Data Quality: A Systematic Review of the Biosurveillance Literature

Authors

  • Tera Reynolds International Society for Disease Surveillance
  • Ian Painter University of Washington
  • Laura Streichert International Society for Disease Surveillance

DOI:

https://doi.org/10.5210/ojphi.v5i1.4376

Abstract

A literature review of data quality issues highlights how the quality of health data has been discussed in the biosurveillance literature and frames it in relation to the broader data quality (DQ) field. Results of the literature review include: completeness as the most commonly measured dimension of DQ; methods for regular DQ monitoring and occasional evaluation; various methods of improving data quality; and communication with the data entry personnel as the most common preventative step. The results suggest that developing a DQ program could facilitate understanding the sources of poor DQ; recognizing DQ problems; and improving DQ for improved efficiency and effectiveness of biosurveillance systems.

Author Biography

Tera Reynolds, International Society for Disease Surveillance

Tera Reynolds joined ISDS in 2011. Prior to joining ISDS, she was a Peace Corps volunteer in South Africa. In this role, she worked with local teachers and community leaders to identify community needs and develop projects to address these needs. Ms. Reynolds also has experience in health communication and education and data analysis. She earned a BA in Biology from Lawrence University and a MPH from Boston University School of Public Health.

Downloads

Published

2013-03-21

How to Cite

Reynolds, T., Painter, I., & Streichert, L. (2013). Data Quality: A Systematic Review of the Biosurveillance Literature. Online Journal of Public Health Informatics, 5(1). https://doi.org/10.5210/ojphi.v5i1.4376

Issue

Section

Oral Presentations: Data Quality and Underlying Patterns in Data Streams