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Kalankesh LR, Monaghesh E. Utilization of EHRs for clinical trials: a systematic review. BMC Med Res Methodol 2024; 24:70. [PMID: 38494497 PMCID: PMC10946197 DOI: 10.1186/s12874-024-02177-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Accepted: 02/08/2024] [Indexed: 03/19/2024] Open
Abstract
BACKGROUND AND OBJECTIVE Clinical trials are of high importance for medical progress. This study conducted a systematic review to identify the applications of EHRs in supporting and enhancing clinical trials. MATERIALS AND METHODS A systematic search of PubMed was conducted on 12/3/2023 to identify relevant studies on the use of EHRs in clinical trials. Studies were included if they (1) were full-text journal articles, (2) were written in English, (3) examined applications of EHR data to support clinical trial processes (e.g. recruitment, screening, data collection). A standardized form was used by two reviewers to extract data on: study design, EHR-enabled process(es), related outcomes, and limitations. RESULTS Following full-text review, 19 studies met the predefined eligibility criteria and were included. Overall, included studies consistently demonstrated that EHR data integration improves clinical trial feasibility and efficiency in recruitment, screening, data collection, and trial design. CONCLUSIONS According to the results of the present study, the use of Electronic Health Records in conducting clinical trials is very helpful. Therefore, it is better for researchers to use EHR in their studies for easy access to more accurate and comprehensive data. EHRs collects all individual data, including demographic, clinical, diagnostic, and therapeutic data. Moreover, all data is available seamlessly in EHR. In future studies, it is better to consider the cost-effectiveness of using EHR in clinical trials.
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Affiliation(s)
- Leila R Kalankesh
- Tabriz Health Services Management Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
- Department of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Elham Monaghesh
- Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran.
- Department of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran.
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2
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Boeker M, Zöller D, Blasini R, Macho P, Helfer S, Behrens M, Prokosch HU, Gulden C. Effectiveness of IT-supported patient recruitment: study protocol for an interrupted time series study at ten German university hospitals. Trials 2024; 25:125. [PMID: 38365848 PMCID: PMC10870691 DOI: 10.1186/s13063-024-07918-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 01/09/2024] [Indexed: 02/18/2024] Open
Abstract
BACKGROUND As part of the German Medical Informatics Initiative, the MIRACUM project establishes data integration centers across ten German university hospitals. The embedded MIRACUM Use Case "Alerting in Care - IT Support for Patient Recruitment", aims to support the recruitment into clinical trials by automatically querying the repositories for patients satisfying eligibility criteria and presenting them as screening candidates. The objective of this study is to investigate whether the developed recruitment tool has a positive effect on study recruitment within a multi-center environment by increasing the number of participants. Its secondary objective is the measurement of organizational burden and user satisfaction of the provided IT solution. METHODS The study uses an Interrupted Time Series Design with a duration of 15 months. All trials start in the control phase of randomized length with regular recruitment and change to the intervention phase with additional IT support. The intervention consists of the application of a recruitment-support system which uses patient data collected in general care for screening according to specific criteria. The inclusion and exclusion criteria of all selected trials are translated into a machine-readable format using the OHDSI ATLAS tool. All patient data from the data integration centers is regularly checked against these criteria. The primary outcome is the number of participants recruited per trial and week standardized by the targeted number of participants per week and the expected recruitment duration of the specific trial. Secondary outcomes are usability, usefulness, and efficacy of the recruitment support. Sample size calculation based on simple parallel group assumption can demonstrate an effect size of d=0.57 on a significance level of 5% and a power of 80% with a total number of 100 trials (10 per site). Data describing the included trials and the recruitment process is collected at each site. The primary analysis will be conducted using linear mixed models with the actual recruitment number per week and trial standardized by the expected recruitment number per week and trial as the dependent variable. DISCUSSION The application of an IT-supported recruitment solution developed in the MIRACUM consortium leads to an increased number of recruited participants in studies at German university hospitals. It supports employees engaged in the recruitment of trial participants and is easy to integrate in their daily work.
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Affiliation(s)
- Martin Boeker
- Institute of Medical Biometry and Statistics, Medical Faculty and Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
- Chair of Medical Informatics, Institute of Artificial Intelligence and Informatics in Medicine, Klinikum rechts der Isar, School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Daniela Zöller
- Institute of Medical Biometry and Statistics, Medical Faculty and Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
| | - Romina Blasini
- Institute of Medical Informatics, Justus-Liebig-University Gießen, Gießen, Germany
| | - Philipp Macho
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), Mainz University Medical Center, Mainz, Germany
| | - Sven Helfer
- Department of Pediatrics, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Max Behrens
- Institute of Medical Biometry and Statistics, Medical Faculty and Medical Center, University of Freiburg, Freiburg im Breisgau, Germany
| | - Hans-Ulrich Prokosch
- Chair of Medical Informatics, Department of Medical Informatics, Biometrics and Epidemiology, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Christian Gulden
- Chair of Medical Informatics, Department of Medical Informatics, Biometrics and Epidemiology, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany.
