Adapting data management education to support clinical research projects in an academic medical center

Kevin B. Read

Abstract


Background: Librarians and researchers alike have long identified research data management (RDM) training as a need in biomedical research. Despite the wealth of libraries offering RDM education to their communities, clinical research is an area that has not been targeted. Clinical RDM (CRDM) is seen by its community as an essential part of the research process where established guidelines exist, yet educational initiatives in this area are unknown.

Case Presentation: Leveraging the author’s academic library’s experience supporting CRDM through informationist grants and REDCap training in our medical center, we developed a 1.5 hour CRDM workshop. This workshop was designed to use established CRDM guidelines in clinical research and address common questions asked by our community through the library’s existing data support program. The workshop was offered to the entire medical center 4 times between November 2017 and July 2018. This case study describes the development, implementation, and evaluation of this workshop.

Conclusions: The 4 workshops were well attended and well received by the medical center community, with 99% stating that they would recommend the class to others and 98% stating that they would use what they learned in their work. Attendees also articulated how they would implement the main competencies they learned from the workshop into their work. For the library, the effort to support CRDM has led to the coordination of a larger institutional collaborative training series to educate researchers on best practices with data, as well as the formation of institution-wide policy groups to address researcher challenges with CRDM, data transfer, and data sharing.

Keywords


Clinical Data Management; Education; REDCap; Clinical Research; Data Quality; Data Standards

Full Text:

PDF HTML

References


Anderson NR, Lee ES, Brockenbrough JS, Minie ME, Fuller S, Brinkley J, Tarczy-Hornoch P. Issues in biomedical research data management and analysis: needs and barriers. J Am Med Inform Assoc. 2007 Jul–Aug;14(4):478–88.

Wang X, Williams C, Liu ZH, Croghan J. Big data management challenges in health research—a literature review. Briefings Bioinform. 2017 Aug 7.

Barone L, Williams J, Micklos D. Unmet needs for analyzing biological big data: a survey of 704 NSF principal investigators. PLoS Comput Biol. 2017 Oct 19;13(10):e1005755. Corrected: PLoS Comput Biol. 2017 Nov 13;13(11):e1005858.

Johansson B, Fogelberg-Dahm M, Wadensten B. Evidence-based practice: the importance of education and leadership. J Nurs Manag. 2010 Jan;18(1):70–7.

Federer LM, Lu YL, Joubert DJ. Data literacy training needs of biomedical researchers. J Med Libr Assoc. 2016 Jan;104(1):52–7. DOI: http://dx.doi.org/10.3163/1536-5050.104.1.008.

Scaramozzino JM, Ramírez ML, McGaughey KJ. A study of faculty data curation behaviors and attitudes at a teaching-centered university. Coll Res Libr. 2012 Jul;73(4):349–65.

Carlson J, Johnston L, Westra B, Nichols M. Developing an approach for data management education: a report from the data information literacy project. Int J Digit Curation. 2013;8(1):204–17.

Macmillan D. Developing data literacy competencies to enhance faculty collaborations. LIBER Q. 2015;24(3):140–60.

Wittenberg J, Elings M. Building a research data management service at the University of California, Berkeley: a tale of collaboration. IFLA J. 2017 Mar;43(1):89–97.

Piorun ME, Kafel D, Leger-Hornby T, Najafi S, Martin ER, Colombo P, LaPelle N. Teaching research data management: an undergraduate/graduate curriculum. J eSci Libr. 2012;1(1):8.

Reisner BA, Vaughan KTL, Shorish YL. Making data management accessible in the undergraduate chemistry curriculum. J Chem Educ. 2014;91(11):1943–6.

Adamick J, Reznik-Zellen RC, Sheridan M. Data management training for graduate students at a large research university. J eSci Libr. 2013;1(3):8.

Fransson J, Lagunas PT, Kjellberg S, Toit MD. Developing integrated research data management support in close relation to doctoral students’ research practices. Proc Assoc Inf Sci Technol. 2016;53(1):1–4.

Clement R, Blau A, Abbaspour P, Gandour-Rood E. Team-based data management instruction at small liberal arts colleges. IFLA J. 2017 Mar;43(1):105–18.

Johnston L, Jeffryes J. Steal this idea: a library instructors’ guide to educating students in data management skills. Coll Res Libr News. 2014 Sep;75(8):431–4.

Johnston L, Lafferty M, Petsan B. Training researchers on data management: a scalable, cross-disciplinary approach. J eSci Libr. 2012;1(2):2.

Muilenburg J, Lebow M, Rich J. Lessons learned from a research data management pilot course at an academic library. J eSci Libr. 2014;3(1):8.

Southall J, Scutt C. Training for research data management at the Bodleian Libraries: national contexts and local implementation for researchers and librarians. New Rev Acad Libr. 2017;23(2–3):303–22.

Tammaro AM, Casarosa V, eds. Research data management in the curriculum: an interdisciplinary approach. Procedia Computer Science; 2014.

Verbakel E, Grootveld M. ‘Essentials 4 Data Support’: five years’ experience with data management training. IFLA J. 2016 Dec;42(4):278–83.

DeBose KG, Haugen I, Miller RK. Information literacy instruction programs: supporting the college of agriculture and life sciences community at Virginia Tech. Libr Trends. 2017 Winter;65(3):316–38.

