Prior studies have suggested that obstetrical (OB) ultrasound in low- and middle-income countries has aided in detection of high-risk conditions, which in turn could improve OB management. We are participating in a cluster-randomized clinical trial of OB ultrasound, which is designed to assess the effect of basic OB ultrasound on maternal mortality, fetal mortality, neonatal mortality, and maternal near-miss in 5 low-income countries. We designed a 2-week course in basic OB ultrasound, followed by 12 weeks of oversight, to train health care professionals with no prior ultrasound experience to perform basic OB ultrasound to screen for high-risk pregnancies. All patients with high-risk pregnancies identified by the trainees were referred to higher-level health facilities where fully trained sonographers confirmed the diagnoses before any actions were taken. Although there have been several published studies on basic OB ultrasound training courses for health care workers in low- and middle-income countries, quality control reporting has been limited. The purpose of this study is to report on quality control results of these trainees. Health care workers trained in similar courses could have an adjunctive role in ultrasound screening for high-risk OB conditions where access to care is limited. After completion of the ultrasound course, 41 trainees in 5 countries performed 3801 ultrasound examinations during a 12-week pilot period. Each examination was reviewed by ultrasound trainers for errors in scanning parameters and errors in diagnosis, using predetermined criteria. Of the 32,480 images comprising the 3801 examinations, 94.8% were rated as satisfactory by the reviewers. There was 99.4% concordance between trainee and reviewer ultrasound diagnosis. The results suggest that trained health care workers could play a role in ultrasound screening for high-risk OB conditions.
BACKGROUND: To describe quantitative data quality monitoring and performance metrics adopted by the Global Network´s (GN) Maternal Newborn Health Registry (MNHR), a maternal and perinatal population-based registry (MPPBR) based in low and middle income countries (LMICs). METHODS: Ongoing prospective, population-based data on all pregnancy outcomes within defined geographical locations participating in the GN have been collected since 2008. Data quality metrics were defined and are implemented at the cluster, site and the central level to ensure data quality. Quantitative performance metrics are described for data collected between 2010 and 2013. RESULTS: Delivery outcome rates over 95% illustrate that all sites are successful in following patients from pregnancy through delivery. Examples of specific performance metric reports illustrate how both the metrics and reporting process are used to identify cluster-level and site-level quality issues and illustrate how those metrics track over time. Other summary reports (e.g. the increasing proportion of measured birth weight compared to estimated and missing birth weight) illustrate how a site has improved quality over time. CONCLUSION: High quality MPPBRs such as the MNHR provide key information on pregnancy outcomes to local and international health officials where civil registration systems are lacking. The MNHR has measures in place to monitor data collection procedures and improve the quality of data collected. Sites have increasingly achieved acceptable values of performance metrics over time, indicating improvements in data quality, but the quality control program must continue to evolve to optimize the use of the MNHR to assess the impact of community interventions in research protocols in pregnancy and perinatal health. ; Fil: Goudar, Shivaprasad S. KLE University. Jawaharlal Nehru Medical College; India ; Fil: Stolka, Kristen B. Research Triangle Institute International; Estados Unidos ; Fil: Koso Thomas, Marion. Eunice Kennedy Shriver National Institute of Child Health and Human Development; Estados Unidos ; Fil: Honnungar, Narayan V. KLE University. Jawaharlal Nehru Medical College; India ; Fil: Mastiholi, Shivanand C. KLE University. Jawaharlal Nehru Medical College; India ; Fil: Ramadurg, Umesh Y. S. Nijalingappa Medical College; India ; Fil: Dhaded, Sangappa M. KLE University. Jawaharlal Nehru Medical College; India ; Fil: Pasha, Omrana. Aga Khan University; Pakistán ; Fil: Patel, Archana. Indira Gandhi Government Medical College and Lata Medical Research Foundation; India ; Fil: Esamai, Fabian. University School of Medicine; Kenia ; Fil: Chomba, Elwyn. University of Zambia; Zambia ; Fil: Garces, Ana. Universidad de San Carlos; Guatemala ; Fil: Althabe, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto de Efectividad Clínica y Sanitaria; Argentina ; Fil: Carlo, Waldemar A. University of Alabama at Birmingahm; Estados Unidos ; Fil: Goldenberg, Robert L. Columbia University; Estados Unidos ; Fil: Hibberd, Patricia L. Massachusetts General Hospital for Children; Estados Unidos ; Fil: Liechty, Edward A. Indiana University; Estados Unidos ; Fil: Krebs, Nancy F. University of Colorado School of Medicine; Estados Unidos ; Fil: Hambidge, Michael K. University of Colorado School of Medicine; Estados Unidos ; Fil: Moore, Janet L. Research Triangle Institute International; Estados Unidos ; Fil: Wallace, Dennis D. Research Triangle Institute International; Estados Unidos ; Fil: Derman, Richard J. Christiana Care Health Services; Estados Unidos ; Fil: Bhalachandra, Kodkany S. KLE University. Jawaharlal Nehru Medical College; India ; Fil: Bose, Carl L. University of North Carolina; Estados Unidos
OBJECTIVE: To describe the causes of maternal death in a population-based cohort in six low and middle-income countries using a standardized, hierarchical, algorithmic cause of death (COD) methodology DESIGN: A population-based, prospective observational study SETTING: Seven sites in six low-middle income countries including the Democratic Republic of the Congo (DRC), Guatemala, India (2), Kenya, Pakistan and Zambia. POPULATION: All deaths amongst pregnant women resident in the study sites from 2014 to December 2016. METHODS: For women who died, we used a standardized questionnaire to collect clinical data regarding maternal conditions present during pregnancy and delivery. These data were analyzed using a computer-based algorithm to assign cause of maternal death based on the International Classification of Disease - Maternal Mortality system (trauma, abortion-related, eclampsia, hemorrhage, pregnancy-related infection and medical conditions). We also compared the COD results to health care provider assigned maternal COD. MAIN OUTCOME MEASURES: Assigned causes of maternal mortality RESULTS: Amongst 158,205 women, there were 221 maternal deaths. The most common algorithm-assigned maternal COD were obstetric hemorrhage (38.6%), pregnancy-related infection (26.4%) and preeclampsia/eclampsia (18.2%). Agreement between algorithm-assigned COD and COD assigned by health care providers ranged from 75% for hemorrhage to 25% for medical causes coincident to pregnancy. CONCLUSIONS: The major maternal COD in the Global Network sites were hemorrhage, pregnancy-related infection and preeclampsia/eclampsia. This system could allow public health programs in low and middle-income countries to generate transparent and comparable data for maternal COD across time or regions.
