Measurement and accountability for maternal, newborn and child health: fit for 2030?

Added to this mix is the global push to use modelled estimates (predictions) for programme monitoring when real data in real time is better fit for purpose.4 The various data platforms need to be rationalised, core indicator sets contextualised, and the culture of data use for decision making strengthened at different levels of health systems. Realising the gains available from the proliferation of guidance needs actors at multiple levels to have the capacity, motivation, incentive and confidence to use data and not be overwhelmed by its complexity. [...]making data more relevant will need more investment in institutions and people. Taking the example of effective coverage measurement, multiple dimensions of healthcare quality have been integrated in mainstream measurement guidance,6 digital tools have been developed, methods tested for linking relevant data sources and some engagement in countries undertaken to pressure test these innovations. [...]the coverage of healthcare for women and children is increasing and disparities are narrowing in many settings.7 But despite wide-spread description, the same types of inequalities often persist.