How to Improve Cancer Patients ENrollment in Clinical Trials From rEal-Life Databases Using the Observational Medical Outcomes Partnership Oncology Extension: Results of the PENELOPE Initiative in Urologic Cancers.

PURPOSE: To compare the computability of Observational Medical Outcomes Partnership (OMOP)-based queries related to prescreening of patients using two versions of the OMOP common data model (CDM; v5.3 and v5.4) and to assess the performance of the Greater Paris University Hospital (APHP) prescreening tool. MATERIALS AND METHODS: We identified the prescreening information items being relevant for prescreening of patients with cancer. We randomly selected 15 academic and industry-sponsored urology phase I-IV clinical trials (CTs) launched at APHP between 2016 and 2021. The computability of the related prescreening criteria (PC) was defined by their translation rate in OMOP-compliant queries and by their execution rate on the APHP clinical data warehouse (CDW) containing data of 205,977 patients with cancer. The overall performance of the prescreening tool was assessed by the rate of true- and false-positive cases of three randomly selected CTs. RESULTS: We defined a list of 15 minimal information items being relevant for patients' prescreening. We identified 83 PC of the 534 eligibility criteria from the 15 CTs. We translated 33 and 62 PC in queries on the basis of OMOP CDM v5.3 and v5.4, respectively (translation rates of 40% and 75%, respectively). Of the 33 PC translated in the v5.3 of the OMOP CDM, 19 could be executed on the APHP CDW (execution rate of 58%). Of 83 PC, the computability rate on the APHP CDW reached 23%. On the basis of three CTs, we identified 17, 32, and 63 patients as being potentially eligible for inclusion in those CTs, resulting in positive predictive values of 53%, 41%, and 21%, respectively. CONCLUSION: We showed that PC could be formalized according to the OMOP CDM and that the oncology extension increased their translation rate through better representation of cancer natural history.

Cross border semantic interoperability for learning health systems: The EHR4CR semantic resources and services.

With the development of platforms enabling the integration and use of phenome, genome, and exposome data in the context of international research, data management challenges are increasing, and scalable solutions for cross border and cross domain semantic interoperability need to be developed. Reusing routinely collected clinical data, especially, requires computable portable phenotype algorithms running across different electronic health record (EHR) products and healthcare systems. We propose a framework for describing and comparing mediation platforms enabling cross border phenotype identification within federated EHRs. This framework was used to describe the experience gained during the EHR4CR project and the evaluation of the platform developed for accessing semantically equivalent data elements across 11 European participating EHR systems from 5 countries. Developers of semantic interoperability platforms are beginning to address a core set of requirements in order to reach the goal of developing cross border semantic integration of data.

Cross border semantic interoperability for clinical research: the EHR4CR semantic resources and services.

With the development of platforms enabling the use of routinely collected clinical data in the context of international clinical research, scalable solutions for cross border semantic interoperability need to be developed. Within the context of the IMI EHR4CR project, we first defined the requirements and evaluation criteria of the EHR4CR semantic interoperability platform and then developed the semantic resources and supportive services and tooling to assist hospital sites in standardizing their data for allowing the execution of the project use cases. The experience gained from the evaluation of the EHR4CR platform accessing to semantically equivalent data elements across 11 European participating EHR systems from 5 countries demonstrated how far the mediation model and mapping efforts met the expected requirements of the project. Developers of semantic interoperability platforms are beginning to address a core set of requirements in order to reach the goal of developing cross border semantic integration of data.

Standard-based EHR-enabled applications for clinical research and patient safety: CDISC - IHE QRPH - EHR4CR & SALUS collaboration.

Integration profiles collaboratively developed by CDISC and IHE for integrating data from Electronic Health Records (EHRs) with clinical research and pharmacovigilance are limited to resolving lexical/syntactic data integration issues and do not address semantic barriers. This paper describes the collaboration between two European projects - EHR4CR and SALUS - in implementing ISO/IEC 11179-based metadata registries (MDRs) and semantically integrated cross-platform data access. A common "semantic MDR" provides a framework for bidirectional/cross-MDR mapping and federated queries are enabled using the newly-defined IHE Data Exchange (DEX) profile. In the pilot implementation, mappings for 178 EHR4CR and 199 SALUS metadata elements were persisted in the semantic MDR. The DEX profile was then used to access semantically equivalent data elements in SALUS or EHR4CR participating EHR systems. ISO/IEC 11179-based MDRs and DEX integration profile address the goal of developing pan-EU computable semantic integration of data from clinical care, clinical research, and patient safety platforms.

