"What gets measured better gets done better": The landscape of validation of global maternal and newborn health indicators through key informant interviews

Background A large number of indicators are currently used to monitor the state of maternal and newborn health, including those capturing dimensions of health system and input, care access and availability, care quality and safety, coverage and outcomes, and impact. Validity of these indicators is a key issue in the process of assessing indicator performance and suitability. This paper aims to understand the meaning of indicator validity in the field of maternal and newborn health, and to identify key recommendations for future research. Methods This qualitative study used purposive sampling to identify key informants until thematic saturation was achieved. We interviewed 32 respondents from a variety of backgrounds using semi-structured interviews covering five themes: the meaning of indicator validity, methodological approaches to assessing validity, acceptable levels of indicator validity, gaps in validation research, and recommendations for addressing these gaps. Interview transcripts were analysed data using thematic content approach. Results Three conceptually different definitions of indicator validity were described by respondents. They considered indicator validity to encompass meaning and potential to spur action, going beyond diagnostic validity. Indicator validation was seen as an ongoing process of building and synthesising a wide range of evidence rather than a one-size-fits-all cut-off in diagnostic validity tests. Gaps identified included assessing validity of indicators of quality of care and indicators based on facility-level data, as well as expanding studies to a broader range of global settings. The key recommendation was to develop a coordinated approach to summarising and evaluating research on indicator validity, including capacity building in appraising and communicating the available evidence for country-specific needs. Conclusion The findings will inform future recommendations around indicator testing and validation.