Clinical Research Informatics: Survey of Recent Advances and Trends in a Maturing Field

Summary

Objectives: To provide a survey of the field of clinical research informatics (CRI), focusing in particular on significant developments over the past 3 years and the insights they provide about the progress and state of the field.

Methods: An iterative “scoping review” of the literature published in scientific journals and conference proceedings that are relevant to CRI, from late 2009 to early 2013.

Results: 212 articles were identified, and 64 were selected to illustrate recent advances in the field. Based on those, six categories of CRI activity were identified: Data and Knowledge Management, Discovery and Standards; Clinical Data Re-Use for Research; Researcher Support and Resources; Participant Recruitment; Patients/Consumers and CRI; Policy, Regulatory and Fiscal Matters.

Conclusions: This survey demonstrates that the field of CRI has matured and is now well established. The ongoing work is essential to overcome many of the challenges the clinical research enterprise is facing and more work is needed. Even as work continues to establish necessary infrastructure, methods, and best practices, CRI researchers should strive for more rigorous study designs to evaluate the impacts of the work in the field. There is little doubt that the field is poised for rapid growth, and that the CRI literature will continue to reflect that growth in years to come.

Keywords

Clinical research - medical informatics - clinical trials - translational science - review literature as topic

• References

• 1 The Cancer Biomedical Informatics Grid (caBIG): infrastructure and applications for a worldwide research community. Stud Health Technol Inform 2007; 129 (Pt 1) 330-4.
• 2 Kakazu KK, Cheung LW, Lynne W. The Cancer Biomedical Informatics Grid (caBIG): pioneering an expansive network of information and tools for collaborative cancer research. Hawaii Med J 2004; Sep 63 (9) 273-5.
• 3 Zerhouni EA. Translational and clinical science-time for a new vision. N Engl J Me. 2005; Oct 13 353 (15) 1621-3.
• 4 Zerhouni EA. Clinical research at a crossroads: the NIH roadmap. J Investig Med 2006; May 1 54 (4) 171-3.
• 5 Payne PR, Johnson SB, Starren JB, Tilson HH, Dowdy D. Breaking the translational barriers: the value of integrating biomedical informatics and translational research. J Investig Med 2005; May 53 (4) 192-200.
• 6 Sung NS, Crowley Jr. WF, Genel M, Salber P, Sandy L, Sherwood LM. et al. Central challenges facing the national clinical research enterprise. JAMA 2003; Mar 12 289 (10) 1278-87.
• 7 Oster S, Langella S, Hastings S, Ervin D, Madduri R, Phillips J. et al. caGrid 1.0: an enterprise Grid infrastructure for biomedical research. J Am Med Inform Assoc 2008; Mar-Apr 15 (2) 138-49.
• 8 Saltz J, Oster S, Hastings S, Langella S, Kurc T, Sanchez W. et al. caGrid: design and implementation of the core architecture of the cancer biomedical informatics grid. Bioinformatics 2006; Aug 1 22 (15) 1910-6.
• 9 Embi PJ, Payne PR. Clinical research informatics: challenges, opportunities and definition for an emerging domain. J Am Med Inform Assoc 2009; May-Jun 16 (3) 316-27.
• 10 Chung TK, Kukafka R, Johnson SB. Reengineering clinical research with informatics. J Investig Med 2006; Sep 54 (6) 327-33.
• 11 Oster S, Langella S, Hastings S, Ervin D, Madduri R, Phillips J. et al. caGrid 1.0: An Enterprise Grid Infrastructure for Biomedical Research. J Am Med Inform Assoc 2008; Jan 1 15 (2) 138-49.
• 12 The Cancer Biomedical Informatics Grid (caBIG): infrastructure and applications for a worldwide research community. Medinfo 2007; 12 (Pt 1) 330-4.