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Eysenbach G, Ulrich H, Bergh B, Schreiweis B. Functional Requirements for Medical Data Integration into Knowledge Management Environments: Requirements Elicitation Approach Based on Systematic Literature Analysis. J Med Internet Res 2023; 25:e41344. [PMID: 36757764 PMCID: PMC9951079 DOI: 10.2196/41344] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 10/24/2022] [Accepted: 11/17/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND In patient care, data are historically generated and stored in heterogeneous databases that are domain specific and often noninteroperable or isolated. As the amount of health data increases, the number of isolated data silos is also expected to grow, limiting the accessibility of the collected data. Medical informatics is developing ways to move from siloed data to a more harmonized arrangement in information architectures. This paradigm shift will allow future research to integrate medical data at various levels and from various sources. Currently, comprehensive requirements engineering is working on data integration projects in both patient care- and research-oriented contexts, and it is significantly contributing to the success of such projects. In addition to various stakeholder-based methods, document-based requirement elicitation is a valid method for improving the scope and quality of requirements. OBJECTIVE Our main objective was to provide a general catalog of functional requirements for integrating medical data into knowledge management environments. We aimed to identify where integration projects intersect to derive consistent and representative functional requirements from the literature. On the basis of these findings, we identified which functional requirements for data integration exist in the literature and thus provide a general catalog of requirements. METHODS This work began by conducting a literature-based requirement elicitation based on a broad requirement engineering approach. Thus, in the first step, we performed a web-based systematic literature review to identify published articles that dealt with the requirements for medical data integration. We identified and analyzed the available literature by applying the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. In the second step, we screened the results for functional requirements using the requirements engineering method of document analysis and derived the requirements into a uniform requirement syntax. Finally, we classified the elicited requirements into a category scheme that represents the data life cycle. RESULTS Our 2-step requirements elicitation approach yielded 821 articles, of which 61 (7.4%) were included in the requirement elicitation process. There, we identified 220 requirements, which were covered by 314 references. We assigned the requirements to different data life cycle categories as follows: 25% (55/220) to data acquisition, 35.9% (79/220) to data processing, 12.7% (28/220) to data storage, 9.1% (20/220) to data analysis, 6.4% (14/220) to metadata management, 2.3% (5/220) to data lineage, 3.2% (7/220) to data traceability, and 5.5% (12/220) to data security. CONCLUSIONS The aim of this study was to present a cross-section of functional data integration-related requirements defined in the literature by other researchers. The aim was achieved with 220 distinct requirements from 61 publications. We concluded that scientific publications are, in principle, a reliable source of information for functional requirements with respect to medical data integration. Finally, we provide a broad catalog to support other scientists in the requirement elicitation phase.
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Affiliation(s)
- G Eysenbach
- Institute for Medical Informatics and StatisticsKiel University and University Hospital Schleswig-HolsteinKielGermany
| | - Hannes Ulrich
- Institute for Medical Informatics and Statistics, Kiel University and University Hospital Schleswig-Holstein, Kiel, Germany
| | - Björn Bergh
- Institute for Medical Informatics and Statistics, Kiel University and University Hospital Schleswig-Holstein, Kiel, Germany
| | - Björn Schreiweis
- Institute for Medical Informatics and Statistics, Kiel University and University Hospital Schleswig-Holstein, Kiel, Germany
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Gruendner J, Deppenwiese N, Folz M, Köhler T, Kroll B, Prokosch HU, Rosenau L, Rühle M, Scheidl MA, Schüttler C, Sedlmayr B, Twrdik A, Kiel A, Majeed RW. Architecture for a feasibility query portal for distributed COVID-19 Fast Healthcare Interoperability Resources (FHIR) patient data repositories: Design and Implementation Study (Preprint). JMIR Med Inform 2022; 10:e36709. [PMID: 35486893 PMCID: PMC9135115 DOI: 10.2196/36709] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 03/16/2022] [Accepted: 04/11/2022] [Indexed: 12/04/2022] Open
Abstract
Background An essential step in any medical research project after identifying the research question is to determine if there are sufficient patients available for a study and where to find them. Pursuing digital feasibility queries on available patient data registries has proven to be an excellent way of reusing existing real-world data sources. To support multicentric research, these feasibility queries should be designed and implemented to run across multiple sites and securely access local data. Working across hospitals usually involves working with different data formats and vocabularies. Recently, the Fast Healthcare Interoperability Resources (FHIR) standard was developed by Health Level Seven to address this concern and describe patient data in a standardized format. The Medical Informatics Initiative in Germany has committed to this standard and created data integration centers, which convert existing data into the FHIR format at each hospital. This partially solves the interoperability problem; however, a distributed feasibility query platform for the FHIR standard is still missing. Objective This study described the design and implementation of the components involved in creating a cross-hospital feasibility query platform for researchers based on FHIR resources. This effort was part of a large COVID-19 data exchange platform and was designed to be scalable for a broad range of patient data. Methods We analyzed and designed the abstract components necessary for a distributed feasibility query. This included a user interface for creating the query, backend with an ontology and terminology service, middleware for query distribution, and FHIR feasibility query execution service. Results We implemented the components described in the Methods section. The resulting solution was distributed to 33 German university hospitals. The functionality of the comprehensive network infrastructure was demonstrated using a test data set based on the German Corona Consensus Data Set. A performance test using specifically created synthetic data revealed the applicability of our solution to data sets containing millions of FHIR resources. The solution can be easily deployed across hospitals and supports feasibility queries, combining multiple inclusion and exclusion criteria using standard Health Level Seven query languages such as Clinical Quality Language and FHIR Search. Developing a platform based on multiple microservices allowed us to create an extendable platform and support multiple Health Level Seven query languages and middleware components to allow integration with future directions of the Medical Informatics Initiative. Conclusions We designed and implemented a feasibility platform for distributed feasibility queries, which works directly on FHIR-formatted data and distributed it across 33 university hospitals in Germany. We showed that developing a feasibility platform directly on the FHIR standard is feasible.
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Affiliation(s)
- Julian Gruendner
- Chair of Medical Informatics, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Noemi Deppenwiese
- Center of Medical Information and Communication Technology, University Hospital Erlangen, Erlangen, Germany
| | - Michael Folz
- Institute of Medical Informatics, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Thomas Köhler
- Federated Information Systems, German Cancer Research Center, Heidelberg, Germany
| | - Björn Kroll
- IT Center for Clinical Research, University of Lübeck, Lübeck, Germany
| | - Hans-Ulrich Prokosch
- Chair of Medical Informatics, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Lorenz Rosenau
- IT Center for Clinical Research, University of Lübeck, Lübeck, Germany
| | - Mathias Rühle
- Leipzig Research Centre for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Marc-Anton Scheidl
- Chair of Medical Informatics, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Christina Schüttler
- Chair of Medical Informatics, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Brita Sedlmayr
- Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Alexander Twrdik
- Leipzig Research Centre for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Alexander Kiel
- Federated Information Systems, German Cancer Research Center, Heidelberg, Germany
- Leipzig Research Centre for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Raphael W Majeed
- Institute for Medical Informatics, University Clinic Rheinisch-Westfälische Technische Hochschule Aachen, Aachen, Germany
- Universities of Giessen and Marburg Lung Center, German Centre For Lung Research, Justus-Liebig University Giessen, Giessen, Germany
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Kaspar M, Fette G, Hanke M, Ertl M, Puppe F, Störk S. Automated provision of clinical routine data for a complex clinical follow-up study: A data warehouse solution. Health Informatics J 2022; 28:14604582211058081. [PMID: 34986681 DOI: 10.1177/14604582211058081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
A deep integration of routine care and research remains challenging in many respects. We aimed to show the feasibility of an automated transformation and transfer process feeding deeply structured data with a high level of granularity collected for a clinical prospective cohort study from our hospital information system to the study's electronic data capture system, while accounting for study-specific data and visits. We developed a system integrating all necessary software and organizational processes then used in the study. The process and key system components are described together with descriptive statistics to show its feasibility in general and to identify individual challenges in particular. Data of 2051 patients enrolled between 2014 and 2020 was transferred. We were able to automate the transfer of approximately 11 million individual data values, representing 95% of all entered study data. These were recorded in n = 314 variables (28% of all variables), with some variables being used multiple times for follow-up visits. Our validation approach allowed for constant good data quality over the course of the study. In conclusion, the automated transfer of multi-dimensional routine medical data from HIS to study databases using specific study data and visit structures is complex, yet viable.
