Situational Analysis of the Perinatal Network of Care in Nairobi City County - Assessing Neonatal Healthcare Services

Abstract

Background: High perinatal mortality rates and disparities in health outcomes in Nairobi City County’s public hospitals underscore the urgency to identify underlying problems. A situational analysis of the perinatal care network can identify the problems and inform the development of appropriate solutions to improve the outcomes. This situational analysis identified gaps in the perinatal network within major Nairobi public hospitals to inform evidence-based recommendations for enhanced neonatal health outcomes. Aim: To assess the perinatal care network within four selected public hospitals in Nairobi City County regarding neonatal care capacity, referral challenges, and effectiveness of the referral system. Study Design: The situational analysis employed a concurrent mixed-methods study design. Concurrent triangulation was applied to integrate qualitative data from healthcare professionals’ interviews with quantitative data on neonatal referrals from the Clinical Information Network (CIN) database and physical assessment of the equipment in the new born units using a modified Health Facility Assessment (HFA) tool. Study Sites: The four public hospitals where this study was conducted are Kenyatta National Hospital (KNH), Pumwani Maternity and Research Hospital (PMRH), Mama Lucy Kibaki Hospital (MLKH), and Mbagathi County Hospital (MCH). Study Population, Sampling, Data Collection, Management, and Analysis: The study population included perinatal care facilities whose information were retrieved from the CIN database and healthcare professionals in the newborn unit (NBU). Purposive sampling was used to identify the healthcare professionals to interview to collect the qualitative data. Quantitative data collected from the CIN database and physical identification of the available equipment and staffing informed about the neonatal care capacity, referral patterns, and collaborations. A triangulation approach was applied to combine the patterns observed upon quantitative analysis of CIN data and HFA data with the insights shared through the interviews to describe the perinatal care network, the challenges faced during referrals, and the effectiveness of the referral system accurately. xiii Results: The top three catchment areas for MLKH, MCH, and PMRH were Kayole II Sub-county hospital, Mutuini Sub-county hospital, and Dandora health center with 117, 97, and 82 referrals to the three level five hospitals respectively. The level five hospitals further referred neonates who needed specialized care to KNH; neonates needing critical care were referred to either MCH or KNH. MLKH received the most referrals yet it was the least equipped and staffed, and its NICU had not become operational by the time of data collection. PMRH requires a NICU, pediatric unit, and a functional diagnostic imaging department to offer comprehensive neonatal care services. Limited space, staff shortages, lack of some equipment, strained ambulances, resource-intensive admission criteria, poor communication systems, and absence of clear referral strategies, protocols, and policies reduce the capacity of the perinatal network of care for neonatal referrals. Restricting referrals to the NBU in the nearby level five hospital, dedicating KNH for referrals that require specialized and critical care that cannot be obtained in the level five hospitals improve the effectiveness of the referral system. Conclusion: A neonatal referral system exists in the perinatal network of care in NCC but its capacity is lower than the needs of the catchment areas. Addressing the challenges facing the referral system by leveraging the existing partnerships to expand the infrastructure, improve the equipment, and increase the workforce in the NBUs in the level five hospitals can increase the effectiveness of the referral system by accommodating more referrals and freeing KNH for referrals that specifically need specialized care