Abstract

BackgroundThe measurement of progress in maternal and newborn health often relies on data provided by women in surveys on the quality of care they received. The majority of these indicators, however, including the widely tracked “skilled attendance at birth” indicator, have not been validated. We assess the validity of a large set of maternal and newborn health indicators that are included or have the potential to be included in population–based surveys.MethodsWe compare women’s reports of care received during labor and delivery in two Kenyan hospitals prior to discharge against a reference standard of direct observations by a trained third party (n = 662). We assessed individual–level reporting accuracy by quantifying the area under the receiver operating curve (AUC) and estimated population–level accuracy using the inflation factor (IF) for each indicator with sufficient numbers for analysis.FindingsFour of 41 indicators performed well on both validation criteria (AUC>0.70 and 0.75<IF<1.25). These were: main provider during delivery was a nurse/midwife, a support companion was present at birth, cesarean operation, and low birthweight infant (<2500 g). Twenty–one indicators met acceptable levels for one criterion only (11 for AUC; 9 for IF). The skilled birth attendance indicator met the IF criterion only.InterpretationFew indicators met both validation criteria, partly because many routine care interventions almost always occurred, and there was insufficient variation for robust analysis. Validity is influenced by whether the woman had a cesarean section, and by question wording. Low validity is associated with indicators related to the timing or sequence of events. The validity of maternal and newborn quality of care indicators should be assessed in a range of settings to refine these findings.

Highlights

  • The measurement of progress in maternal and newborn health often relies on data provided by women in surveys on the quality of care they received

  • To illustrate the implications of the inflation factor (IF) estimates for other contexts in which the true prevalence is different from our study setting, we model the estimated survey prevalence for select indicators across all possible coverage levels using the above equation [27]

  • That a small number of the initial list of 82 indicators met both validation criteria is partly due to the fact that many preventative care interventions almost always occurred, and there was insufficient variation for robust analysis

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Summary

Methods

We compare women’s reports of care received during labor and delivery in two Kenyan hospitals prior to discharge against a reference standard of direct observations by a trained third party (n = 662). According to the 2014 Kenya DHS, nationally, 61% of births in the five years preceding the survey were delivered in a health facility; in Kisumu and Kiambu districts the prevalence was 70% and 93%, respectively [16]. Fertility levels among women in the two districts are lower than the national rate, with the total fertility rate in Kisumu at 3.6 births per woman and in Kiambu at 2.7, compared with 3.9 nationally [16]. Data collection took place from July to September 2013. Participants included eligible women who underwent labor and delivery and were able to provide consent

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