• 13 Collen MF. Clinical research databases--a historical review. J Med Syst 1990; Dec 14 (6) 323-44.
• 14 Gillen JE, Tse T, Ide NC, McCray AT. Design, implementation and management of a web-based data entry system for ClinicalTrials.gov. Stud Health Technol Inform 2004; 107 (Pt 2) 1466-70.
• 15 Holve E, Segal C, Lopez MH, Rein A, Johnson BH. The Electronic Data Methods (EDM) forum for comparative effectiveness research (CER). Med Care 2012; Jul 50 Suppl S7-10.
• 16 Friedman CP, Wong AK, Blumenthal D. Achieving a nationwide learning health system. Sci Transl Med. [Research Support, U.S. Gov't, Non-P.H.S.] 2010 Nov 10 2. (57) 57cm29.
• 17 Levac D, Colquhoun H, O'Brien KK. Scoping studies: advancing the methodology. Implement Sci. 2010 5. 69.
• 18 Murphy SN, Weber G, Mendis M, Gainer V, Chueh HC, Churchill S. et al. Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2). J Am Med Inform Assoc 2010; Jan 1 17 (2) 124-30.
• 19 Kohane IS, Churchill SE, Murphy SN. A translational engine at the national scale: informatics for integrating biology and the bedside. J Am Med Inform Assoc [Research Support, N.I.H., Extramural]. 2012; 19 (2) 181-5.
• 20 Segagni D, Ferrazzi F, Larizza C, Tibollo V, Napolitano C, Priori SG. et al. R Engine Cell: integrating R into the i2b2 software infrastructure. J Am Med Inform Assoc. 2011 Jan 24.
• 21 Weber GM, Murphy SN, McMurry AJ, Macfadden D, Nigrin DJ, Churchill S. et al. The Shared Health Research Information Network (SHRINE): a prototype federated query tool for clinical data repositories. J Am Med Inform Assoc 2009; Jan 1 16 (5) 624-30.
• 22 Anderson N, Abend A, Mandel A, Geraghty E, Gabriel D, Wynden R. et al. Implementation of a deidentified federated data network for population-based cohort discovery. J Am Med Inform Assoc. 2011 Aug 26.
• 23 Brajovic S, Piazza-Hepp T, Swartz L, Dal Pan G. Quality assessment of spontaneous triggered adverse event reports received by the Food and Drug Administration. Pharmacoepidemiol Drug Saf 2012; Jun 21 (6) 565-70 discussion 71-2.
• 24 Tasneem A, Aberle L, Ananth H, Chakraborty S, Chiswell K, McCourt BJ. et al. The Database for Aggregate Analysis of ClinicalTrials.gov (AACT) and Subsequent Regrouping by Clinical Specialty. PLoS One 2012; Apr 16 7 (3) e33677.
• 25 Sim I, Carini S, Tu S, Wynden R, Pollock BH, Mollah SA. et al. The human studies database project: federating human studies design data using the ontology of clinical research. AMIA Summits Transl Sci Proc 2010; Jan 1 2010: 51-5.
• 26 Richesson RL, Krischer J. Data standards in clinical research: gaps, overlaps, challenges and future directions. J Am Med Inform Assoc 2007; 14 (6) 687-96.
• 27 Kush RD, Helton E, Rockhold FW, Hardison CD. Electronic health records, medical research, and the Tower of Babel. N Engl J Med 2008; 358 (16) 1738-40.
• 28 Holzer K, Gall W. Utilizing IHE-based electronic health record systems for secondary use. Methods Inf Med 2011; 50 (4) 319.
• 29 Fridsma DB, Evans J, Hastak S, Mead CN. The BRIDG project: a technical report. J Am Med Inform Assoc 2008; Mar-Apr 15 (2) 130-7.
• 30 Breil B, Kenneweg J, Fritz F, Bruland P, Doods D, Trinczek B. et al. Multilingual medical data models in ODM format-a novel form-based approach to semantic interoperability between routine health-care and clinical research. Appl Clin Inf 2012; 3: 276-89.
• 31 Weng C, Tu SW, Sim I, Richesson R. Formal representations of eligibility criteria: A literature review. J Biomed Inform 2010; 43 (3) 451.
