Can epidemiology inform global health and development targets?

A quality assessment of Health Management Information System (HMIS) data for maternal and child health in Jimma Zone, Ethiopia

Health management information system (HMIS) data are important for guiding the attainment of health targets in low- and middle-income countries. However, the quality of HMIS data is often poor. High-quality information is especially important for populations experiencing high burdens of disease and mortality, such as pregnant women, newborns, and children. The purpose of this study was to assess the quality of maternal and child health (MCH) data collected through the Ethiopian Ministry of Health’s HMIS in three districts of Jimma Zone, Oromiya Region, Ethiopia over a 12-month period from July 2014 to June 2015. Considering data quality constructs from the World Health Organization’s data quality report card, we appraised the completeness, timeliness, and internal consistency of eight key MCH indicators collected for all the primary health care units (PHCUs) located within three districts of Jimma Zone (Gomma, Kersa and Seka Chekorsa). We further evaluated the agreement between MCH service coverage estimates from the HMIS and estimates obtained from a population-based cross-sectional survey conducted with 3,784 women who were pregnant in the year preceding the survey, using Pearson correlation coefficients, intraclass correlation coefficients (ICC), and Bland-Altman plots. We found that the completeness and timeliness of facility reporting were highest in Gomma (75% and 70%, respectively) and lowest in Kersa (34% and 32%, respectively), and observed very few zero/missing values and moderate/extreme outliers for each MCH indicator. We found that the reporting of MCH indicators improved over time for all PHCUs, however the internal consistency between MCH indicators was low for several PHCUs. We found poor agreement between MCH estimates obtained from the HMIS and the survey, indicating that the HMIS may over-report the coverage of key MCH services, namely, antenatal care, skilled birth attendance and postnatal care. The quality of MCH data within the HMIS at the zonal level in Jimma, Ethiopia, could be improved to inform MCH research and programmatic efforts.

Health information priorities for more effective implementation and monitoring of non-communicable disease programs in low- and middle-income countries: lessons from the Pacific

BACKGROUND

Non-communicable diseases (NCDs) place enormous burdens on individuals and health systems. While there has been significant global progress to guide the development of national NCD monitoring programs, many countries still struggle to adequately establish critical information systems to prioritise NCD control approaches.

DISCUSSION

In this paper, we use the recent experience of the Pacific as a case study to highlight four key lessons about prioritising strategies for health information system development for monitoring NCDs: first, NCD interventions must be chosen strategically, taking into account local disease burden and capacities; second, NCD monitoring efforts must align with those interventions so as to be capable of evaluating progress; third, in order to ensure efficiency and sustainability, NCD monitoring strategies must be integrated into existing health information systems; finally, countries should monitor the implementation of key policies to control food and tobacco industries. Prioritising NCD interventions to suit local needs is critical and should be accompanied by careful consideration of the most appropriate and feasible monitoring strategies to track and evaluate progress.