Improving immunisation through data for decision-making in Pacific Island Countries and Areas

Abstract

Data and the systems that generate information are the foundation of evidence-based decision-making. High-quality, fit-for-purpose data on immunisation system performance can drive decision-making and subsequent improvements in vaccination coverage. Yet, there is limited evidence that data are used in decision-making, especially in low-resource settings. Pacific Island Countries & Areas (PICs) comprise 21 Small Island Developing States that face unique challenges to delivering immunisation. There is a paucity of evidence on immunisation information systems in PICs, including the processes for generating immunisation data, the extent of immunisation data use, and the drivers and barriers to using data in decision-making. This research aimed to examine the role of data for decision-making to strengthen immunisation systems in PICs. It addressed 3 key questions: 1. How is immunisation system performance measured, and what is the relationship between immunisation performance in routine versus emergency contexts? 2. What data are most important to measure to improve immunisation in PICs? 3. How are immunisation data used in decision-making in PICs? To address the first question, I identified indicators from existing monitoring and evaluation resources measuring the performance of immunisation systems (Ch 2). I found over 600 indicators, implying a large burden of data collection and reporting for countries. I then examined the association between routine immunisation and COVID-19 vaccination coverage in Small Island Developing States through a quantitative analysis of immunisation performance indicators (Ch 3). I found that higher COVID-19 vaccination coverage was associated with sustaining pre pandemic routine immunisation coverage during the pandemic, introducing and sustaining new vaccines in national immunisation programs, and higher workforce density. To answer the second question, I conducted an expert elicitation study, asking immunisation and health information system experts across PICs to identify the most important indicators for immunisation decision-making (Ch 4). Although experts' preferences for indicators varied, some common factors influenced their preferences. Health system factors, roles and influence of various health system actors, and country-level factors like population size and distribution affected perceptions of the relevance of different indicators to decision-making and feasibility of obtaining these data. These findings suggest that contextualising immunisation performance measurement could lead to greater use of evidence in decision-making while reducing the burden of data collection and reporting. To address the third question, I conducted a qualitative study to examine how vaccination coverage data are used by decision-makers in Vanuatu, examining use of data from paper-based systems for routine immunisation and an electronic immunisation register (EIR) for COVID-19 vaccination (Ch 5). I found limited use of routine immunisation data, but clear examples of use of COVID-19 vaccination data to monitor program rollout, allocate resources and plan actions to deliver the program. While the EIR facilitated data use, systemic factors such as increased resourcing, improved data management and greater accountability fostered an enabling ecosystem where data were demanded and data-driven decision-making was expected.

This thesis highlights the complexity of factors influencing data use in PICs. The findings reaffirm the need to build and invest in strong health system foundations, especially workforce in PICs, where limited capacity constrains immunisation performance. Additionally, appropriate policies, management and supervision, and sufficient financial and technical resources are required to improve data generation and its use. Immunisation information systems that streamline data processes and focus on the most relevant data can drive improvements in overall immunisation system performance. Show more