Prevalence and Factors Associated With Maternal Near-misses at Kenyatta National Hospital - a 3 Year Retrospective Analysis

Abstract

Background: The third sustainable development goal aims to reduce the global maternal mortality ratio to less than 70 per 100,000 live births by 2030. Traditionally, maternal mortality audits have been the usual channel employed to mitigate the ever high mortality rates. Kenya’s maternal mortality ratio has reduced from 488 to 362, but a lot is still desired in terms of achieving significant reduction of the rates. In-depth reviews of maternal near misses, defined as women who nearly died but survived life threatening conditions in pregnancy, childbirth or puerperium, may be the silver lining to this dark cloud. Near misses occur frequently, and maternal mortalities almost invariably arise from them. Many high income countries are turning to the use of NMCR as a strategy for bettering patient care and hence significantly reduce maternal mortality. In Kenya, prevalence of near miss events and factors associated with them is not routinely reported or published. MNM risk factor identification will lead to heightened vigilance hence better preparedness and management practices and overall improvement in quality of care in maternal and new-born services. Objective: To determine the prevalence and factors associated with maternal near misses at Kenyatta National Hospital between 1st January 2017 and 31st December 2019. Methodology: A cross sectional study with a case control component undertaken retrospectively over a period of 3 years. Study population shall be women admitted into KNH for delivery or pregnancy related care during the 3 year interval. Maternal near misses shall be determined by subjecting records of women who experienced SMO to WHO NM criteria. The case control study will be used to evaluate factors associated with development of MNM. Cases will be women admitted at KNH with confirmed pregnancy for delivery or with pregnancy related conditions or in puerperium, with complications that are commensurate with the WHO NM criteria. Controls will be patients having the same admission date as the cases, with normal deliveries. Data will be collected by 6 research assistants through the use of a questionnaire. Collected data will be analysed using SPSS version21. Descriptive analysis of cases and controls’ socio-demographics will be done, with categorical variables being summarized as proportions and frequencies with continuous variables being summarized as means, medians and interquartile ranges. Inferential analysis will be done, with univariate and multivariate logistic regression performed to obtain odds ratios of risk factors associated with MNM, with statistical significance at p < 0.05