The Clinical Research Environment

  • Philip R. O. PayneEmail author
Part of the Health Informatics book series (HI)


The conduct of clinical research is a data- and information-intensive endeavor, involving a variety of stakeholders spanning a spectrum from patients to providers to private sector entities to governmental policymakers. Increasingly, the modern clinical research environment relies on the use of informatics tools and methods, in order to address such diverse and challenging needs. In this chapter, we introduce the major stakeholders, activities, and use cases for informatics tools and methods that characterize the clinical research environment. This includes an overview of the ways in which informatics-based approaches influence the design of clinical studies, ensuing clinical research workflow, and the dissemination of evidence and knowledge generated during such activities. Throughout this review, we will provide a number of exemplary linkages to core biomedical informatics challenges and opportunities and the foundational theories and frameworks underlying such issues. Finally, this chapter places the preceding review in the context of a number of national-scale initiatives that seek to address such needs and requirements while advancing the frontiers of discovery science and precision medicine.


Clinical research funding Clinical research design Clinical research workflow Clinical research data management Data sharing Discovery science Precision medicine 


  1. 1.
    Embi PJ, Payne PR. Clinical research informatics: challenges, opportunities and definition for an emerging domain. J Am Med Inform Assoc. 2009;16(3):316–27.CrossRefGoogle Scholar
  2. 2.
    Embi PJ, Payne PR. Advancing methodologies in Clinical Research Informatics (CRI). J Biomed Inform. 2014;52(C):1–3.CrossRefGoogle Scholar
  3. 3.
    Johnson SB, Farach FJ, Pelphrey K, Rozenblit L. Data management in clinical research: synthesizing stakeholder perspectives. J Biomed Inform. 2016;60:286–93.CrossRefGoogle Scholar
  4. 4.
    Kahn MG, Weng C. Clinical research informatics: a conceptual perspective. J Am Med Inform Assoc. 2012;19(e1):e36–42.CrossRefGoogle Scholar
  5. 5.
    Payne PR, Pressler TR, Sarkar IN, Lussier Y. People, organizational, and leadership factors impacting informatics support for clinical and translational research. BMC Med Inform Decis Mak. 2013;13(1):20.CrossRefGoogle Scholar
  6. 6.
    Weng C, Kahn M. Clinical research informatics for big data and precision medicine. IMIA Yearb. 2016;(1):211–8.Google Scholar
  7. 7.
    Embi PJ, Kaufman SE, Payne PR. Biomedical informatics and outcomes research. Circulation. 2009;120(23):2393–9.CrossRefGoogle Scholar
  8. 8.
    Goldenberg NA, Daniels SR, Mourani PM, Hamblin F, Stowe A, Powell S, et al. Enhanced infrastructure for optimizing the design and execution of clinical trials and longitudinal cohort studies in the era of precision medicine. J Pediatr. 2016;171:300–6. e2.CrossRefGoogle Scholar
  9. 9.
    Prokscha S. Practical guide to clinical data management. Boca Raton: CRC Press; 2011.Google Scholar
  10. 10.
    Richesson R, Horvath M, Rusincovitch S. Clinical research informatics and electronic health record data. Yearb Med Inform. 2014;9(1):215.PubMedPubMedCentralGoogle Scholar
  11. 11.
    Saad ED, Paoletti X, Burzykowski T, Buyse M. Precision medicine needs randomized clinical trials. Nat Rev Clin Oncol. 2017;14(5):317–23.CrossRefGoogle Scholar
  12. 12.
    Nelson EC, Dixon-Woods M, Batalden PB, Homa K, Van Citters AD, Morgan TS, et al. Patient focused registries can improve health, care, and science. BMJ. 2016;354:i3319.CrossRefGoogle Scholar
  13. 13.
    Pencina MJ, Peterson ED. Moving from clinical trials to precision medicine: the role for predictive modeling. JAMA. 2016;315(16):1713–4.CrossRefGoogle Scholar
  14. 14.
    Friedman LM, Furberg C, DeMets DL, Reboussin DM, Granger CB. Fundamentals of clinical trials. Cham: Springer; 1998.CrossRefGoogle Scholar
