This study presents a large number of intracluster correlation coefficients whose values can be considered low (close to zero) in most variables, showing intracluster heterogeneity.
The greater ICC values were found in process variables, especially management in spontaneous preterm labor conditions, as corticosteroids use, Group B streptococcus screening, use of tocolytic agents and use of antibiotic. Indeed, the mean ICC value for these variables was 10 times higher than the mean ICC of the study. The variable with the highest ICC was “corticosteroids – betamethasone”, with a value of 0.965. The prevalence of this variable was 85%, showing a high degree of homogeneity in this management for preterm labor. These findings are in accordance with the literature that describes ICC values generally higher for variables related to process compared to those variables related to outcome [15, 16].
In the field of maternal and perinatal healthcare, Taljaard et al. calculated ICC values based on data obtained from secondary/tertiary services . Comparing with our study, they found an overall median ICC of 0.067 versus 0.028. For maternal and newborn outcome variables, their median ICCs was 0.011 (versus 0.014), and 0.054 (versus 0.041), respectively. The findings of those investigators showed that, for variables associated to process, ICC values tend to be > 0.07. The present findings are in agreement with this observation.
Pagel et al. estimated ICC for a range of outcomes using data from five community-based clusters randomized controlled trials in three low-income countries. Estimated ICC values for mortality outcomes were lower than those for process outcomes, with narrower confidence intervals throughout for trials with larger number of clusters.
All comparisons show that the smaller the cluster size, the higher the ICC and the opposite occurs regarding the prevalence of the condition. Estimates of intracluster correlation are much less reliable for rare outcomes and the size of the cluster had a greater impact than the number of clusters on the reliability of estimates for rare outcomes .
Furthermore, higher healthcare levels tend to increase the degree of homogeneity [18, 19]. The size of ICC increases if the ICC represents data from secondary rather than primary care. This may be a reflection of the underlying heterogeneity of the datasets under consideration as the conditions represented across the different datasets were diverse. Although numerically small (average 0.01), such differences can have a substantial effect on sample size, even when the average of cluster is small . The clusters in this study are secondary and tertiary hospitals, most of them are teaching hospitals, with the majority of procedures performed in conformity with evidence-based healthcare protocols.
Stratified randomization had the effect of reducing estimates of cluster correlation . However, in the same way that in Brazilian Network for Surveillance of Severe Maternal Morbidity Study , which found ICC values close to zero, the selection of clusters did not performed stratification by region. The distribution of centers in this study, with almost half located in southeast region, is in accordance with the actual distribution of healthcare institutions and the proportionality of births per region in the country [21, 22].
The large number of intracluster correlation coefficients presented in this study, considered low (close to zero) in most of variables, can probably be seen as a good parameter of variance for calculating sample size in new studies in the field of perinatal and maternal health .
We can, however, to identify some possible limitations of the study, including the fact that we used a non-probabilistic sample from the centers (hospitals). Therefore, strictly speaking, the findings cannot be generalized to other populations. However, the majority of hospitals included in the study was third level referral hospitals taking care of high risk pregnancies and preterm babies. Probably the results would be applicable to other centers with such characteristics, irrespective of being private or public, especially in middle income countries like Brazil.