Fong BL, Wang M. Required data management training for graduate students in an earth and environmental sciences department. J eSci Libr. 2015;4(1):3.

Hou CY. Meeting the needs of data management training: the federation of Earth Science Information Partners (ESIP) data management for scientists short course. Issues Sci Technol Libr. 2015 Spring;2015(80).

Thielen J, Hess AN. Advancing research data management in the social sciences: implementing instruction for education graduate students into a doctoral curriculum. Behav Soc Sci Libr. 2018:1–15.

Dressel WF. Research data management instruction for digital humanities. J eSci Libr. 2017;6(2):5.

Bruland P, Breil B, Fritz F, Dugas M. Interoperability in clinical research: from metadata registries to semantically annotated CDISC ODM. Studies Health Technol Inform. 2012;180:564–8.

Gaddale JR. Clinical data acquisition standards harmonization importance and benefits in clinical data management. Perspect Clin Res. 2015 Oct–Dec;6(4):179–83.

Krishnankutty B, Bellary S, Kumar NB, Moodahadu LS. Data management in clinical research: an overview. Indian J Pharm. 2012 Mar;44(2):168–72.

Leroux H, Metke-Jimenez A, Lawley MJ. Towards achieving semantic interoperability of clinical study data with FHIR. J Biomed Semantics. 2017 Sep 19;8(1):41.

Arthofer K, Girardi D. Data quality- and master data management—a hospital case. Stud Health Technol Inform. 2017;236:259–66.

Callahan T, Barnard J, Helmkamp L, Maertens J, Kahn M. Reporting data quality assessment results: identifying individual and organizational barriers and solutions. EGEMS (Washington, DC). 2017 Sep 4;5(1):16.

Houston L, Probst Y, Yu P, Martin A. Exploring data quality management within clinical trials. Appl Clin Inform. 2018 Jan;9(1):72–81.

Teunenbroek TV, Baker J, Dijkzeul A. Towards a more effective and efficient governance and regulation of nanomaterials. Particle Fibre Toxicol. 2017 Dec 19;14(1):54.

Ohmann C, Banzi R, Canham S, Battaglia S, Matei M, Ariyo C, Becnel L, Bierer B, Bowers S, Clivio L, Dias M, Druml C, Faure H, Fenner M, Galvez J, Ghersi D, Gluud C, Groves T, Houston P, Karam G, Kalra D, Knowles RL, Krleža-Jerić K, Kubiak C, Kuchinke W, Kush R, Lukkarinen A, Marques PS, Newbigging A, O’Callaghan J, Ravaud P, Schlünder I, Shanahan D, Sitter H, Spalding D, Tudur-Smith C, van Reusel P, van Veen EB, Visser GR, Wilson J, Demotes-Mainard J. Sharing and reuse of individual participant data from clinical trials: principles and recommendations. BMJ Open. 2017 Dec 14;7(12):e018647.

Polancich S, James DH, Miltner RS, Smith GL, Moneyham L. Building DNP essential skills in clinical data management and analysis. Nurse Educ. 2018 Jan/Feb;43(1):37–41.

Sirgo G, Esteban F, Gomez J, Moreno G, Rodriguez A, Blanch L, Guardiola J7, Gracia R, De Haro L, Bodí M. Validation of the ICU-DaMa tool for automatically extracting variables for minimum dataset and quality indicators: the importance of data quality assessment. Int J Med Inform. 2018 Apr;112:166–72.

Society for Clinical Data Management. Good clinical data management practices. The Society; 2017.

Sylvia M, Terhaar M. An approach to clinical data management for the doctor of nursing practice curriculum. J Prof Nurs. 2014 Jan–Feb;30(1):56–62.

Read KB, LaPolla FWZ, Tolea MI, Galvin JE, Surkis A. Improving data collection, documentation, and workflow in a dementia screening study. J Med Libr Assoc. 2017 Apr;105(2):160–66. DOI: http://dx.doi.org/10.5195/jmla.2017.221.

Read K, LaPolla FWZ. A new hat for librarians: providing REDCap support to establish the library as a central data hub. J Med Libr Assoc. 2018 Jan;106(1):120–6. DOI: http://dx.doi.org/10.5195/jmla.2018.327.

Data management for clinical research [course]. Coursera, Vanderbilt University; 2016.

Society for Clinical Data Management. Developing data management plans [course]. The Society; 2017.

Surkis A, LaPolla FWZ, Contaxis N, Read KB. Data Day to Day: building a community of expertise to address data skills gaps in an academic medical center. J Med Libr Assoc. 2017 Apr;105(2):185–91. DOI: http://dx.doi.org/10.5195/jmla.2017.35.

Stuckey H. The second step in data analysis: coding qualitative research data. J Soc Health Diabetes. 2015;3(1):7–10.

Bardyn TP, Patridge EF, Moore MT, Koh JJ. Health sciences libraries advancing collaborative clinical research data management in universities. J eSci Libr. 2018;7(2):4.




DOI: https://doi.org/10.5195/jmla.2019.580

Refbacks

  • There are currently no refbacks.




Copyright (c) 2019 Kevin B. Read

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.