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Affiliation(s)
- Mathias Kaspar
- Comprehensive Heart Failure Center and Department of Internal Medicine I, 27207University and University Hospital Würzburg, Würzburg, Germany
- Department of Health Services Research, 11233Carl von Ossietzky University of Oldenburg, Oldenburg, Germany
| | - Georg Fette
- Service Center Medical Informatics, 27207Würzburg University Hospital, Würzburg, Germany
| | - Monika Hanke
- Comprehensive Heart Failure Center and Department of Internal Medicine I, 27207University and University Hospital Würzburg, Würzburg, Germany
| | - Maximilian Ertl
- Service Center Medical Informatics, 27207Würzburg University Hospital, Würzburg, Germany
| | - Frank Puppe
- Chair of Computer Science VI, 9190University of Würzburg, Würzburg, Germany
| | - Stefan Störk
- Comprehensive Heart Failure Center and Department of Internal Medicine I, 27207University and University Hospital Würzburg, Würzburg, Germany
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Scheibner J, Sleigh J, Ienca M, Vayena E. Benefits, challenges, and contributors to success for national eHealth systems implementation: a scoping review. J Am Med Inform Assoc 2021; 28:2039-2049. [PMID: 34151990 DOI: 10.1093/jamia/ocab096] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 04/27/2021] [Accepted: 05/21/2021] [Indexed: 11/14/2022] Open
Abstract
OBJECTIVE Our scoping review aims to assess what legal, ethical, and socio-technical factors contribute to or inhibit the success of national eHealth system implementations. In addition, our review seeks to describe the characteristics and benefits of eHealth systems. MATERIALS AND METHODS We conducted a scoping review of literature published in English between January 2000 and 2020 using a keyword search on 5 databases: PubMed, Scopus, Web of Science, IEEEXplore, and ProQuest. After removal of duplicates, abstract screening, and full-text filtering, 86 articles were included from 8276 search results. RESULTS We identified 17 stakeholder groups, 6 eHealth Systems areas, and 15 types of legal regimes and standards. In-depth textual analysis revealed challenges mainly in implementation, followed by ethico-legal and data-related aspects. Key factors influencing success include promoting trust of the system, ensuring wider acceptance among users, reconciling the system with legal requirements, and ensuring an adaptable technical platform. DISCUSSION Results revealed support for decentralized implementations because they carry less implementation and engagement challenges than centralized ones. Simultaneously, due to decentralized systems' interoperability issues, federated implementations (with a set of national standards) might be preferable. CONCLUSION This study identifies the primary socio-technical, legal, and ethical factors that challenge and contribute to the success of eHealth system implementations. This study also describes the complexities and characteristics of existing eHealth implementation programs, and suggests guidance for resolving the identified challenges.
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Affiliation(s)
- James Scheibner
- Department of Health Sciences and Technology, Health Ethics and Policy Laboratory, ETH Zürich, Zürich, Switzerland.,College of Business, Government and Law, Flinders University, Adelaide, Australia
| | - Joanna Sleigh
- Department of Health Sciences and Technology, Health Ethics and Policy Laboratory, ETH Zürich, Zürich, Switzerland
| | - Marcello Ienca
- Department of Health Sciences and Technology, Health Ethics and Policy Laboratory, ETH Zürich, Zürich, Switzerland
| | - Effy Vayena
- Department of Health Sciences and Technology, Health Ethics and Policy Laboratory, ETH Zürich, Zürich, Switzerland
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Laaksonen N, Varjonen JM, Blomster M, Palomäki A, Vasankari T, Airaksinen J, Huupponen R, Scheinin M, Juuso Blomster. Assessing an Electronic Health Record research platform for identification of clinical trial participants. Contemp Clin Trials Commun 2021; 21:100692. [PMID: 33409423 PMCID: PMC7773855 DOI: 10.1016/j.conctc.2020.100692] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 11/05/2020] [Accepted: 12/14/2020] [Indexed: 11/29/2022] Open
Abstract
Electronic health records (EHR) are a potential resource for identification of clinical trial participants. We evaluated how accurately a commercially available EHR Research Platform, InSite, is able to identify potential trial participants from the EHR system of a large tertiary care hospital. Patient counts were compared with results obtained in a conventional manual search performed for a reference study that investigated the associations of atrial fibrillation (AF) and cerebrovascular incidents. The Clinical Data Warehouse (CDW) of Turku University Hospital was used to verify the capabilities of the EHR Research Platform. The EHR query resulted in a larger patient count than the manual query (EHR Research Platform 5859 patients, manual selection 2166 patients). This was due to the different search logic and some exclusion criteria that were not addressable in structured digital format. The EHR Research Platform (5859 patients) and the CDW search (5840 patients) employed the same search logic. The temporal relationship between the two diagnoses could be identified when they were available in structured format and the time difference was longer than a single hospital visit. Searching for patients with the EHR Research Platform can help to identify potential trial participants from a hospital's EHR system by limiting the number of records to be manually reviewed. EHR query tools can best be utilized in trials where the selection criteria are expressed in structured digital format.
