology general workflow and pathology image workflow--rely on 13 transactions based on HL7 or DICOM standard. We propose a model of the case in anatomical pathology and of other information entities (orders, image folders and reports) and real-world objects (specimen, tissue samples, slides, etc). Cases representation in XML schemas, based on DICOM specification, allows producing DICOM image files and reports to be stored into a PACS (Picture Archiving and Communication System.

We carried out a systematic review of published trials to identify the methodological characteristics of studies and technical characteristics of computerized clinical decision support systems (CCDSSs) associated with efficacy for the main outcome of the study. Four characteristics of the content of decision support and the way in which the user is provided with assistance seem to be associated with the success of CCDSSs: a) System-initiated interventions, b) Assistance without user control over output, c) Systems in which data are automatically retrieved from the electronic medical record and d) Systems providing corollary actions in CPOE. Major differences in outcome reporting between studies could be reduced by the use of dedicated tools to standardize methodological reporting.

Clinical Information Systems (CIS) implementation has faced user resistance. Consequently, we aimed to assess the acceptability of an integrated CIS. We designed an electronic survey instrument from two theoretical models (Delone and McLean, and Technology Acceptance Model). Dimensions hypothesized to be determinant of user satisfaction were: user characteristics, CIS use, quality, usefulness, and service quality. The questionnaire was administered to physicians, nurses and medical secretaries of the Georges Pompidou university Hospital (HEGP) in Paris. Answers were obtained from 324 users (93 physicians, 174 nurses, and 57 secretaries). Cronbach's alpha coefficients showed a correct reliability within each dimension. Secretaries and nurses were more satisfied with the CIS than physicians. Except for CIS use, after adjustment for confounders, female gender, perceived CIS quality, usefulness, and service quality were strongly correlated with user satisfaction. This study reinforces the necessity of several models and dimensions to evaluate the acceptability of a complex CIS, with a specific approach for different user profiles.

WHO-ART was developed by the WHO collaborating centre for international drug monitoring in order to code adverse drug reactions. We assume that computation of semantic distance between WHO-ART terms may be an efficient way to group related medical conditions in the WHO database in order to improve signal detection. Our objective was to develop a method for clustering WHO-ART terms according to some proximity of their meanings. Our material comprises 758 WHO-ART terms. A formal definition was acquired for each term as a list of elementary concepts belonging to SNOMED international axes and characterized by modifier terms in some cases. Clustering was implemented as a terminology service on a J2EE server. Two different unsupervised machine learning algorithms (KMeans, Pvclust) clustered WHO-ART terms according to a semantic distance operator previously described. Pvclust grouped 51% of WHO-ART terms. K-Means grouped 100% of WHO-ART terms but 25% clusters were heterogeneous with k = 180 clusters and 6% clusters were heterogeneous with k = 32 clusters. Clustering algorithms associated to semantic distance could suggest potential groupings of WHO-ART terms that need validation according to the user's requirements.

Automated signal generation is a growing field in pharmacovigilance that relies on data mining of huge spontaneous reporting systems for detecting unknown adverse drug reactions (ADR). Previous implementations of quantitative techniques did not take into account issues related to the medical dictionary for regulatory activities (MedDRA) terminology used for coding ADRs. MedDRA is a first generation terminology lacking formal definitions; grouping of similar medical conditions is not accurate due to taxonomic limitations. Our objective was to build a data-mining tool that improves signal detection algorithms by performing terminological reasoning on MedDRA codes described with the DAML+OIL description logic. We propose the PharmaMiner tool that implements quantitative techniques based on underlying statistical and bayesian models. It is a JAVA application displaying results in tabular format and performing terminological reasoning with the Racer inference engine. The mean frequency of drug-adverse effect associations in the French database was 2.66. Subsumption reasoning based on MedDRA taxonomical hierarchy produced a mean number of occurrence of 2.92 versus 3.63 (p < 0.001) obtained with a combined technique using subsumption and approximate matching reasoning based on the ontological structure. Semantic integration of terminological systems with data mining methods is a promising technique for improving machine learning in medical databases.