The Electronic Healthcare Record for Clinical Research (EHR4CR) information model and terminology.

A major barrier to repurposing routinely collected data for clinical research is the heterogeneity of healthcare information systems. Electronic Healthcare Record for Clinical Research (EHR4CR) is a European platform designed to improve the efficiency of conducting clinical trials. In this paper, we propose an initial architecture of the EHR4CR Semantic Interoperability Framework. We used a model-driven engineering approach to build a reference HL7-based multidimensional model bound to a set of reference clinical terminologies acting as a global as view model. We then conducted an evaluation of its expressiveness for patient eligibility. The EHR4CR information model consists in one fact table dedicated to clinical statement and 4 dimensions. The EHR4CR terminology integrates reference terminologies used in patient care (e.g LOINC, ICD-10, SNOMED CT, etc). We used the Object Constraint Language (OCL) to represent patterns of eligibility criteria as constraints on the EHR4CR model to be further transformed in SQL statements executed on different clinical data warehouses.

The Information Quality Triangle: a methodology to assess clinical information quality.

Building qualitative clinical decision support or monitoring based on information stored in clinical information (or EHR) systems cannot be done without assessing and controlling information quality. Numerous works have introduced methods and measures to qualify and enhance data, information models and terminologies quality. This paper introduces an approach based on an Information Quality Triangle that aims at providing a generic framework to help in characterizing quality measures and methods in the context of the integration of EHR data in a clinical datawarehouse. We have successfully experimented the proposed approach at the HEGP hospital in France, as part of the DebugIT EU FP7 project.

Ensuring HL7-based information model requirements within an ontology framework.

This paper describes the building of an HL7-based Information Model Ontology (IMO) that can be exploited by a domain ontology in order to distribute querying over different clinical data repositories. We employed the Open Medical Development Framework (OMDF) based on a model driven development methodology. OMDF provides model transformation features to build an HL7-based information model that covers the conceptual scope of a target project. The resulting IMO is used to mediate between ontologically queries and information retrieval from semantically less defined Hospital Information Systems (HIS). In the context of the DebugIT project - which scope corresponds to the control of infectious diseases and antimicrobial resistances - Information Model Ontology is integrated to the DebugIT domain ontology in order to express queries.

Functional requirements of terminology services for coupling interface terminologies to reference terminologies.

Desiderata for interface terminologies (IT), designed to support interactions between humans and structured medical information, differ from desiderata for reference terminologies (RT). Terminology experts have recommended that IT be mapped to RT. The interface terminology of the Georges Pompidou European Hospital (GPEH-IT) contains more than 5,000 concepts, sometimes linked to ICD-10 but not yet to the SNOMED 3.5 VF, now available in France. Our objective was to use a formal characterization framework to compare GPEH-IT to SNOMED 3.5 VF and to define the functionalities of terminology services for managing both IT and RT and the mapping between them. We discuss the role of IT and RT in representing the meaning of clinical data.

Integrating anatomical pathology to the healthcare enterprise.

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.

Integration of multiple ontologies in breast cancer pathology.

The diagnostic variability in pathology, widely reported in the literature, is partly due to the use of different classification systems by pathologists. The descriptions of morphological characteristics on the same image within different classification systems can be considered as different points of view of pathologists. Our aim is to represent the points of view of the experts in pathology during image interpretation and to propose a method ological and technical solution in order to implement interoperability between these points of view. According to the hybrid ontology approach, we developed a system in three stages consisting in 1) the representation of the various points of view in local ontologies 2) the realization of a shared vocabulary and the development of a mapping tool used to allow the matching of local ontologies and shared vocabulary 3) the development of a transcoding algorithm for the translation of a case description from one point of view to another. A first evaluation of the transcoding algorithm was conducted for 33 cases of breast pathology. Our results show that the pathologists generally produce descriptions of the cases which do not follow rigorously the interpretation rules corresponding to the point of view they assert to adopt. While most of the concepts of local ontologies can be transcoded from a local ontology to another one (varying from 62.5 % to 100% according to the local ontology), the transcoding of a description which is valid according to a certain point of view, often results in a description which is not rigorously in accordance with the new point of view. These results underline the differences of interpretation rules existing in the different points of view.