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Affiliation(s)
- Niina Laaksonen
- Institute of Biomedicine, University of Turku, Kiinamyllynkatu 10, FI-20520, Turku, Finland
| | - Juha-Matti Varjonen
- Auria Clinical Informatics, Hospital District of Southwest Finland, PO Box 52, FI-20521, Turku, Finland
| | - Minna Blomster
- Auria Clinical Informatics, Hospital District of Southwest Finland, PO Box 52, FI-20521, Turku, Finland
| | - Antti Palomäki
- Heart Centre, Turku University Hospital, PO Box 52, FI-2052, Turku, Finland
| | - Tuija Vasankari
- Heart Centre, Turku University Hospital, PO Box 52, FI-2052, Turku, Finland
| | - Juhani Airaksinen
- Heart Centre, Turku University Hospital, PO Box 52, FI-2052, Turku, Finland
| | - Risto Huupponen
- Institute of Biomedicine, University of Turku, Kiinamyllynkatu 10, FI-20520, Turku, Finland
| | - Mika Scheinin
- Institute of Biomedicine, University of Turku, Kiinamyllynkatu 10, FI-20520, Turku, Finland
| | - Juuso Blomster
- Institute of Biomedicine, University of Turku, Kiinamyllynkatu 10, FI-20520, Turku, Finland.,Heart Centre, Turku University Hospital, PO Box 52, FI-2052, Turku, Finland
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Johnson EA, Carrington JM. Clinical Research Integration Within the Electronic Health Record: A Literature Review. Comput Inform Nurs 2020; 39:129-135. [PMID: 33657055 DOI: 10.1097/cin.0000000000000659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Clinical trials have become commonplace as a treatment option. As clinical trial participants are integrated into all healthcare delivery settings, organizations are tasked with sustaining specific care regimens with appropriate documentation and maintenance of participant protections within electronic health records. Our aim was to identify the common elements necessary for electronic health record integration of clinical research for optimal trial conduct and participant management. Review of literature was conducted utilizing PubMed and CINAHL to identify relevant publications that described use of the electronic health record to directly support trial conduct, with a total of 15 publications ultimately meeting inclusion criteria. Three thematic groupings emerged that categorized common aspects of clinical research integration: functional, structural, and procedural components. These components include technological requirements (platform/system), regulatory and legal compliance, and stakeholder involvement with clinical trial procedures (recruitment of participants). Without a centralized means of providing clinicians with current treatment and adverse event management information, participant injury or likelihood of withdrawal will increase. Further research is required to develop an optimal model of research-related integration within commercial electronic health records.
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Affiliation(s)
- Elizabeth A Johnson
- Author Affiliations: The University of Arizona (Ms Johnson), Tucson; and University of Florida (Dr Carrington), Gainesville
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Becker L, Ganslandt T, Prokosch HU, Newe A. Applied Practice and Possible Leverage Points for Information Technology Support for Patient Screening in Clinical Trials: Qualitative Study. JMIR Med Inform 2020; 8:e15749. [PMID: 32442156 PMCID: PMC7327588 DOI: 10.2196/15749] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 03/08/2020] [Accepted: 03/28/2020] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Clinical trials are one of the most challenging and meaningful designs in medical research. One essential step before starting a clinical trial is screening, that is, to identify patients who fulfill the inclusion criteria and do not fulfill the exclusion criteria. The screening step for clinical trials might be supported by modern information technology (IT). OBJECTIVE This explorative study aimed (1) to obtain insights into which tools for feasibility estimations and patient screening are actually used in clinical routine and (2) to determine which method and type of IT support could benefit clinical staff. METHODS Semistandardized interviews were conducted in 5 wards (cardiology, gynecology, gastroenterology, nephrology, and palliative care) in a German university hospital. Of the 5 interviewees, 4 were directly involved in patient screening. Three of them were clinicians, 1 was a study nurse, and 1 was a research assistant. RESULTS The existing state of study feasibility estimation and the screening procedure were dominated by human communication and estimations from memory, although there were many possibilities for IT support. Success mostly depended on the experience and personal motivation of the clinical staff. Electronic support has been used but with little importance so far. Searches in ward-specific patient registers (databases) and searches in clinical information systems were reported. Furthermore, free-text searches in medical reports were mentioned. For potential future applications, a preference for either proactive or passive systems was not expressed. Most of the interviewees saw the potential for the improvement of the actual systems, but they were also largely satisfied with the outcomes of the current approach. Most of the interviewees were interested in learning more about the various ways in which IT could support and relieve them in their clinical routine. CONCLUSIONS Overall, IT support currently plays a minor role in the screening step for clinical trials. The lack of IT usage and the estimations made from memory reported by all the participants might constrain cognitive resources, which might distract from clinical routine. We conclude that electronic support for the screening step for clinical trials is still a challenge and that education of the staff about the possibilities for electronic support in clinical trials is necessary.
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Affiliation(s)
- Linda Becker
- Chair of Health Psychology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Thomas Ganslandt
- Department of Biomedical Informatics, Heinrich-Lanz-Zentrum, Mannheim, Germany.,University Medicine, Ruprecht-Karls University Heidelberg, Heidelberg, Germany
| | - Hans-Ulrich Prokosch
- Chair of Medical Informatics, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Axel Newe
- Chair of Medical Informatics, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
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10
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Davies G, Jordan S, Brooks CJ, Thayer D, Storey M, Morgan G, Allen S, Garaiova I, Plummer S, Gravenor M. Long term extension of a randomised controlled trial of probiotics using electronic health records. Sci Rep 2018; 8:7668. [PMID: 29769554 PMCID: PMC5955897 DOI: 10.1038/s41598-018-25954-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2017] [Accepted: 04/09/2018] [Indexed: 12/12/2022] Open
Abstract
Most randomised controlled trials (RCTs) are relatively short term and, due to costs and available resources, have limited opportunity to be re-visited or extended. There is no guarantee that effects of treatments remain unchanged beyond the study. Here, we illustrate the feasibility, benefits and cost-effectiveness of enriching standard trial design with electronic follow up. We completed a 5-year electronic follow up of a RCT investigating the impact of probiotics on asthma and eczema in children born 2005–2007, with traditional fieldwork follow up to two years. Participants and trial outcomes were identified and analysed after five years using secure, routine, anonymised, person-based electronic health service databanks. At two years, we identified 93% of participants and compared fieldwork with electronic health records, highlighting areas of agreement and disagreement. Retention of children from lower socio-economic groups was improved, reducing volunteer bias. At 5 years we identified a reduced 82% of participants. These data allowed the trial’s first robust analysis of asthma endpoints. We found no indication that probiotic supplementation to pregnant mothers and infants protected against asthma or eczema at 5 years. Continued longer-term follow up is technically straightforward.