  15. 15.
    Hulley SB, Cummings SR, Browner WS, Grady DG, Newman TB. Designing clinical research. Philadelphia: Lippincott Williams & Wilkins; 2013.Google Scholar
  16. 16.
    Brightling CE. Clinical trial research in focus: do trials prepare us to deliver precision medicine in those with severe asthma? Lancet Respir Med. 2017;5(2):92–5.CrossRefGoogle Scholar
  17. 17.
    Browner WS. Publishing and presenting clinical research. Philadelphia: Lippincott Williams & Wilkins; 2012.Google Scholar
  18. 18.
    Vicini P, Fields O, Lai E, Litwack E, Martin AM, Morgan T, et al. Precision medicine in the age of big data: the present and future role of large-scale unbiased sequencing in drug discovery and development. Clin Pharmacol Ther. 2016;99(2):198–207.CrossRefGoogle Scholar
  19. 19.
    Korn EL, Freidlin B. Adaptive clinical trials: advantages and disadvantages of various adaptive design elements. JNCI J Natl Cancer Inst. 2017;109(6):djx013.CrossRefGoogle Scholar
  20. 20.
    Embi PJ, Payne PR. Evidence generating medicine: redefining the research-practice relationship to complete the evidence cycle. Med Care. 2013;51:S87–91.CrossRefGoogle Scholar
  21. 21.
    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;5(3):281–4.CrossRefGoogle Scholar
  22. 22.
    Mandel JC, Kreda DA, Mandl KD, Kohane IS, Ramoni RB. SMART on FHIR: a standards-based, interoperable apps platform for electronic health records. J Am Med Inform Assoc. 2016;23(5):899–908.CrossRefGoogle Scholar
  23. 23.
    Mandl KD, Mandel JC, Kohane IS. Driving innovation in health systems through an apps-based information economy. Cell Syst. 2015;1(1):8–13.CrossRefGoogle Scholar
  24. 24.
    Chambers DA, Feero WG, Khoury MJ. Convergence of implementation science, precision medicine, and the learning health care system: a new model for biomedical research. JAMA. 2016;315(18):1941–2.CrossRefGoogle Scholar
  25. 25.
    Embi PJ. Future directions in clinical research informatics. Clinical research informatics. New York: Springer; 2012. p. 409–16.Google Scholar
  26. 26.
    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;53(4):192–201.CrossRefGoogle Scholar
  27. 27.
    Patel VL, Arocha JF, Kaufman DR. A primer on aspects of cognition for medical informatics. J Am Med Inform Assoc. 2001;8(4):324–43.CrossRefGoogle Scholar
  28. 28.
    Zhang J, Patel VL. Distributed cognition, representation, and affordance. Pragmat Cogn. 2006;14(2):333–41.CrossRefGoogle Scholar
  29. 29.
    Payne PR. Advancing user experience research to facilitate and enable patient-centered research: current state and future directions. eGEMs. 2013;1(1):1026.CrossRefGoogle Scholar
  30. 30.
    Ashley EA. Towards precision medicine. Nat Rev Genet. 2016;17(9):507–22.CrossRefGoogle Scholar
  31. 31.
    Hunter DJ. Uncertainty in the era of precision medicine. N Engl J Med. 2016;375(8):711–3.CrossRefGoogle Scholar
  32. 32.
    Tenenbaum JD, Avillach P, Benham-Hutchins M, Breitenstein MK, Crowgey EL, Hoffman MA, et al. An informatics research agenda to support precision medicine: seven key areas. J Am Med Inform Assoc. 2016;23(4):791–5.CrossRefGoogle Scholar
  33. 33.
    Collins FS, Varmus H. A new initiative on precision medicine. N Engl J Med. 2015;372(9):793–5.CrossRefGoogle Scholar
  34. 34.
    Sankar PL, Parker LS. The precision medicine initiative’s all of us research program: an agenda for research on its ethical, legal, and social issues. Genet Med. 2017;19(7):743.CrossRefGoogle Scholar
  35. 35.
    Ekins S. Pharmaceutical and biomedical project management in a changing global environment. Hoboken: Wiley; 2011.Google Scholar

Copyright information

© Springer International Publishing 2019

Authors and Affiliations

  1. 1.Institute for Informatics (I2)Washington University in St. Louis School of MedicineSt. LouisUSA

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