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Cluster-based studies involving aggregate units such as hospitals or medical practices are increasingly being used in healthcare evaluation. An important characteristic of such studies is the presence of intracluster correlation, typically quantified by the intracluster correlation coefficient (ICC). Sample size calculations for cluster-based studies need to account for the ICC, or risk underestimating the sample size required to yield the desired levels of power and significance. In this article, we present values for ICCs that were obtained from data on 97,095 pregnancies and 98,072 births taking place in a representative sample of 120 hospitals in eight Latin American countries. We present ICCs for 86 variables measured on mothers and newborns from pregnancy to the time of hospital discharge, including 'process variables' representing actual medical care received for each mother and newborn. Process variables are of primary interest in the field of implementation research. We found that overall, ICCs ranged from a minimum of 0.0003 to a maximum of 0.563 (median 0.067). For maternal and newborn outcome variables, the median ICCs were 0.011 (interquartile range 0.007-0.037) and 0.054 (interquartile range 0.013-0.075) respectively; however, for process variables, the median was 0.161 (interquartile range 0.072-0.328). Thus, we confirm previous findings that process variables tend to have higher ICCs than outcome variables. We demonstrate that ICCs generally tend to increase with higher prevalences (close to 0.5). These results can help researchers calculate the required sample size for future research studies in maternal and perinatal health.
Taljaard et al. (Wed,) studied this question.