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Affiliation(s)
- Gareth Davies
- Swansea University Medical School, Singleton Park, Swansea, UK
| | - Sue Jordan
- Department of Nursing, The College of Human and Health Sciences, Swansea University, Singleton Park, Swansea, UK.
| | | | - Daniel Thayer
- Swansea University Medical School, Singleton Park, Swansea, UK
| | - Melanie Storey
- Department of Nursing, The College of Human and Health Sciences, Swansea University, Singleton Park, Swansea, UK
| | - Gareth Morgan
- The Children's Trust, Tadworth, Surrey, UK.,The Harley Street Clinic Children's Hospital, London, UK
| | - Stephen Allen
- Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, UK
| | - Iveta Garaiova
- Research Department, Cultech Limited, Baglan Industrial Park, Port Talbot, UK
| | - Sue Plummer
- Research Department, Cultech Limited, Baglan Industrial Park, Port Talbot, UK
| | - Mike Gravenor
- Swansea University Medical School, Singleton Park, Swansea, UK
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Lablans M, Kadioglu D, Muscholl M, Ückert F. Exploiting Distributed, Heterogeneous and Sensitive Data Stocks while Maintaining the Owner’s Data Sovereignty. Methods Inf Med 2018. [PMID: 26196653 DOI: 10.3414/me14-01-0137] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
SummaryBackground: To achieve statistical significance in medical research, biological or data samples from several bio- or databanks often need to be complemented by those of other institutions. For that purpose, IT-based search services have been established to locate datasets matching a given set of criteria in databases distributed across several institutions. However, previous approaches require data owners to disclose information about their samples, raising a barrier for their participation in the network.Objective: To devise a method to search distributed databases for datasets matching a given set of criteria while fully maintaining their owner’s data sovereignty.Methods: As a modification to traditional federated search services, we propose the decentral search, which allows the data owner a high degree of control. Relevant data are loaded into local bridgeheads, each under their owner’s sovereignty. Researchers can formulate criteria sets along with a project proposal using a central search broker, which then notifies the bridgeheads. The criteria are, however, treated as an inquiry rather than a query: Instead of responding with results, bridgeheads notify their owner and wait for his/her decision regarding whether and what to answer based on the criteria set, the matching datasets and the specific project proposal. Without the owner’s explicit consent, no data leaves his/ her institution.Results: The decentral search has been deployed in one of the six German Centers for Health Research, comprised of eleven university hospitals. In the process, compliance with German data protection regulations has been confirmed. The decentral search also marks the centerpiece of an open source registry software toolbox aiming to build a national registry of rare diseases in Germany.Conclusions: While the sacrifice of real-time answers impairs some use-cases, it leads to several beneficial side effects: improved data protection due to data parsimony, tolerance for incomplete data schema mappings and flexibility with regard to patient consent. Most importantly, as no datasets ever leave their institution, owners can reject projects without facing potential peer pressure. By its lower barrier for participation, a decentral search service is likely to attract a larger number of partners and to bring a researcher into contact with the right potential partners.
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Affiliation(s)
- M Lablans
- Martin Lablans, University Medical Center Mainz, Obere Zahlbacher Straße 69, 55131 Mainz, Germany, E-mail:
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Abstract
OBJECTIVES To summarize significant developments in Clinical Research Informatics (CRI) over the past two years and discuss future directions. METHODS Survey of advances, open problems and opportunities in this field based on exploration of current literature. RESULTS Recent advances are structured according to three use cases of clinical research: Protocol feasibility, patient identification/ recruitment and clinical trial execution. DISCUSSION CRI is an evolving, dynamic field of research. Global collaboration, open metadata, content standards with semantics and computable eligibility criteria are key success factors for future developments in CRI.
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Affiliation(s)
- M Dugas
- Prof. Dr. Martin Dugas, Institute of Medical Informatics, University of Münster, Albert-Schweitzer-Campus 1
- A11, D-48149 Münster, Germany, Tel: +49 251 83 55262, E-mail:
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13
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Williams R, Kontopantelis E, Buchan I, Peek N. Clinical code set engineering for reusing EHR data for research: A review. J Biomed Inform 2017; 70:1-13. [PMID: 28442434 DOI: 10.1016/j.jbi.2017.04.010] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Revised: 03/21/2017] [Accepted: 04/13/2017] [Indexed: 01/26/2023]
Abstract
INTRODUCTION The construction of reliable, reusable clinical code sets is essential when re-using Electronic Health Record (EHR) data for research. Yet code set definitions are rarely transparent and their sharing is almost non-existent. There is a lack of methodological standards for the management (construction, sharing, revision and reuse) of clinical code sets which needs to be addressed to ensure the reliability and credibility of studies which use code sets. OBJECTIVE To review methodological literature on the management of sets of clinical codes used in research on clinical databases and to provide a list of best practice recommendations for future studies and software tools. METHODS We performed an exhaustive search for methodological papers about clinical code set engineering for re-using EHR data in research. This was supplemented with papers identified by snowball sampling. In addition, a list of e-phenotyping systems was constructed by merging references from several systematic reviews on this topic, and the processes adopted by those systems for code set management was reviewed. RESULTS Thirty methodological papers were reviewed. Common approaches included: creating an initial list of synonyms for the condition of interest (n=20); making use of the hierarchical nature of coding terminologies during searching (n=23); reviewing sets with clinician input (n=20); and reusing and updating an existing code set (n=20). Several open source software tools (n=3) were discovered. DISCUSSION There is a need for software tools that enable users to easily and quickly create, revise, extend, review and share code sets and we provide a list of recommendations for their design and implementation. CONCLUSION Research re-using EHR data could be improved through the further development, more widespread use and routine reporting of the methods by which clinical codes were selected.
