Evaluating quality neonatal care, call Centre service, tele-health and community engagement in reducing newborn morbidity and mortality in Bungoma county, Kenya

Background: Neonatal mortality is a major health burden in Bungoma County with the rate estimated at 31 per 1000 live births and is above the national average of 22 per 1000. Nonetheless, out of the nine sub county hospitals, only two are fairly equipped with necessary infrastructure and skilled personnel to manage neonatal complications such as prematurity, neonatal sepsis, neonatal jaundice, birth asphyxia and respiratory distress syndrome. Additionally, with more than 50% of neonates delivered without skilled attendance, in below par hygiene environments such as home and on the roadsides, with non-existent community based referral system, the situation is made worse. The study aims to evaluate the progress made by an intervention “Collaborative Newborn Support Project” geared towards reducing neonatal mortality rate by 30% between October 2015 and December 2018 in Bungoma County, Kenya. Methods/Design: This intervention will take a quasi-experimental design approach with experimental and control sites. The project will involve pre- and post-intervention data collection with comparison group to assess intervention effects. The primary outcome will be the percentage reduction of neonatal mortality in Bungoma County. Secondary outcomes include; a) Percentage of mothers or care givers able to identify at least three danger signs in neonates in the project area, b) Proportion of neonates with complications referred to specialized neonatal centers, through the call center, c) Percentage of health providers in neonatal care units who adhere to expected neonatal standards of care (rapid and complete application of standard protocols), d) Percentage increase in neonates with severe complications in the specialized neonatal units and e) Percentage of neonates who stay in neonatal care units beyond 5 days. Discussion: We outline implementation details of the ongoing ‘Collaborative Newborn Support Project’ in Bungoma County, Kenya. This includes strategies in the operations of the telehealth platform, call centre service, community engagement and measuring of the outputs and outcomes. The funding and ethical approvals have been obtained and the study commenced. Trial registration: PACTR201712002802638 Retrospectively registered on 5th December 2017 at Pan African Clinical Trials Registry.