The objective of this study was to analyze the impact of medication ordering and administration functions of CPOE on doctor-nurse communications and cooperation. We performed an extensive analysis of the work situations in several departments of three different hospitals. One of the hospitals is still using paper-based orders, the second one is currently implementing a patient care information system (PCIS), but the analysis was carried out with paper-based orders. The third hospital has a PCIS installed with available medication ordering functions. We used standard methods from cognitive psychology to analyze physicians, and nurses' activity, communications and cooperation. This approach was combined with a usability analysis of both work systems, paper and computer-based. The paper-based situation is characterized by a synchronous cooperation with a distributed decision-making where physicians and nurses rely mostly on verbal communications to coordinate their actions; paper order sheets are weakly structured and poorly support the documentation task. In the computer situation, physicians and nurses work in an asynchronous mode, and leave to the system the coordination of their actions. Orders are exhaustively documented but some data may be misinterpreted. Some of these problems are due to usability flaws of the Human Computer Interface. We conclude with recommendations for usability improvement of CPOE systems, combined with recommendations for the organization of doctor-nurse communication when implementing such systems.

Computerized Physician Order Entry (CPOE) addresses critical functions in healthcare systems. As the name clearly indicates, these systems focus on order entry. With regard to medication orders, such systems generally force physicians to enter exhaustively documented orders. But a cognitive analysis of the physician's medication ordering task shows that order entry is the last (and least) important step of the entire cognitive therapeutic decision making task. We performed a comparative analysis of these complex cognitive tasks in two working environments, computer-based and paper-based. The results showed that information gathering, selection and interpretation are critical cognitive functions to support the therapeutic decision making. Thus the most important requirement from the physician's perspective would be an efficient display of relevant information provided first in the form of a summarized view of the patient's current treatment, followed by in a more detailed focused display of those items pertinent to the current situation. The CPOE system examined obviously failed to provide the physicians this critical summarized view. Following these results, consistent with users' complaints, the Company decided to engage in a significant re-engineering process of their application.

In a distributed patient record environment, we analyze the processes needed to ensure exchange and access to EHR data. We propose an adapted method and the tools for data synchronization. Our study takes into account the issue of user rights management for data access and decreasing the amount of data exchanged over the network. We describe a XML-based synchronization model that is portable and independent of specific medical data models. The implemented platform consists of several servers, of local network clients, of workstations running user's interfaces and of data exchange and synchronization tools.

Background: Pharmacovigilance experts detect new adverse drug reactions (ADR) by manually reviewing spontaneous reporting systems. Automated signal generation aims to focus the attention of experts on drug-adverse event associations which are disproportionally present in the database. Although adverse events are coded by means of controlled vocabularies such as the MedDRA dictionary, this semantic information is not taken into account for signal generation., Objective: To improve the performance of current signal detection algorithms using knowledge based approach., Method: We developed a formal ontology of ADRs and built a data mining tool that uses description logic representations of MedDRA terms to group medically related case reports., Results: This knowledge based approach increased the sensitivity of signal detection with no decrease in specificity., Discussion: A knowledge based approach improved the performance of signal detection tools. However, the huge work-load involved in the knowledge engineering step limits the use of this approach for machine learning.

Implementation of CPOE systems in Healthcare Institutions has proven efficient in reducing medication errors but it also induces hidden side-effects on Doctor-Nurse cooperation. We propose a usability engineering approach to this problem. An extensive activity analysis of the medication ordering and administration process was performed in several departments of 3 different hospitals. Two of these hospitals are still using paper-based orders, while the 3rd one is in the roll-out phase of medication functions of its CPOE system. We performed a usability assessment of this CPOE system. The usability assessment uncovered usability problems for the entry of medication administration time scheduling by the physician and revealed that the information can be ambiguous for the nurse. The comparison of cooperation models in both situation shows that users tend to adopt a distributed decision making paradigm in the paper-based situation, while the CPOE system supports a centralized decision making process. This analysis can support recommendation for the re-engineering of the Human-Computer Interface.

In the pathology domain, consensus sessions around multi-headed microscopes enhance reproducibility and can reduce inter- and intra-observer variability. Computerized tools and Web technology could facilitate the organization of consensus sessions and assist pathologists to agree on features that are relevant to diagnosis. In the context of the IDEM project, whose aim is to achieve a computerized platform to allow pathologists to derive consensual diagnostic during Internet-based collaborative sessions, we propose a new extension of the existing TELESLIDE format. This new extended format enables the storage and the exchange of multi-experts descriptions that will be processed by the IDEM consensus engine to produce consensual descriptions. We describe this new format and its implementation in the IDEM teleconsensus platform.

