PhD defence Jill Molenaar

Supervisors

• Prof. dr; Lenka Benova (ITM)

• Prof. dr. Josefien van Olmen (University of Antwerp)

• Prof. dr. Andrea Pembe ((Muhimbili University of Health and Allied Sciences, Tanzania/Karolinska Institute, Sweden)

• Prof. dr. Claudia Hanson (Karolinska Institute, Sweden)

Summary

We have more data on maternal and newborn health (MNH) than ever before. Much of what we know about the health of women and babies around the time of childbirth in low- and middle-income countries (LMICs) comes from large survey studies, conducted every few years, that ask thousands of women about their pregnancies and births. More and more, we are also relying on data collected routinely. These are data recorded by healthcare workers (HCWs) about the health status of women and babies and about the care they receive. The ambition is that these data tell us how mothers and newborns are faring so that we can focus our efforts to keep improving their health.

MNH data are not neutral. Behind every number is a person who recorded it, and a system that decided it mattered to capture that information. MNH data influence how HCWs are supervised and judged, how money is allocated, and how care is provided. This thesis asks what the MNH measurement system looks like from the inside: how global measurement priorities are experienced by the HCWs, managers, and policymakers responsible for making them work. It focuses specifically on Tanzania, alongside research at the international level.

The research in Tanzania involved observations and interviews with people across the health system, ranging from HCWs in hospital labour wards to managers at district and regional level, and national-level policymakers. Starting from the labour ward, the research highlights the challenges HCWs face in recording data in multiple paper registers and digital systems. Although new digital systems are helpful, they do not take away the resource shortages and time constraints which make it difficult to produce accurate, timely data. The research also shows that many HCWs feel the data are not meant for them. When information flows upward to managers and donors without returning anything useful, HCWs document for reporting purposes only. And when linked to top-down targets and fear of blame, data become ‘political things’ which are sometimes strategically handled or manipulated as a form of self-protection. These dynamics undermine the accuracy of the data and their usefulness to improve care. The research also shows that when it comes to understanding the quality of the health services provided to women and newborns, data only ever tell part of the story. Routine data systems can capture how many women gave birth and whether certain procedures were carried out, but detailed information about care processes and women’s experience of care are challenging to capture in routine health data.

The research also included observations and interviews at the international level with the technical experts, international agencies and donors who shape which indicators matter and what countries should report on. This highlighted how the ambition to measure more and more has resulted in long lists of indicators, placing a heavy burden on already stretched health systems. The fundamental purpose of global measurement – who it is really for – repeatedly came into question. Global data systems have largely been built to give donors and international agencies evidence that progress is made and that their money is well spent, rather than to help local teams improve healthcare. Recent cuts to major international data programmes showed just how fragile this system is.

What connects the labour ward in Mtwara to international meeting rooms is a consistent finding: data travel readily upward, while the people capturing data closest to patients are least supported to use these data. This thesis shows how this is the result of measurement systems built around the information needs of distant decision-makers, rather than around the needs of people close to care provision. Changing this requires a different starting point. Health information systems should be designed primarily to be relevant for HCWs and local leaders, not as an afterthought. Investment should go into data that stay local and support local decisions, even if they never appear in a global report. And any investment in collecting data should be matched by equal investment in helping people understand and act on data. Ultimately, data about women and newborns should be useful for the people caring for women and newborns. A health system that learns from itself starts there.