This blog was originally published by Saving Lives at Birth. Written by Rachel Whelan.
15 million babies are born too soon every year, making premature birth the leading cause of newborn death around the world. Most preterm births and deaths occur in low-income countries, where 5.6 million babies are born in homes and another 4.4 million are born in primary care facilities with limited capacity for special care. The majority of deaths in preterm babies could be prevented with feasible, low-cost interventions, such as kangaroo mother care and early recognition and treatment of complications of prematurity, including infections and jaundice.
But in low-income settings, how do we know which babies are premature in the first place? In high-income countries, most women recall their last menstrual period and have an ultrasound, which provides accurate pregnancy dating. However, in many low-income countries, the percentage of women who have access to ultrasound is in the single digits.
With this in mind, for Saving Lives at Birth Round 1 and with support from the World Health Organization, we have been testing the accuracy of a range of different methods to help community health workers (CHWs) easily identify preterm infants. We’ve been conducting our analysis in the Projahnmo field site in Sylhet, Bangladesh as part of a collaboration between Johns Hopkins Bloomberg School of Public Health, International Center for Diarrheal Disease Research – Bangladesh, Shimantik NGO, and the Bangladeshi Ministry of Health and Family Welfare. We assess each newborn by measuring various physical characteristics, including the flexibility of the baby’s ear and length of the baby’s foot. We then compare these measurements to previously captured ultrasounds, which allows us to evaluate the accuracy of each method at discerning prematurity.
A community health worker measures a newborn’s foot.
Once preterm babies are identified, providing these high-risk newborns with specialized, life-saving care is the next step in preventing preterm birth complications and deaths. With our new Saving Lives at Birth Round 4 grant, we plan to develop a toolkit to help CHWs better identify and manage small babies. The first part of the toolkit will be a mobile phone application to help the CHW identify premature infants using our simple and rapid preterm assessment. The mobile application will also guide the CHW through managing the preterm baby at home, with modules for early referral to the hospital for the very premature baby as well as modules for home-based management of common complications and illnesses, such as possible severe bacterial infection, jaundice, feeding difficulties, and hypothermia. The mobileapplication will support clinical decision-making to ensure that each essential step in the care pathway is followed every time for every baby.
The second essential piece of our small baby toolkit will be a simple, low-cost plastic jaundice ruler to improve the ability of CHWs to assess newborns for jaundice. Jaundice is perhaps the most common neonatal illness, affecting 50% of full term and 80% of preterm babies, but which in severe cases can lead to permanent brain damage or death. Neonatal jaundice occurs when the liver cannot process old red blood cells fast enough and a pigment called bilirubin builds up in the blood, turning the baby’s skin and eyes yellow. The more yellow the skin, the more bilirubin in the blood, and the more severe the disease.
To this end, we are creating a ruler that uses colors instead of numbers as its units of measurement. This jaundice ruler will be developed and validated in Bangladesh. After pressing the ruler into the baby’s skin, the CHW will be able to match the yellow tones in the skin to the yellow tones in the ruler to determine the severity of disease.
Together, these tools will empower community health workers to more accurately recognize, refer and manage premature and jaundiced newborns. In turn, this will improve access to effective treatment for mothers and their babies, an important step in reducjng neonatal morbidity and mortality in the highest burden and lowest resource settings.