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Affiliation(s)
- Richard Williams
- MRC Health eResearch Centre, University of Manchester, Manchester, UK; NIHR Greater Manchester Primary Care Patient Safety Translational Research Centre, University of Manchester, Manchester, UK.
| | - Evangelos Kontopantelis
- MRC Health eResearch Centre, University of Manchester, Manchester, UK; NIHR School for Primary Care Research, University of Manchester, Manchester, UK
| | - Iain Buchan
- MRC Health eResearch Centre, University of Manchester, Manchester, UK; NIHR Greater Manchester Primary Care Patient Safety Translational Research Centre, University of Manchester, Manchester, UK; NIHR Manchester Biomedical Research Centre, University of Manchester, Manchester, UK
| | - Niels Peek
- MRC Health eResearch Centre, University of Manchester, Manchester, UK; NIHR Greater Manchester Primary Care Patient Safety Translational Research Centre, University of Manchester, Manchester, UK
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14
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Daniel C, Ouagne D, Sadou E, Paris N, Hussain S, Jaulent M, Kalra D. Cross border semantic interoperability for learning health systems: The EHR4CR semantic resources and services. Learn Health Syst 2017; 1:e10014. [PMID: 31245551 PMCID: PMC6516724 DOI: 10.1002/lrh2.10014] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Revised: 07/07/2016] [Accepted: 07/28/2016] [Indexed: 12/15/2022] Open
Abstract
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.
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Affiliation(s)
- Christel Daniel
- Sorbonne Universités, UPMC Univ Paris 06, INSERM UMR_S 1142, LIMICSF‐75006ParisFrance
- AP‐HPParisFrance
| | - David Ouagne
- Sorbonne Universités, UPMC Univ Paris 06, INSERM UMR_S 1142, LIMICSF‐75006ParisFrance
| | - Eric Sadou
- Sorbonne Universités, UPMC Univ Paris 06, INSERM UMR_S 1142, LIMICSF‐75006ParisFrance
- AP‐HPParisFrance
| | | | - Sajjad Hussain
- Sorbonne Universités, UPMC Univ Paris 06, INSERM UMR_S 1142, LIMICSF‐75006ParisFrance
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15
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Jiang G, Kiefer RC, Rasmussen LV, Solbrig HR, Mo H, Pacheco JA, Xu J, Montague E, Thompson WK, Denny JC, Chute CG, Pathak J. Developing a data element repository to support EHR-driven phenotype algorithm authoring and execution. J Biomed Inform 2016; 62:232-42. [PMID: 27392645 DOI: 10.1016/j.jbi.2016.07.008] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2016] [Accepted: 07/04/2016] [Indexed: 01/25/2023]
Abstract
The Quality Data Model (QDM) is an information model developed by the National Quality Forum for representing electronic health record (EHR)-based electronic clinical quality measures (eCQMs). In conjunction with the HL7 Health Quality Measures Format (HQMF), QDM contains core elements that make it a promising model for representing EHR-driven phenotype algorithms for clinical research. However, the current QDM specification is available only as descriptive documents suitable for human readability and interpretation, but not for machine consumption. The objective of the present study is to develop and evaluate a data element repository (DER) for providing machine-readable QDM data element service APIs to support phenotype algorithm authoring and execution. We used the ISO/IEC 11179 metadata standard to capture the structure for each data element, and leverage Semantic Web technologies to facilitate semantic representation of these metadata. We observed there are a number of underspecified areas in the QDM, including the lack of model constraints and pre-defined value sets. We propose a harmonization with the models developed in HL7 Fast Healthcare Interoperability Resources (FHIR) and Clinical Information Modeling Initiatives (CIMI) to enhance the QDM specification and enable the extensibility and better coverage of the DER. We also compared the DER with the existing QDM implementation utilized within the Measure Authoring Tool (MAT) to demonstrate the scalability and extensibility of our DER-based approach.
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Affiliation(s)
- Guoqian Jiang
- Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA.
| | - Richard C Kiefer
- Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Luke V Rasmussen
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Harold R Solbrig
- Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Huan Mo
- Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA
| | - Jennifer A Pacheco
- Center for Genetic Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Jie Xu
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Enid Montague
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; School of Computing, DePaul University, Chicago, IL, USA
| | | | - Joshua C Denny
- Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA; Department of Medicine, Vanderbilt University, Nashville, TN, USA
| | | | - Jyotishman Pathak
- Division of Health Informatics, Weill Cornell Medical College, Cornell University, New York City, NY, USA
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Lablans M, Kadioglu D, Mate S, Leb I, Prokosch HU, Ückert F. Strategien zur Vernetzung von Biobanken. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2016; 59:373-8. [DOI: 10.1007/s00103-015-2299-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Zusammenfassung
Hintergrund
Nicht selten benötigt ein medizinisches Forschungsvorhaben mehr biologisches Material, als in einer einzigen Biobank verfügbar ist. Daher unterstützt eine Vielzahl von Strategien das Auffinden potentieller Forschungspartner mit passenden Proben, auch ohne dass diese zuvor in einer zentralisierten Sammlung zusammengeführt werden müssen.
Ziel
Der vorliegende Beitrag beschreibt die Klassifizierung verschiedener Strategien zur Vernetzung von Biomaterialbanken, speziell zur Probensuche, sowie eine IT-Infrastruktur, die diese Ansätze kombiniert.
Material und Methoden
Bestehende Strategien lassen sich nach drei Kriterien klassifizieren: a) Granularität der Probendaten: grobe Daten auf Bankebene (Katalog) vs. feingranulare Daten auf Probenebene, b) Speicherort der Probendaten: zentrale (zentraler Suchdienst) vs. dezentrale Datenhaltung (föderierte Suchdienste) und c) Automatisierungsgrad: automatisch (abfragebasiert, föderierter Suchdienst) vs. halbautomatisch (anfragebasiert, dezentrale Suche). Alle genannten Suchdienste setzen eine Datenintegration voraus; dabei helfen Metadaten bei der Überwindung semantischer Heterogenität.
Ergebnisse
Der „Common Service IT“ in BBMRI-ERIC („Biobanking and Biomolecular Resources Research Infrastructure-European Research Infrastructure Consortium“) vereint einen Katalog, die dezentrale Suche und Metadaten in einer integrierten Plattform, um Forschern vielseitige Werkzeuge zur Suche nach passendem Probenmaterial zu geben und bei den Biobankern gleichzeitig ein hohes Maß an Datenhoheit zu bewahren.
Diskussion
Trotz ihrer Unterschiede schließen sich die vorgestellten Strategien zur Vernetzung von Biomaterialbanken gegenseitig nicht aus. Vielmehr lassen sie sich in gemeinsamen Forschungsinfrastrukturen sinnvoll ergänzen und sie können sogar voneinander profitieren.