Bungoma County (coordinates 0.8479° N, 34.7020° E), Western Kenya has a population of approximately 1.7 m and an area of 2069 km2. The County has an urbanization rate of 21.7%, literacy levels of 60.5% with 87.6% of residents between the ages of 15–18 attending primary school. It has a poverty rate of 52.9% and access to electricity access of 4.5% [4, 15]. The main ethnic groups in the county are the Bukusu and Sabaoti sub-tribes of Luhya and Kalenjin respectively. The main economic activities include: Agriculture, manufacturing and retail services. Agriculture is the backbone of Bungoma County and most families rely on crop production and animal rearing. The main crops include maize, beans, finger millet, sweet potatoes, bananas, Irish potatoes and assorted vegetables. These are grown primarilly for subsistence with the excess sold to meet other family needs. On the other hand, the main cash crops include sugar cane, cotton, palm oil, coffee, sun flower and tobacco. Most families integrate livestock production with farming. The main livestock kept include cattle, sheep, goats, donkeys, pigs, poultry and bees. Most of this is on a small scale but some farmers also produce milk and poultry products for commercial use. Milk and sugarcane farmers sell their produce mainly through cooperative societies. The County is comprised of 6 constituencies: Kimilili, Webuye East, Webuye West, Sirisia, Kanduyi, Bumula and Mt. Elgon. This guided the selection of project intervention sites. These sites are in the following facilities; Bungoma County referral hospital, Webuye Sub-County hospital, Kimilili, Sirisia, Bumula, Naitiri, Mt. Elgon, Sinoko and Chwele. This intervention will take a quasi-experimental design approach with an experimental and control site. The project will involve pre- and post-intervention data collection with one comparison group to assess intervention effects. The study will be conducted at level 4 and 5 hospitals, each hospital having high volume of clients and covering a sub-county, all with similar maternal, newborn and child health indicators. Five hospitals will be the implementation sites while 4 hospitals will be control sites in a step wedge approach. The implementation sites will be selected purposely. The control sites will receive the full intervention after 1 year when the first set of comparison with the intervention site has been completed. The 5 experimental site hospitals will receive a set of interventions which include: refurbishing of new born units, installation of equipment such as incubators, respirators, Ambu bags, and radiators. Establishment of a tele-health platform to enable free flow of information amongst clinicians and obstetricians, establishment of a call center for follow up of patients, training of health care providers in neonatology, and creating awareness amongst the community will be key cross cutting interventions, implying they will benefit the intervention site as well as control site. The control sites will not receive the main intervention benefits (equipped specialized newborn units) until after 1 year of implementation in the experimental sites. The project will undertake a baseline, mid-term and end-line surveys. The step wedge design which allows for the measurement of process, outcome and impact indicators within each site (at different time points) will be used. The design also allows a comparison between different combinations of the intervention components. Percentage reduction in newborn deaths in Bungoma County between October 2015 and December 2018. This will be measured by comparing the number of newborn deaths at the nine project facilities (in the period of implementation), with the number of deaths at the same facilities in the similar period before the intervention; converted to percentage and aggregated by facility. Tools To minimize bias and contamination, the intervention sites will be selected purposely from the nine county and sub- county hospitals. The sites selected will include the two facilities that have some level of neonatal facilities to ensure that the intervention sites and the control sites have distinct features separating the two. We will measure the utilization of services in the selected facilities at baseline, mid-term and end-line levels. To determine utilization of neonatal services, we will collect data directly from the source through a data abstraction form in the nine health facilities throughout the project period. Further, the community health workers and volunteers will also provide information of the number of cases they refer to specific facilities. Cases that fail to arrive at the health facilities will also be captured and the data from the facilities and the community health workers will be cleaned, cross checked and analyzed to provide required results for utilization of neonatal services. Quality of care will be determined through observations of service provision by clinicians, as well as checking use of neonatal equipment and the severity of conditions managed by the health providers in the units. Bungoma County, the area targeted by community sensitization will be source area for target newborn caregivers/newborn mothers who will be simple randomly selected to participate in the survey. Statistical methods for determining sample size will be employed to ensure the correct sample size is picked to avoid biases and ensure the outcomes are valid. There are approximately 29,845 births in Bungoma County per annum [16]. This number will be split twice for control and intervention group. The study will allow a margin of error of 5% at confidence level of 95% to obtain the correct sample size for the study. It is also expected that at least one of the variables of interest (e.g., knowledge of 3 danger signs in neonates) will be 50% among the respondents. Using the formula: where N is the population size, r is the fraction of responses that we are interested in, and Z(c/100) is the critical value for the confidence level c, we get 375 as our ideal sample size in the control and intervention areas (i.e., four data collectors in each area conducting 8 surveys daily for 12 working days each). See Additional file 1. There are 177 health facilities in Bungoma County of which 12 are hospitals and the rest are health centers, dispensaries and clinics. In this study, nine high volume health facilities will be selected to participate in the study. Five Facilities will be intervention sites while four health facilities will be the control sites. The intervention sites will be selected purposely from the nine project facilities. The sample size calculation is based on net change in the proportion of neonates who present with complications in health facilities. From the County HMIS data, it is estimated that a significant proportion of babies born with complications are missed out or only a few of them present to health facilities. In Bungoma County, currently only 21% present in health facilities. Through the Newborn collaborative support project, we seek to increase this by 50%, (21 to 32%). Given that births are 29,845 [16] and current situation is 21% presenting in health facilities we get a population of 6268 neonates. This means we get a sample size of 125 neonates for intervention and 125 for control group. Data collection tools such as questionnaires will be administered randomly amongst the selected cases. See Additional file 2. Ninety health care providers who give informed consent to participate in the study and meet the requirement of the selection criteria will be interviewed through a questionnaire to determine their knowledge and skills levels in neonatal care. The health care providers have already been trained in their respective areas but may be deficient in neonatal care. It is approximated that their knowledge on neonatology is at 65% and this needs to be increased up to about 90%. See Additional file 3. In- depth interviews will be conducted with key informants in the selected project sites (See Additional file 4). They include the following: 1 – County Director of health services 1 – Director of nursing services in the county 1 – County RH coordinator 1 –Pediatrician in the county 9 – Medical Superintendents/Facility –in- charges – one in each Hospital 9- Nurses in – charge on maternity – one in each Facility 9- Staff in- charge of new born units

• gitaka, jesse
• natecho, alice
• mwambeo, humphrey m.
• gatungu, daniel
• githanga, david
• abuya, timothy