Abstract
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.
Highlights
As a comprehensive, disaggregated and comparable source of information about health services in low and middle-income countries, health management information systems (HMIS) have the strong potential to act as the cornerstone for effective policy decision making[1,2]
We further evaluated the agreement between maternal and child health (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
Maternal and child health indicators. In this data quality assessment, we examined several key maternal health services and immunization coverage indicators recommended by the World Health Organization (WHO) [23], including: antenatal care first (ANC1) and fourth (ANC4) visit coverage; deliveries attended by a skilled birth attendant (SBA) in health facilities; access to early postnatal care (PNC); and, infant receipt of Diphtheria, Tetanus, Pertussis vaccine first (DTP1) and third (DTP3) dose
Summary
As a comprehensive, disaggregated and comparable source of information about health services in low and middle-income countries, health management information systems (HMIS) have the strong potential to act as the cornerstone for effective policy decision making[1,2]. Numerous issues exist related to the completeness, timeliness, and accuracy of HMIS data [3,4,5,6,7,8,9,10,11,12,13], resulting in the tendency for countries and global health initiatives to rely on indicators measured through population-based surveys, such as the Demographic Health Survey and Multiple Indicator Cluster Survey These surveys, do not provide continuous estimates of population-level indicators given their cross-sectional nature [2,11]. As part of the Federal Ministry of Health (FMoH) “One Plan, One Budget & One Report” policy, Ethiopia contracted the consulting firm John Snow, Inc in the years 2006–2007 to assess and redesign its HMIS The aim of this effort was to improve the management and optimum use of resources for making timely decisions and promoting effective health care system delivery [14]. Following the 2006 reform, another assessment in 2009–2010 highlighted that the HMIS remained “cumbersome and fragmented” [14], with persisting poor quality of data and inadequate skills for collecting, analyzing and interpreting the information among the health care staff at the lowest levels of the health system [14]
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