1. Labour and delivery ward register data availability, quality, and utility - Every Newborn - birth indicators research tracking in hospitals (EN-BIRTH) study baseline analysis in three countries
- Author
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Harriet Ruysen, Nahya Salim, Shafiqul Ameen, Alodear Patrick Kitende, Godfrey Mbaruku, Tazeen Tahsina, Kizito Shirima, Amina Omari Semhando, Elisha Joshi, Sabu Thapa, Omkar Basnet, Namala Mkopi, Anna Wisiko, Asmita Poudel, Priyanka Chaudhary, Georgia R Gore-Langton, John Mathias Bakuza, Josephine Shabani, Donat Shamba, Vladimir S. Gordeev, Rajendra Prasad Poudel, Christostomus Chingalo, Japhet Kombo, Joy E Lawn, Bibek Chitrakar, Cleopatra Mtei, Rabina Karki, Ahmed Ehsanur Rahman, Victoria Mwenisongole, Tanvir Hossain, Louise T Day, Dorothy Boggs, Ashish K C, Marystella Revocatus Shirati, Sojib Bin Zaman, Hannah Blencowe, Qazi Sadeq-ur Rahman, Durga Poudel, and Shams El Arifeen
- Subjects
medicine.medical_specialty ,Reproduktionsmedicin och gynekologi ,Maternal ,Health informatics ,Tanzania ,Health administration ,03 medical and health sciences ,Hospital ,0302 clinical medicine ,Health facility ,Nepal ,Pregnancy ,Environmental health ,Obstetrics, Gynecology and Reproductive Medicine ,Medicine ,Indicators ,Humans ,030212 general & internal medicine ,Registries ,Measurement ,Bangladesh ,030219 obstetrics & reproductive medicine ,biology ,business.industry ,lcsh:Public aspects of medicine ,Health Policy ,Mortality rate ,Public health ,Delivery Rooms ,Infant, Newborn ,Registers ,lcsh:RA1-1270 ,Public Health, Global Health, Social Medicine and Epidemiology ,Stillbirth ,biology.organism_classification ,Newborn ,Routine Health Management Information Systems ,Data Accuracy ,Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi ,Data quality ,Birth ,Female ,business ,Count data ,Research Article - Abstract
Background Countries with the highest burden of maternal and newborn deaths and stillbirths often have little information on these deaths. Since over 81% of births worldwide now occur in facilities, using routine facility data could reduce this data gap. We assessed the availability, quality, and utility of routine labour and delivery ward register data in five hospitals in Bangladesh, Nepal, and Tanzania. This paper forms the baseline register assessment for the Every Newborn-Birth Indicators Research Tracking in Hospitals (EN-BIRTH) study. Methods We extracted 21 data elements from routine hospital labour ward registers, useful to calculate selected maternal and newborn health (MNH) indicators. The study sites were five public hospitals during a one-year period (2016–17). We measured 1) availability: completeness of data elements by register design, 2) data quality: implausibility, internal consistency, and heaping of birthweight and explored 3) utility by calculating selected MNH indicators using the available data. Results Data were extracted for 20,075 births. Register design was different between the five hospitals with 10–17 of the 21 selected MNH data elements available. More data were available for health outcomes than interventions. Nearly all available data elements were > 95% complete in four of the five hospitals and implausible values were rare. Data elements captured in specific columns were 85.2% highly complete compared to 25.0% captured in non-specific columns. Birthweight data were less complete for stillbirths than live births at two hospitals, and significant heaping was found in all sites, especially at 2500g and 3000g. All five hospitals recorded count data required to calculate impact indicators including; stillbirth rate, low birthweight rate, Caesarean section rate, and mortality rates. Conclusions Data needed to calculate MNH indicators are mostly available and highly complete in EN-BIRTH study hospital routine labour ward registers in Bangladesh, Nepal and Tanzania. Register designs need to include interventions for coverage measurement. There is potential to improve data quality if Health Management Information Systems utilization with feedback loops can be strengthened. Routine health facility data could contribute to reduce the coverage and impact data gap around the time of birth.
- Published
- 2020