• 32 Tenenbaum JD, Whetzel PL, Anderson K, Borromeo CD, Dinov ID, Gabriel D. et al. The Biomedical Resource Ontology (BRO) to enable resource discovery in clinical and translational research. J Biomed Inform 2011; Mar 44 (1) 137-45.
• 33 Kong YM, Dahlke C, Xiang Q, Qian Y, Karp D, Scheuermann RH. Toward an ontology-based framework for clinical research databases. Journal ofbiomedical informatics. 2011; Mar 44 (1) 48-58.
• 34 Szalma S, Koka V, Khasanova T, Perakslis ED. Effective knowledge management in translational medicine. J Transl Med. 2010 Jan 1 8. 68.
• 35 Richesson RL, Nadkarni P. Data standards for clinical research data collection forms: current status and challenges. J Am Med Inform Assoc 2011; May 12 18 (3) 341-6.
• 36 Shaw M, Detwiler LT, Noy N, Brinkley J, Suciu D. vSPARQL: a view definition language for the semantic web. J Biomed Inform 2011; Mar 44 (1) 102-17.
• 37 Wynden R, Weiner M, Sim I, Gabriel D, Casale M, Carini S. et al. Ontology mapping and data discovery for the translational investigator. AMIA Summits Transl Sci Proc 2010; 2010: 66-70.
• 38 Rea S, Pathak J, Savova G, Oniki TA, Westberg L, Beebe CE. et al. Building a robust, scalable and standards-driven infrastructure for secondary use of EHR data: The SHARPn project. J Biomed Inform 2012; 45 (4) 763-71.
• 39 Behrman RE, Benner JS, Brown JS, McClellan M, Woodcock J, Platt R. Developing the Sentinel System-a national resource for evidence development. N Engl J Med 2011; 364 (6) 498-9.
• 40 El Fadly A, Rance B, Lucas N, Mead C, Chatellier G, Lastic P-Y. et al. Integrating clinical research with the healthcare enterprise: from the RE-USE project to the EHR4CR platform. J Biomed Inform 2011; 44: S94-S102.
• 41 Carroll RJ, Thompson WK, Eyler AE, Mandelin AM, Cai T, Zink RM. et al. Portability of an algorithm to identify rheumatoid arthritis in electronic health records. J Am Med Inform Assoc. 2012 Mar 28.
• 42 Denny JC, Ritchie MD, Basford MA, Pulley JM, Bastarache L, Brown-Gentry K. et al. PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations. Bioin-formatics 2010; May 1 26 (9) 1205-10.
• 43 Ritchie MD, Denny JC, Crawford DC, Ramirez AH, Weiner JB, Pulley JM. et al. Robust replication of genotype-phenotype associations across multiple diseases in an electronic medical record. Am J Hum Genet 2010; Apr 9 86 (4) 560-72.
• 44 Kho AN, Pacheco JA, Peissig PL, Rasmussen L, Newton KM, Weston N. et al. Electronic medical records for genetic research: results of the eMERGE consortium. Sci Transl Med. 2011 Apr 20 3. (79) 79re1.
• 45 Dregan A, Toschke MA, Wolfe CD, Rudd A, Ashworth M, Gulliford MC. Utility of electronic patient records in primary care for stroke secondary prevention trials. BMC Public Health. 2011 11. 86.
• 46 Sagreiya H, Altman RB. The utility of general purpose versus specialty clinical databases for research: warfarin dose estimation from extracted clinical variables. J Biomed Inform 2010; Oct 43 (5) 747-51.
• 47 Kiragga AN, Castelnuovo B, Schaefer P, Muwonge T, Easterbrook PJ. Quality of data collection in a large HIV observational clinic database in sub-Saharan Africa: implications for clinical research and audit of care. J Int AIDS Soc 2011; 14: 3.
• 48 Parsons A, McCullough C, Wang J, Shih S. Validity of electronic health record-derived quality measurement for performance monitoring. J Am Med Inform Assoc. 2012 Mar 09.
• 49 Kern LM, Malhotra S, Barron Y, Quaresimo J, Dhopeshwarkar R, Pichardo M. et al. Accuracy of Electronically Reported “Meaningful Use” Clinical Quality Measures: A Cross-sectional Study. Ann Intern Med 2013; Jan 15 158 (2) 77-83.
• 50 Herzberg S, Rahbar K, Stegger L, Schafers M, Dugas M. Concept and implementation of a computer-based reminder system to increase completeness in clinical documentation. Int J Med Inform 2011; Jun 80 (5) 351-8.
