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Journal of Research in Nursing
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Data quality management: an example in caregiver research

Marie-Luise Friedemann

College of Nursing and Health Sciences, Florida International University, Florida, friedemm{at}fiu.edu

Carlos Mayorga

Institute and researchers in South Florida

Frederick L. Newman

Robert Stempel College of Public Health, Florida International University, Florida

The purpose of this paper is to assist nurse researchers around the world in addressing data quality issues by guiding them through an example of a complex multicultural study of caregivers who take care of elders in their home. Using data flow diagrams for visualization, methods of data quality management are outlined in the stages of subject recruitment, data gathering, and data monitoring. Various strategies are used to improve the quality of such data as the sample, information on consent forms, raw interview data, and the electronic data file. These strategies are aimed at avoiding various sources of human error, error in sampling, non-response and coverage error, as well as error of measurement and processing. Ultimately, this exemplar demonstrates an approach to realistic decision making and may offer nurse researchers incentives for discussion of their own data quality plans. Since immigrant population groups are expanding in many countries across the world, nurse researchers who seek to include such ethnic groups in their studies may find the multiethnic considerations included in the discussion of additional value.

Journal of Research in Nursing, Vol. 12, No. 4, 333-344 (2007)
DOI: 10.1177/1070729781744987
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