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Affiliation(s)
- Martin Lablans
- Medizinische Informatik in der Translationalen Onkologie, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, 69120, Heidelberg, Deutschland.
| | - Dennis Kadioglu
- Institut für medizinische Biometrie, Epidemiologie und Informatik (IMBEI), Universitätsmedizin Mainz, 55101, Mainz, Deutschland
| | - Sebastian Mate
- Lehrstuhl für Medizinische Informatik, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Deutschland
| | - Ines Leb
- Lehrstuhl für Medizinische Informatik, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Deutschland
| | - Hans-Ulrich Prokosch
- Lehrstuhl für Medizinische Informatik, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Deutschland
| | - Frank Ückert
- Medizinische Informatik in der Translationalen Onkologie, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, 69120, Heidelberg, Deutschland
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Dixon BE, Whipple EC, Lajiness JM, Murray MD. Utilizing an integrated infrastructure for outcomes research: a systematic review. Health Info Libr J 2015; 33:7-32. [PMID: 26639793 DOI: 10.1111/hir.12127] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2014] [Accepted: 10/16/2015] [Indexed: 02/06/2023]
Abstract
OBJECTIVE To explore the ability of an integrated health information infrastructure to support outcomes research. METHODS A systematic review of articles published from 1983 to 2012 by Regenstrief Institute investigators using data from an integrated electronic health record infrastructure involving multiple provider organisations was performed. Articles were independently assessed and classified by study design, disease and other metadata including bibliometrics. RESULTS A total of 190 articles were identified. Diseases included cognitive, (16) cardiovascular, (16) infectious, (15) chronic illness (14) and cancer (12). Publications grew steadily (26 in the first decade vs. 100 in the last) as did the number of investigators (from 15 in 1983 to 62 in 2012). The proportion of articles involving non-Regenstrief authors also expanded from 54% in the first decade to 72% in the last decade. During this period, the infrastructure grew from a single health system into a health information exchange network covering more than 6 million patients. Analysis of journal and article metrics reveals high impact for clinical trials and comparative effectiveness research studies that utilised data available in the integrated infrastructure. DISCUSSION Integrated information infrastructures support growth in high quality observational studies and diverse collaboration consistent with the goals for the learning health system. More recent publications demonstrate growing external collaborations facilitated by greater access to the infrastructure and improved opportunities to study broader disease and health outcomes. CONCLUSIONS Integrated information infrastructures can stimulate learning from electronic data captured during routine clinical care but require time and collaboration to reach full potential.
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Affiliation(s)
- Brian E Dixon
- Richard M. Fairbanks School of Public Health at IUPUI, Indianapolis, IN, USA.,Regenstrief Institute, Inc., Indianapolis, IN, USA.,Center for Health Information and Communication, Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service CIN 13-416, Richard L. Roudebush VA Medical Center, Indianapolis, IN, USA
| | - Elizabeth C Whipple
- Ruth Lilly Medical Library, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Michael D Murray
- Regenstrief Institute and Purdue University, Indianapolis, IN, USA
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Sun H, Depraetere K, De Roo J, Mels G, De Vloed B, Twagirumukiza M, Colaert D. Semantic processing of EHR data for clinical research. J Biomed Inform 2015; 58:247-259. [PMID: 26515501 DOI: 10.1016/j.jbi.2015.10.009] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2015] [Revised: 09/10/2015] [Accepted: 10/17/2015] [Indexed: 11/24/2022]
Abstract
There is a growing need to semantically process and integrate clinical data from different sources for clinical research. This paper presents an approach to integrate EHRs from heterogeneous resources and generate integrated data in different data formats or semantics to support various clinical research applications. The proposed approach builds semantic data virtualization layers on top of data sources, which generate data in the requested semantics or formats on demand. This approach avoids upfront dumping to and synchronizing of the data with various representations. Data from different EHR systems are first mapped to RDF data with source semantics, and then converted to representations with harmonized domain semantics where domain ontologies and terminologies are used to improve reusability. It is also possible to further convert data to application semantics and store the converted results in clinical research databases, e.g. i2b2, OMOP, to support different clinical research settings. Semantic conversions between different representations are explicitly expressed using N3 rules and executed by an N3 Reasoner (EYE), which can also generate proofs of the conversion processes. The solution presented in this paper has been applied to real-world applications that process large scale EHR data.
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Affiliation(s)
- Hong Sun
- Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, 9000 Gent, Belgium.
| | - Kristof Depraetere
- Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, 9000 Gent, Belgium
| | - Jos De Roo
- Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, 9000 Gent, Belgium
| | - Giovanni Mels
- Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, 9000 Gent, Belgium
| | - Boris De Vloed
- Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, 9000 Gent, Belgium
| | - Marc Twagirumukiza
- Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, 9000 Gent, Belgium
| | - Dirk Colaert
- Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, 9000 Gent, Belgium
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User Satisfaction Evaluation of the EHR4CR Query Builder: A Multisite Patient Count Cohort System. BIOMED RESEARCH INTERNATIONAL 2015; 2015:801436. [PMID: 26539525 PMCID: PMC4619869 DOI: 10.1155/2015/801436] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/30/2015] [Accepted: 07/02/2015] [Indexed: 11/17/2022]
Abstract
The Electronic Health Records for Clinical Research (EHR4CR) project aims to develop services and technology for the leverage reuse of Electronic Health Records with the purpose of improving the efficiency of clinical research processes. A pilot program was implemented to generate evidence of the value of using the EHR4CR platform. The user acceptance of the platform is a key success factor in driving the adoption of the EHR4CR platform; thus, it was decided to evaluate the user satisfaction. In this paper, we present the results of a user satisfaction evaluation for the EHR4CR multisite patient count cohort system. This study examined the ability of testers (n = 22 and n = 16 from 5 countries) to perform three main tasks (around 20 minutes per task), after a 30-minute period of self-training. The System Usability Scale score obtained was 55.83 (SD: 15.37), indicating a moderate user satisfaction. The responses to an additional satisfaction questionnaire were positive about the design of the interface and the required procedure to design a query. Nevertheless, the most complex of the three tasks proposed in this test was rated as difficult, indicating a need to improve the system regarding complicated queries.