• 51 Wright A, Pang J, Feblowitz JC, Maloney FL, Wilcox AR, McLoughlin KS. et al. Improving completeness of electronic problem lists through clinical decision support: a randomized, controlled trial. J Am Med Inform Assoc. 2012 Feb 03.
• 52 Murphy SN, Dubey A, Embi PJ, Harris PA, Richter BG, Turisco F. et al. Current state of information technologies for the clinical research enterprise across academic medical centers. Clin Transl Sci 2012; Jun 5 (3) 281-4.
• 53 Pulley J, Harris P, Yarbrough T, Swafford J, Edwards T, Bernard G. An informatics-based tool to assist researchers in initiating research at an academic medical center: Vanderbilt Customized Action Plan. Acad Med 2010; Jan 1 85 (1) 164-8.
• 54 Payne PRO, Borlawsky TB, Rice R, Embi PJ. Evaluating the impact of conceptual knowledge engineering on the design and usability of a clinical and translational science collaboration portal. AMIA Summits Transl Sci Proc 2010; Jan 1 2010: 41-5.
• 55 Borlawsky TB, Lele O, Jensen D, Hood NE, Wewers ME. Enabling distributed electronic research data collection for a rural Appalachian tobacco cessation study. J Am Med Inform Assoc 2011; Dec 18 Suppl 1 i140-3.
• 56 Shi Q, You YN, Nelson H, Allen MS, Winchester D, Stewart A. et al. Cancer registries: a novel alternative to long-term clinical trial follow-up based on results of a comparative study. Clin Trials 2010; Dec 1 7 (6) 686-95.
• 57 Payne PRO, Borlawsky TB, Stephens W, Barrett MC, Nguyen-Pham T, Greaves AW. The TRITON Project: Design and Implementation of an Integrative Translational Research Information Management Platform. AMIA Annu Symp Proc 2010; Jan 1 2010: 617-21.
• 58 Nagarajan R, Lowery CL, Hogan WR. Temporal evolution of biomedical research grant collaborations across multiple scales--a CTSA baseline study. AMIA Annual Symposium proceedings / AMIA Symposium AMIA Symposium 2011; 2011: 987-93.
• 59 Kitterman DR, Cheng SK, Dilts DM, Orwoll ES. The prevalence and economic impact of low-enrolling clinical studies at an academic medical center. Acad Med 2011; Nov 86 (11) 1360-6.
• 60 Embi PJ, Jain A, Clark J, Bizjack S, Hornung R, Harris CM. Effect of a clinical trial alert system on physician participation in trial recruitment. Arch Intern Med 2005; Oct 24 165 (19) 2272-7.
• 61 Embi PJ, Jain A, Clark J, Harris CM. Development of an electronic health record-based Clinical Trial Alert system to enhance recruitment at the point of care. AMIA Annu Symp Proc 2005; 231-5.
• 62 Herasevich V, Pieper MS, Pulido J, Gajic O. Enrollment into a time sensitive clinical study in the critical care setting: results from computerized septic shock sniffer implementation. J Am Med Inform Assoc 2011; Aug 16 18 (5) 639-44.
• 63 Weng C, Bigger JT, Busacca L, Wilcox A, Getaneh A. Comparing the effectiveness of a clinical registry and a clinical data warehouse for supporting clinical trial recruitment: a case study. AMIA Annu Symp Proc 2010; Jan 1 2010: 867-71.
• 64 Embi PJ, Leonard AC. Evaluating alert fatigue over time to EHR-based clinical trial alerts: findings from a randomized controlled study. J Am Med Inform Assoc 2012; Jun 1 19 (e1) e145-e8.
• 65 Harris PA, Scott KW, Lebo L, Hassan N, Lightner C, Pulley J. ResearchMatch: A National Registry to Recruit Volunteers for Clinical Research. Acad Med 2012; Feb 87 (1) 66-73.
• 66 Ferranti JM, Gilbert W, McCall J, Shang H, Barros T, Horvath MM. The design and implementation of an open-source, data-driven cohort recruitment system: the Duke Integrated Subject Cohort and Enrollment Research Network (DISCERN). J Am Med Inform Assoc. 2011 Sep 23.
