Information Technology for Clinical, Translational and Comparative Effectiveness Research

Summary

Objectives: To select and summarize key constributions to current research and to select best papers published in 2014 in the field of Clinical Research Informatics (CRI).

Method: A bibliographic search using a combination of MeSH and free terms search over PubMed on Clinical Research Informatics (CRI) was performed followed by a double-blind literature review.

Results: The review process yielded four papers, illustrating various aspects of current research efforts done in the area of CRI. The first paper exemplifies the process of developping a domain ontology for integrating structured, unstructured, and signal data into a coherent structure for patient care as well as clinical research. In the second paper, the authors analysed in five sites’ hospital information system environments in Germany the possibility of implementing a patient recruitment process and provided recommendations for the development of dedicated patient recruitment modules. The third paper describes the IMI EHR4CR project which developed an instance of a platform, providing communication, security and semantic interoperability services to the eleven participating hospitals and ten pharmaceutical companies located in seven European countries. The last paper describes the relation between health status severity and the availability of data in EHR systems. They demonstrate that it introduces a biasis in patient selection for clinical research.

Conclusions: Distributed research networks are growing in importance for clinical research and population health surveillance and current research demonstartes that different projects and initiatives could be well placed to deliver international scale solutions to enable the reuse of hospital EHR data to support clinical research studies. Selected articles demonstrate the potential of formal representation of multimodal and multi-level data in supporting data interoperability across clinical research and care domains. With the development of pragmatic research, designed with input from health systems and producing evidence that can be readily used to improve care, a key issue for “learning health care organizations” is to systematically assess the quality of their data.

Keywords

Medical informatics - biomedical research - clinical research - patient selection - phenotyping

 

• References

• 1 Bowton E, Field JR, Wang S, Schildcrout JS, Van Driest SL, Delaney JT. et al. Biobanks and electronic medical records: enabling cost-effective research. Sci Transl Med 2014; Apr 30 6 (234) 234.
• 2 Boyd JH, Randall SM, Ferrante AM, Bauer JK, Brown AP, Semmens JB. Technical challenges of providing record linkage services for research. BMC Med Inform Decis Mak 2014; Mar 31 14: 23.
• 3 Curtis JR, Wright NC, Xie F, Chen L, Zhang J, Saag KG. et al. Use of health plan combined with registry data to predict clinical trial recruitment. Clin Trials 2014; Feb 11 (01) 96-101.
• 4 Doods J, Botteri F, Dugas M, Fritz F. EHR4CR WP7. A European inventory of common electronic health record data elements for clinical trial feasibility. Trials 2014; Jan 10 15: 18.
• 5 He S, Narus SP, Facelli JC, Lau LM, Botkin JR, Hurdle JF. A domain analysis model for eIRB systems: Addressing the weak link in clinical research informatics. J Biomed Inform 2014; Dec 52: 121-9.
• 6 Holmes JH, Elliott TE, Brown JS, Raebel MA, Davidson A, Nelson AF. et al. Clinical research data warehouse governance for distributed research networks in the USA: a systematic review of the literature. J Am Med Inform Assoc 2014; Jul-Aug 21 (04) 730-6.
• 7 Jiang G, Evans J, Oniki TA, Coyle JF, Bain L, Huff SM. et al. Harmonization of detailed clinical models with clinical study data standards. Methods Inf Med 2015; Jan 12 54 (01) 65-74.
• 8 Kahn MG, Weng C. Clinical research informatics: a conceptual perspective. J Am Med Inform Assoc 2012; Jun 19 e1 e36-42.
• 9 Moor GD, Sundgren M, Kalra D, Schmidt A, Dugas M, Claerhout B. et al. Using Electronic Health Records for Clinical Research: the Case of the EHR4CR Project. J Biomed Inform 2014 Oct 18.
• 10 Murphy SN, Herrick C, Wang Y, Wang TD, Sack D, Andriole KP. et al. High Throughput Tools to Access Images from Clinical Archives for Research. J Digit Imaging 2014 Oct 15.
• 11 Rusanov A, Weiskopf NG, Wang S, Weng C. Hidden in plain sight: bias towards sick patients when sampling patients with sufficient electronic health record data for research. BMC Med Inform Decis Mak 2014; Jun 11 14: 51.
• 12 Sahoo SS, Lhatoo SD, Gupta DK, Cui L, Zhao M, Jayapandian C. et al. Epilepsy and seizure ontology: towards an epilepsy informatics infrastructure for clinical research and patient care. J Am Med Inform Assoc 2014; Jan-Feb 21 (01) 82-9.
• 13 Schreiweis B, Trinczek B, Köpcke F, Leusch T, Majeed RW, Wenk J. et al. Comparison of electronic health record system functionalities to support the patient recruitment process in clinical trials. Int J Med Inform 2014; Nov 83 (11) 860-8.
• 14 Shivade C, Raghavan P, Fosler-Lussier E, Embi PJ, Elhadad N, Johnson SB. et al. A review of approaches to identifying patient phenotype cohorts using electronic health records. J Am Med Inform Assoc 2014; Mar-Apr 21 (02) 221-30.
• 15 Tate AR, Beloff N, Al-Radwan B, Wickson J, Puri S, Williams T. et al. Exploiting the potential of large databases of electronic health records for research using rapid search algorithms and an intuitive query interface. J Am Med Inform Assoc 2014; Mar-Apr 21 (02) 292-8.
• 16 Trifirò G, Coloma PM, Rijnbeek PR, Romio S, Mosseveld B, Weibel D. et al. Combining multiple healthcare databases for postmarketing drug and vaccine safety surveillance: why and how?. J Intern Med 2014; Jun 275 (06) 551-61.
• 17 van Ommen GJ, Törnwall O, Bréchot C, Dagher G, Galli J, Hveem K. et al. BBMRI-ERIC as a resource for pharmaceutical and life science industries: the development of biobank-based Expert Centres. Eur J Hum Genet 2014 Nov 19.
• 18 Xu W, Guan Z, Sun J, Wang Z, Geng Y. Development of an open metadata schema for prospective clinical research (openPCR) in China. Methods Inf Med 2014; 53 (01) 39-46.