The days from birth to 7 days of life are now the period associated with the highest risk of death across the lifespan in LMIC. Reducing persistently high neonatal mortality is therefore now a key target of the Sustainable Development Goals. Preterm birth, low birth weight, intrauterine / intrapartum hypoxia-ischaemia and severe infection are the major causes of high neonatal mortality and improved prevention linked to care for these conditions, often requiring basic care in hospitals, is now a priority in LMIC. Beyond survival it is also clearly critical that vulnerable babies – those that are so preterm, low-weight or sick that they need admission to hospital in the first days or weeks after birth – have adequate growth and development during and after any hospital admission. Indeed the Global Strategy for Women’s, Children’s and Adolescents’ health now champions issues of survive, thrive and transform. Ensuring adequate growth in the critical early weeks of life is key to this agenda and to subsequent infant and child development.
However, in most LMIC information on early growth of populations of vulnerable babies is lacking. Tracking the growth of this population – that may be an important indicator of the quality of health care received and indeed a whole health system – faces multiple challenges in LMIC. In routine hospital settings information systems are very poorly developed. Newborn babies may have no unique identifier that spans their inpatient and outpatient care, undermining efforts at record linkage. Babies that have been discharged may not have any formal hospital follow up records, instead the family may hold the records documenting a baby’s progress (for example in Kenya these may be held in the Maternal Child Health Passport). Follow-up schedules may not be standardised and follow up itself may not be done by the same clinic or the same providers even in the first weeks of life.
The purpose of this DPhil is to develop and potentially test innovative solutions to generating these growth data for the cohort of vulnerable babies that are discharged from Kenyan hospitals. The DPhil may include:
Field studies would be developed with collaborators based at the KEMRI-Wellcome Trust in Nairobi (www.kemri-wellcome.org) and the Ministry of Health in Kenya and would likely take advantage of ongoing work aiming to improve inpatient neonatal data systems.
The purpose of this DPhil is to introduce the student to health informatics research in LMIC context with a focus on a current major challenge of tracking growth (as an indicator of health status) in babies that have experienced serious illness near the time of birth. The student would learn how to conduct a systematic review and critically appraise informatics tools and their effectiveness in achieving health information goals. They would learn how to design and conduct empirical studies that use a health systems perspective to understand information requirements in addition to studies that address more familiar informatics concerns such as usability. Depending on progress the candidate might proceed to learn how to design and conduct an implementation study within a LMIC context. We therefore expect skills in proposal writing to satisfy the requirements of scientific and ethical review to be developed. Where necessary appropriate training in research methods will be provided (eg. in qualitative or quantitative data collection and analysis) and there will be opportunities for engaging with a wider body of researchers in Oxford and Kenya conducting health systems research. It is anticipated that during the course of the DPhil and linked to the collection of primary data approximately 6 - 9 months may be spent in Kenya based at the Nairobi offices of the KEMRI-Wellcome Trust Research Programme (www.kemri-wellcome.org).
Project reference number: 1026
|Dr Chris Paton||Tropical Medicine||Oxford University, NDM Research Building||GBRemail@example.com|
|Professor Mike English||Tropical Medicine||Oxford University, Nairobi||KENfirstname.lastname@example.org|
There are no publications listed for this DPhil project.