Electronic data collection in epidemiological research

Summary

Objectives

This paper describes the use of Research Electronic Data Capture (REDCap) to conduct one of the follow-up waves of the 2004 Pelotas birth cohort. The aim is to point out the advantages and limitations of using this electronic data capture environment to collect data and control every step of a longitudinal epidemiological research, specially in terms of time savings and data quality.

Methods

We used REDCap as the main tool to support the conduction of a birth cohort follow-up. By exploiting several REDCap features, we managed to schedule assessments, collect data, and control the study workflow. To enhance data quality, we developed specific reports and field validations to depict inconsistencies in real time.

Results

Using REDCap it was possible to investigate more variables without significant increases on the data collection time, when comparing to a previous birth cohort follow-up. In addition, better data quality was achieved since negligible out of range errors and no validation or missing inconsistencies were identified after applying over 7,000 interviews.

Conclusions

Adopting electronic data capture solutions, such as REDCap, in epidemiological research can bring several advantages over traditional paper-based data collection methods. In favor of improving their features, more research groups should migrate from paper to electronic-based epidemiological research.

Citation: Blumenberg C, Barros AJD. Electronic data collection in epidemiological research: The use of REDCap in the Pelotas birth cohorts

 

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Keywords

Epidemiology - public health informatics - electronic data capture - medical informatics - translational research

 

 

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Conflict of Interest

The authors declare that they have no conflicts of interest in the research.

• References

• 1 Grimes DA, Schulz KF. Descriptive studies: What they can and cannot do. Lancet 2002; 359 9301 145-149.
• 2 Magnuson JA, O’Carroll PW. Introduction to Public Health Informatics. In: Magnuson JA, Fu PC. editors. Public Health Informatics and Information Systems. London: Springer; 2003: 3-15.
• 3 Grimes DA, Schulz KF. Cohort studies: marching towards outcomes. Lancet 2002; 359 9303 341-345.
• 4 Barros AJD, Santos IS, Matijasevich A, Araújo CL, Gigante DP, Menezes AMB, Horta BL, Tomasi E, Victora CG, Barros FC. Methods used in the 1982, 1993, and 2004 birth cohort studies from Pelotas, Rio Grande do Sul State, Brazil, and a description of the socioeconomic conditions of participants’ families. Cad Saude Publica 2008; 24 (Suppl. 03) S371-S380.
• 5 Welker JA. Implementation of electronic data capture systems: barriers and solutions. Contemp Clin Trials 2007; 28 (03) 329-336.
• 6 Hesse BW. Public Health Informatics. In: Gibbons MC. editor. eHealth Solut. Healthc. Disparities. New York: Springer; 2008: 109-26.
• 7 Sarkies MN, Bowles K-A, Skinner EH, Mitchell D, Haas R, Ho M, Salter K, May K, Markham D, O’Brian L, Plumb S, Haines TP. Data Collection Methods in Health Services Research: Hospital Length of Stay and Discharge Destination. Appl Clin Inform 2015; 06 (01) 96-109.
• 8 Cornman JC, Glei DA, Goldman N, Chang M-C, Lin H-S, Chuang Y-L, Hurng B-S, Lin Y-H, Lin S-H, Liu I-W, Liu H-Y, Weinstein M. Cohort Profile: The Social Environment and Biomarkers of Aging Study (SEBAS) in Taiwan. Int J Epidemiol 2016; 45 (01) 54-63.
• 9 Schooling CM, Chan WM, Leung SL, Lam TH, Lee SY, Shen C, Leung JY, Leung GM. Cohort Profile: Hong Kong Department of Health Elderly Health Service Cohort. Int. J. Epidemiol 2016; 45 (01) 64-72.
• 10 Wahabi H, Fayed A, Esmaeil S, Alzeidan R, Elawad M, Tabassum R, Hansoti S, Magzoup ME, Al-Kadri H, Elsherif E, Al-Mandil H, Al-Shaikh G, Zakaria N. Riyadh Mother and Baby Multicenter Cohort Study: The Cohort Profile. PLoS One 2016; 11 (03) e0150297.
• 11 Couper M. Web Surveys: A Review of Issues and Approaches. Public Opin Quart 2000; 64 (04) 464-494.
• 12 Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)-A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009; 42 (02) 377-381.
• 13 REDCap. Nashville: Research Electronic Data Capture. [updated 2016 May; cited 2016 Apr 17].
• 14 Santos IS, Barros AJD, Matijasevich A, Zanini R, Chrestani MACesar, Camargo-Figuera FA, Oliveira IO, Barros FC, Victora CG. Cohort Profile Update: 2004 Pelotas (Brazil) Birth Cohort Study. Body composition, mental health and genetic assessment at the 6 years follow-up. Int J Epidemiol 2014; 43 (05) 1437-1437f.
• 15 Gonçalves H, Assunção MC, Wehrmeister FC, Oliveira IO, Barros FC, Victora CG, Hallal PC, Menezes AMB. Cohort profile update: The 1993 Pelotas (Brazil) birth cohort follow-up visits in adolescence. Int J Epidemiol 2014; 43 (04) 1082-1088.
• 16 Walther B, Hossin S, Townend J, Abernethy N, Parker D, Jeffries D. Comparison of electronic data capture (EDC) with the standard data capture method for clinical trial data. PLoS One 2011; 06 (09) e25348.
• 17 Bart T. Comparison of Electronic Data Capture with Paper Data Collection-Is there really An Advantage?. Bus Brief Pharmatech. 2003: 1-4.
• 18 Pavlović I, Kern T, Miklavčič D. Comparison of paper-based and electronic data collection process in clinical trials: Costs simulation study. Contemp Clin Trials 2009; 30 (04) 300-316.
• 19 van den Berg MH, Overbeek A, van der Pal HJ, Versluys AB, Bresters D, van Leeuwen FE, Lambalk CB, Kaspers GJL, van Dulmen-den Broeder E. Using web-based and paper-based questionnaires for collecting data on fertility issues among female childhood cancer survivors: differences in response characteristics. J Med Internet Res 2011; 13 (03) e76.
• 20 Klipin M, Mare I, Hazelhurst S, Kramer B. The process of installing REDCap, a web based database supporting biomedical research: the first year. Appl Clin Inform 2014; 05 (04) 916-929.