Evaluation of data quality improvement interventions focusing on pregnancy outcome and perinatal mortality documentation by Health Surveillance Assistants in the Salima and Balaka districts of Malawi

data quality;mHealth;stillbirth;fetal death;early neonatal death;misclassification;community health worker;Malawi;SMS;adverse pregnancy outcomes;Public Health Studies

Joos, Olga HelenaMosley, W. Henry ;

Johns Hopkins University

关键词: data quality;    mHealth;    stillbirth;    fetal death;    early neonatal death;    misclassification;    community health worker;    Malawi;    SMS;    adverse pregnancy outcomes;    Public Health Studies;   

Others  :  https://jscholarship.library.jhu.edu/bitstream/handle/1774.2/39736/JOOS-DISSERTATION-2016.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: JOHNS HOPKINS DSpace Repository

【 摘 要 】

Perinatal mortality is a statistic that aggregates fetal deaths, commonly known as stillbirths, and early neonatal deaths. The emotional devastation of these events for women and families is compounded by socio-cultural beliefs and practices obscuring their existence in some societies and national health statistics. Community health workers engaged in pregnancy tracking and vital events documentation are in a position to capture these events if they are trained in correct event classification and supported in the data collection process. In Malawi, the Institute for International Programs supported community health workers, known as Health Surveillance Assistants (HSAs), in the monthly documentation of pregnancies, births, and deaths to estimate annual rates of under-five mortality. We implemented a data quality documentation training and data editor verification process to evaluate documentation of vital events, namely adverse pregnancy outcomes. We also implemented a cluster randomized mHealth intervention designed to improve Real-time Mortality Monitoring HSA documentation of pregnancies and pregnancy outcomes. We present the results of these two data quality evaluations in this dissertation.To evaluate the documentation of adverse pregnancy outcomes— induced abortions, miscarriages, stillbirths, and early neonatal deaths— we compared HSA reported adverse pregnancy outcomes against results from the data editor verification process. Classification of early pregnancy loss was poor in both districts, despite improving slightly in the post-training period. To evaluate the effectiveness of the mHealth intervention in improving documentation of pregnancy outcomes, we matched reported pregnancies with live births and adverse pregnancy outcomes. The mHealth interventions improved documentation of matched pregnancies in both treatment groups relative to the baseline period, yet improvements were not noted between groups during the intervention period. Until a fully functional civil registration and vital statistic system is implemented in Malawi, HSAs are a potential source of perinatal mortality data but need substantial support to meet high data quality standards. This level of support was not achieved through the data quality training or mHealth intervention. Further research should be conducted to identify the most effective trainings and mHealth applications to support community health worker documentation of pregnancies and pregnancy outcomes, with a strong focus on adverse pregnancy outcomes.