• 67 Pressler TR, Yen PY, Ding J, Liu J, Embi PJ, Payne PR. Computational challenges and human factors influencing the design and use of clinical research participant eligibility pre-screening tools. BMC Med Inform Decis Mak 2012; 12: 47.
• 68 Weng C, Tu SW, Sim I, Richesson R. Formal representation of eligibility criteria: a literature review. J Biomed Inform 2010; Jun 1 43 (3) 451-67.
• 69 Weng C, Wu X, Luo Z, Boland MR, Theodoratos D, Johnson SB. EliXR: an approach to eligibility criteria extraction and representation. J Am Med Inform Assoc 2011; Dec 16 18 (Suppl 1) i116-i24.
• 70 Hall A, Rode M, Pagnoux C, Yacyshyn E. Patient-Driven On-Line Survey on Granulomatosis with Polyangiitis. Arthritis Rheum. 2011 Nov 04 63. (Suppl 10) 2371.
• 71 Tweet MS, Gulati R, Aase LA, Hayes SN. Spontaneous Coronary Artery Dissection: A Disease-Specific, Social Networking Community-Initiated Study. Mayo Clinic Proceedings 2011; Sep 86 (9) 845-50.
• 72 Bellamy N, Wilson C, Hendrikz J, Whitehouse SL, Patel B, Dennison S. et al. Osteoarthritis Index delivered by mobile phone (m-WOMAC) is valid, reliable, and responsive. J Clin Epidemiol 2011; Mar 64 (2) 182-90.
• 73 Pulley J, Hassan N, Bernard G, Jirjis J, Schildcrout J, Robertson D. et al. Identifying unpredicted drug benefit through query of patient experiential knowledge: a proof of concept web-based system. Clin Transl Sci 2010; Jun 1 3 (3) 98-103.
• 74 Malin B, Benitez K, Masys D. Never too old for anonymity: a statistical standard for demographic data sharing via the HIPAA Privacy Rule. J Am Med Inform Assoc 2011; 18 (1) 3-10.
• 75 Clancy CM, Slutsky JR. Commentary: a progress report on AHRQ's Effective Health Care Program. Health Serv Res 2007; Oct 1 42 (5) xi-xix.
• 76 Collins FS. Reengineering translational science: the time is right. Sci Transl Med. 2011 Jul 06 3. (90) 90cm17.
• 77 Lauer MS, Collins FS. Using science to improve the nation's health system: NIH's commitment to comparative effectiveness research. JAMA 2010; Jun 2 303 (21) 2182-3.
• 78 Embi PJ, Tsevat J. Commentary: the relative research unit: providing incentives for clinician participation in research activities. Acad Med [Editorial]. 2012; Feb 87 (1) 11-4.
• 79 Hersh W, Jacko JA, Greenes R, Tan J, Janies D, Embi PJ. et al. Health-care hit or miss?. Nature 2011; Feb 17 470 (7334) 327-9.
• 80 DeMets DL, Califf RM. A historical perspective on clinical trials innovation and leadership: where have the academics gone?. JAMA [Historical Article] 2011; Mar 16 305 (7) 713-4.
• 81 Cantor MN. Translational informatics: an industry perspective. J Am Med Inform Assoc 2012; Mar 19 (2) 153-5.
• 82 Payne PRO, Embi PJ, Niland J. Foundational biomedical informatics research in the clinical and translational science era: a call to action. J Am Med Inform Assoc 2010; Nov 1 17 (6) 615-6.
• 83 Stead W, Searle J, Fessler H, Smith J, Shortliffe E. Biomedical Informatics: Changing What Physicians Need to Know and How They Learn. Acad Med. 2010 Aug 12.
• 84 Richesson RL, Andrews JE. Clinical research informatics. London; New York: Springer; 2012. Available from: http://dx.doi.org/10.1007/978-1-84882-448-5 http://proxy.ohiolink.edu:9099/login? url= http://dx.doi.org/10.1007/978-1-84882-448-5
• 85 Sarkar IN, Payne PR. The joint summits on translational science: crossing the translational chasm. J Biomed Inform 2011; Dec 44 Suppl 1 S1-2.
• 86 Payne PRO, Embi PJ, Kahn MG. Selected papers from the 2011 Summit on Clinical Research Informatics. J Biomed Inform [Editorial] 2011; Dec 44 Suppl 1 S54-5.
• 87 Calonge N. EDM forum supplement overview. Med Care 2012; Jul 50 Suppl S1-2.