Allowing exchange of information and cooperation among network-wide distributed and heterogeneous applications is a major need of current health-care information systems. The European project SynEx aims at developing an integration platform for both new and legacy applications on each partner's site. We developed, in this project, mediation services based on the generic and reusable software components that facilitate the construction of an integration platform and ease the communication and the meaningful transformation among distributed and heterogeneous applications. The main component of the mediation services is named Pilot, which serves as an intelligent broker. It uses a multi-agents service model allowing the integration platform to be multi-servers. It transforms a client request into a valid high level service on the platform. Each service is broken up into several elementary steps by the Pilot. For each step, the Pilot uses an agent to realize the operation configured by the step. At runtime, the Pilot synchronizes the execution of different steps. To ease the communication and the interaction with the heterogeneous systems, an agent can integrate a Mediator. The Mediators are the communication and interpretation tools within the mediation services. We have developed a generic model that can be specialized for creating specific mediators for the different use cases. The mediator model uses two interfaces to connect the mediator with two systems that need to communicate. Each interface deals with the three aspects through three managers (the Communication Manager, the Syntax Manager and the Semantic Manager). Some ready-to-use specializations are developed for some well defined cases which can reduce the development effort. Once a manager is specialized, it can be used in different combinations with other managers to resolve different problems. The meaningful transformation is ensured on a semantic level in each mediator through the Semantic Model component. This last component allows the mapping among different vocabularies used by different systems through a shared ontology which allows the mapping process to focus on the meaning of the transformed information. We have used XML in different components of the mediation services as the interchange format and the description format. This has enhanced the flexibility of the components. The component based approach allows the generic components to be reused in different contexts and also allows the mediations services to be open to integrate other available technologies thus largely reduce the development efforts.

Objectives: The opening of the Georges Pompidou University Hospital (HEGP) in southwest Paris from the merging of three aging facilities was the opportunity to conceive and deploy a brand new clinical information system (CIS) based on a component-based approach. This paper describes the process of selection of the business components, the main functions currently in use, and the technical infrastructure that proved necessary., Methods: The HEGP CIS features generic and healthcare-related components. The generic components include a reference manager, a security manager, a document manager, a Corba bus, and various mediation and supervision tools. The healthcare-related components include the patient, healthcare record, act management, and resource scheduler components., Results: Major functions of CIS were operational at the opening of the hospital in July 2000. Two years later, the unique patient record and the provider order entry system were used in 96% of the concerned healthcare units. Sixty-five percent of the biological orders and 55% of the imaging orders were directly entered by the physicians. Access to investigation results including on-line availability of images is used by physicians in 100% of the units., Discussion and Conclusion: A component-based approach was found to be high-performing and cost-effective for the design and deployment of HEGP CIS.

Customizable shared Electronic Health Care Records require new mechanisms to dynamically generate user defined objects. An object model based on a semantic network of concepts has been implemented (pragmatic database model). This model offers an easier way to represent "archetypes" of user objects including the concepts, their relationships and the specific organization and representation of the associated knowledge that are necessary to model the context of production of record elements. The aim of this paper is the presentation of this framework and its implementation in an online electronic health record system using Java Web Services technologies. A web-based registry on tobacco was implemented according to this framework and is today daily used in 150 tobacco addiction centers.

As medical information can be encoded within different terminological systems, terms comparison is an important issue to allow communication between applications. In description logics, terms are compared by the means of semantic definitions and subsumption relations. Similarity is also a convenient method for term comparison but is not supported by terminology servers which implement subsumption relations. We present new terminology services built on a semantic distance that could help for semantic mediation between medical applications ranging from semi-automatic encoders to data mining tools. These services are 1) comparison between terms 2) k-nearest-neighbors 3) support for concept coding 4) automatic generation of similarity tables 5) distance based queries 6) support for clustering.

Unlabelled: Face to the development of hospital information system in the "Hôpital Européen George Pompidou" (HEGP), computerized patients records made medical data easier to analyse than before. We use data-mining technology to analyse intra-hospital patients' paths with one year of PMSI data (a French medical information system similar to Diagnosis Related Group)., Methods: 1. "sequential patterns mining" was used to analyse the most frequent patients' paths, 2. an integrated framework of "association rules mining" and "classification rule mining" was used to build prediction rules of patients' paths., Result: We construct a rule based prediction model, which gives the tendency of the patient's paths between the different medical units.