Invited Commentary: The Use of Imperfect Data—Compromise or Compromising?

• Published in: American journal of epidemiology Vol. 167; no. 6; pp. 641 - 643
• Main Author: Howards, Penelope P.
• Format: Journal Article
• Language: English
• Published: United States Oxford University Press 15.03.2008; Oxford Publishing Limited (England)
• Subjects: Algorithms; Automation; Bias; bias (epidemiology); Clinical outcomes; computerized; Data Collection; Drug-Related Side Effects and Adverse Reactions; Epidemiology; Female; Gestational Age; Humans; Medical records; medical records systems; Online data bases; Perinatal Care; Pregnancy; pregnancy outcome; Time Factors; medical records systems, computerized; bias (epidemiology); pregnancy outcome; gestational age
• ISSN: 0002-9262; 1476-6256; 1476-6256
• DOI: 10.1093/aje/kwm368

Automated databases are appealing resources because they contain detailed data that are relatively accessible, but there are also critical gaps in the data available. Researchers may compromise by trying to fill those gaps with proxy variables, but how appropriate these surrogates are is rarely known. In this issue (Am J Epidemiol 2008;167:630–640), Toh et al. consider the effect of using two algorithms to estimate the timing of medication use during pregnancy in the absence of gestational-age data. Although the delivery-date algorithm has promising sensitivity and specificity, it is true under very specific conditions that seem unlikely to hold generally. Furthermore, it seems difficult to know a priori when those conditions do hold. There are times when using imperfect data is acceptable, but, at other times, the data are too imperfect to be helpful. Automated databases are certainly valuable, but they should be used with caution and where possible should be linked to databases that can fill the critical gaps.