Subscribe to RSS
![](/products/assets/desktop/img/oa-logo.png)
DOI: 10.1055/s-0042-1742530
Clinical Research Informatics
![](https://www.thieme-connect.de/media/10.1055-s-00034612/202201/lookinside/thumbnails/10-1055-s-0042-1742530_daniel-1.jpg)
Summary
Objectives: To summarize key contributions to current research in the field of Clinical Research Informatics (CRI) and to select best papers published in 2021.
Method: Using PubMed, we did a bibliographic search using a combination of MeSH descriptors and free-text terms on CRI, followed by a double-blind review in order to select a list of candidate best papers to be peer-reviewed by external reviewers. After peer-review ranking, three section editors met for a consensus meeting and the editorial team was organized to finally conclude on the selected three best papers.
Results: Among the 1,096 papers (published in 2021) returned by the search and in the scope of the various areas of CRI, the full review process selected three best papers. The first best paper describes an operational and scalable framework for generating EHR datasets based on a detailed clinical model with an application in the domain of the COVID-19 pandemics. The authors of the second best paper present a secure and scalable platform for the preprocessing of biomedical data for deep data-driven health management applied for the detection of pre-symptomatic COVID-19 cases and for biological characterization of insulin-resistance heterogeneity. The third best paper provides a contribution to the integration of care and research activities with the REDCap Clinical Data and Interoperability sServices (CDIS) module improving the accuracy and efficiency of data collection.
Conclusions: The COVID-19 pandemic is still significantly stimulating research efforts in the CRI field to improve the process deeply and widely for conducting real-world studies as well as for optimizing clinical trials, the duration and cost of which are constantly increasing. The current health crisis highlights the need for healthcare institutions to continue the development and deployment of Big Data spaces, to strengthen their expertise in data science and to implement efficient data quality evaluation and improvement programs.
Keywords
Clinical Trials as Topic - Observational Studies as Topic - Real-world Data - Real-world Evidence Generation - Phenotyping1 Proposal for a Regulation of the European Parliament and of The Council Laying Down Harmonised Rules on Artificial Intelligence (Artificial Intelligence Act) And Amending Certain Union Legislative Acts https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52021PC0206
Section Editors for the IMIA Yearbook Section on Clinical Research Informatics
Publication History
Article published online:
04 December 2022
© 2022. IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)
Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany
-
References
- 1 Bahmani A, Alavi A, Buergel T, Upadhyayula S, Wang Q, Ananthakrishnan SK, et al. A scalable, secure, and interoperable platform for deep data-driven health management. Nat Commun 2021 Oct 1;12(1):5757.
- 2 Mathes T, Rombey T, Kuss O, Pieper D. No inexplicable disagreements between real-world data-based nonrandomized controlled studies and randomized controlled trials were found. J Clin Epidemiol 2021 May;133:1-13.
- 3 Pedrera-Jiménez M, García-Barrio N, Cruz-Rojo J, Terriza-Torres AI, López-Jiménez EA, Calvo-Boyero F, et al. Obtaining EHR derived datasets for COVID-19 research within a short time: a flexible methodology based on Detailed Clinical Models. J Biomed Inform 2021 Mar;115:103697.
- 4 Verma AA, Pasricha SV, Jung HY, Kushnir V, Mak DYF, Koppula R, et al. Assessing the quality of clinical and administrative data extracted from hospitals: the General Medicine Inpatient Initiative (GEMINI) experience. J Am Med Inform Assoc 2021 Mar 1;28(3):578-87.
- 5 Blacketer C, Defalco FJ, Ryan PB, Rijnbeek PR. Increasing trust in real-world evidence through evaluation of observational data quality. J Am Med Inform Assoc 2021 Sep 18;28(10):2251-7.
- 6 Kapsner LA, Mang JM, Mate S, Seuchter SA, Vengadeswaran A, Bathelt F, et al. Linking a Consortium-Wide Data Quality Assessment Tool with the MIRACUM Metadata Repository. Appl Clin Inform 2021 Aug;12(4):826-35.
- 7 Chen WC, Li H, Wang C, Lu N, Song C, Tiwari R, et al. Evaluation of diagnostic tests for low prevalence diseases: a statistical approach for leveraging real-world data to accelerate the study. J Biopharm Stat 2021 May 4;31(3):375-90.
- 8 Schulz WL, Young HP, Coppi A, Mortazavi BJ, Lin Z, Jean RA, et al. Temporal relationship of computed and structured diagnoses in electronic health record data. BMC Med Inform Decis Mak 2021 Feb 17;21(1):61.
- 9 Dhayne H, Kilany R, Haque R, Taher Y. EMR2vec: Bridging the gap between patient data and clinical trial. Comput Ind Eng 2021 Jun;156:107236.
- 10 Liu L, Bustamante R, Earles A, Demb J, Messer K, Gupta S. A strategy for validation of variables derived from large-scale electronic health record data. J Biomed Inform 2021 Sep;121:103879.
- 11 Liu H, Chi Y, Butler A, Sun Y, Weng C. A knowledge base of clinical trial eligibility criteria. J Biomed Inform 2021 May;117:103771.
- 12 Rogers JR, Hripcsak G, Cheung YK, Weng C. Clinical comparison between trial participants and potentially eligible patients using electronic health record data: A generalizability assessment method. J Biomed Inform 2021 Jul;119:103822.
- 13 Cheng AC, Duda SN, Taylor R, Delacqua F, Lewis AA, Bosler T, et al. REDCap on FHIR: Clinical Data Interoperability Services. J Biomed Inform 2021 Sep;121:103871.
- 14 Forrest CB, McTigue KM, Hernandez AF, Cohen LW, Cruz H, Haynes K, et al. PCORnet® 2020: current state, accomplishments, and future directions. J Clin Epidemiol 2021 Jan;129:60-7.
- 15 Ferretti A, Ienca M, Sheehan M, Blasimme A, Dove ES, Farsides B, et al. Ethics review of big data research: What should stay and what should be reformed? BMC Med Ethics 2021 Apr 30;22(1):51.