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Xu J, Rasmussen LV, Shaw PL, Jiang G, Kiefer RC, Mo H, Pacheco JA, Speltz P, Zhu Q, Denny JC, Pathak J, Thompson WK, Montague E. Review and evaluation of electronic health records-driven phenotype algorithm authoring tools for clinical and translational research. J Am Med Inform Assoc 2015. [PMID: 26224336 DOI: 10.1093/jamia/ocv070] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
OBJECTIVE To review and evaluate available software tools for electronic health record-driven phenotype authoring in order to identify gaps and needs for future development. MATERIALS AND METHODS Candidate phenotype authoring tools were identified through (1) literature search in four publication databases (PubMed, Embase, Web of Science, and Scopus) and (2) a web search. A collection of tools was compiled and reviewed after the searches. A survey was designed and distributed to the developers of the reviewed tools to discover their functionalities and features. RESULTS Twenty-four different phenotype authoring tools were identified and reviewed. Developers of 16 of these identified tools completed the evaluation survey (67% response rate). The surveyed tools showed commonalities but also varied in their capabilities in algorithm representation, logic functions, data support and software extensibility, search functions, user interface, and data outputs. DISCUSSION Positive trends identified in the evaluation included: algorithms can be represented in both computable and human readable formats; and most tools offer a web interface for easy access. However, issues were also identified: many tools were lacking advanced logic functions for authoring complex algorithms; the ability to construct queries that leveraged un-structured data was not widely implemented; and many tools had limited support for plug-ins or external analytic software. CONCLUSIONS Existing phenotype authoring tools could enable clinical researchers to work with electronic health record data more efficiently, but gaps still exist in terms of the functionalities of such tools. The present work can serve as a reference point for the future development of similar tools.
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Affiliation(s)
- Jie Xu
- Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Luke V Rasmussen
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Pamela L Shaw
- Galter Health Science Library, Clinical and Translational Sciences Institute (NUCATS), Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Guoqian Jiang
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Richard C Kiefer
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Huan Mo
- Department of Biomedical Informatics, School of Medicine, Vanderbilt University, Nashville, TN, USA
| | - Jennifer A Pacheco
- Center for Genetic Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Peter Speltz
- Department of Biomedical Informatics, School of Medicine, Vanderbilt University, Nashville, TN, USA
| | - Qian Zhu
- Department of Information Systems, University of Maryland, Baltimore County (UMBC), Baltimore, MD, USA
| | - Joshua C Denny
- Department of Biomedical Informatics, School of Medicine, Vanderbilt University, Nashville, TN, USA
| | - Jyotishman Pathak
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - William K Thompson
- Center for Biomedical Research Informatics, NorthShore University Health System, Evanston, IL, USA
| | - Enid Montague
- Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
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Bialke M, Penndorf P, Wegner T, Bahls T, Havemann C, Piegsa J, Hoffmann W. A workflow-driven approach to integrate generic software modules in a Trusted Third Party. J Transl Med 2015; 13:176. [PMID: 26040848 PMCID: PMC4467617 DOI: 10.1186/s12967-015-0545-6] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2015] [Accepted: 05/25/2015] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Cohort studies and registries rely on massive amounts of personal medical data. Therefore, data protection and information security as well as ethical aspects gain in importance and need to be considered as early as possible during the establishment of a study. Resulting legal and ethical obligations require a precise implementation of appropriate technical and organisational measures for a Trusted Third Party. METHODS This paper defines and organises a consistent workflow-management to realize a Trusted Third Party. In particular, it focusses the technical implementation of a Trusted Third Party Dispatcher to provide basic functionalities (including identity management, pseudonym administration and informed consent management) and measures required to meet study specific conditions of cohort studies and registries. Thereby several independent open source software modules developed and provided by the MOSAIC project are used. This technical concept offers the necessary flexibility and extensibility to address legal and ethical requirements of individual scenarios. RESULTS The developed concept for a Trusted Third Party Dispatcher allows mapping single process steps as well as individual requirements and characteristics of particular studies to workflows, which in turn can be combined to model complex Trusted Third Party processes. The uniformity of this approach permits unrestricted re-combination of the available functionalities (depending on the applied software modules) for various research projects. CONCLUSION The proposed approach for the technical implementation of an independent Trusted Third Party reduces the effort for scenario specific implementations as well as for maintenance. The applicability and the efficacy of the concept for a workflow-driven Trusted Third Party could be confirmed during the establishment of several nationwide studies (e.g. German Centre for Cardiovascular Research and the National Cohort).
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Affiliation(s)
- Martin Bialke
- Institute for Community Medicine, Section Epidemiology of Health Care and Community Health, University Medicine Greifswald, Ellernholzstr. 1-2, 17487, Greifswald, Germany.
| | - Peter Penndorf
- Institute for Community Medicine, Section Epidemiology of Health Care and Community Health, University Medicine Greifswald, Ellernholzstr. 1-2, 17487, Greifswald, Germany. .,German Centre for Cardiovascular Research (DZHK), Greifswald, Germany.
| | - Tim Wegner
- Institute of Applied Microelectronics and Computer Engineering, University of Rostock, Rostock, Germany.
| | - Thomas Bahls
- Institute for Community Medicine, Section Epidemiology of Health Care and Community Health, University Medicine Greifswald, Ellernholzstr. 1-2, 17487, Greifswald, Germany. .,German Centre for Cardiovascular Research (DZHK), Greifswald, Germany.
| | - Christoph Havemann
- Institute for Community Medicine, Section Epidemiology of Health Care and Community Health, University Medicine Greifswald, Ellernholzstr. 1-2, 17487, Greifswald, Germany.
| | - Jens Piegsa
- Institute for Community Medicine, Section Epidemiology of Health Care and Community Health, University Medicine Greifswald, Ellernholzstr. 1-2, 17487, Greifswald, Germany.
| | - Wolfgang Hoffmann
- Institute for Community Medicine, Section Epidemiology of Health Care and Community Health, University Medicine Greifswald, Ellernholzstr. 1-2, 17487, Greifswald, Germany. .,German Centre for Cardiovascular Research (DZHK), Greifswald, Germany.
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Handels H, Ingenerf J. Medical informatics, biometry and epidemiology. Recent developments and advances. Methods Inf Med 2014; 53:235-7. [PMID: 25109423 DOI: 10.3414/me14-10-0005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- H Handels
- Prof. Dr. rer. nat. habil. Heinz Handels, Institute of Medical Informatics, University of Lübeck, Ratzeburger Allee 160, 23562 Lübeck, Germany, E-mail:
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