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Background: Facility-based stillbirth review provides opportunities to estimate incidence, evaluate causes and risk factors for stillbirths, and identify any issues related to the quality of pregnancy and childbirth care which require improvement. Our aim was to systematically review all types and methods of facility-based stillbirth review processes used in different countries across the world, to examine how stillbirth reviews in facility settings are being conducted worldwide and to identify the outcomes of implementing the reviews. Moreover, to identify facilitators and barriers influencing the implementation of the identified facility-based stillbirth reviews processes by conducting subgroup analyses. Methods: A systematic review of published literature was conducted by searching MEDLINE (OvidSP) [1946-present], EMBASE (OvidSP) [1974-present], WHO Global Index Medicus (, Global Health (OvidSP) [1973–2022 Week 8] and CINAHL (EBSCOHost) [1982-present] from their inception until 11 January, 2023. For unpublished or grey literature, the WHO databases, Google Scholar and ProQuest Dissertations & Theses Global were searched, as well as hand searching the reference lists of included studies. MESH terms encompassing “∗Clinical Audit”, “∗Perinatal Mortality”, “Pregnancy Complications”, and “Stillbirth” were used with Boolean operators. Studies that used a facility-based review process or any approach to evaluate care prior to stillbirth, and explained the methods used were included. Reviews and editorials were excluded. Three authors (YYB, UGA, and DBT) independently screened and extracted data, and assessed the risk of bias using an adapted JBI's Checklist for Case Series. A logic model was used to inform the narrative synthesis. The review protocol was registered with PROSPERO, CRD42022304239. Findings: A total of 68 studies from 17 high-income (HICs) and 22 low-and-middle-income countries (LMICs) met the inclusion criteria from a total of 7258 identified records. These were stillbirth reviews conducted at different levels: district, state, national, and international. Three types were identified: audit, review, and confidential enquiry, but not all desired components were included in most processes, which led to a mismatch between the description of the type and the actual method used. Routine data from hospital records was the most common data source for identifying stillbirths, and case assessment was based on stillbirth definition in 48 out of 68 studies. Hospital notes were the most common source of information about care received and causes/risk factors for stillbirth. Short-term and medium-term outcomes were reported in 14 studies, but impact of the review process on reducing stillbirth, which is more difficult to establish, was not reported in any study. Facilitators and barriers in implementing a successful stillbirth review process identified from 14 studies focused on three main themes: resources, expertise, and commitment. Interpretation: This systematic review's findings identified that there is a need for clear guidelines on how to measure the impact of implementation of changes based on outputs of stillbirth reviews and methods to enable effective dissemination of learning points in the future and promoting them through training platforms. In addition, there is a need to develop and adopt a universal definition of stillbirth to facilitate meaningful comparison of stillbirth rates between regions. The key limitation of this review is that while using a logic model for narrative synthesis was deemed most appropriate for this study, sequence of implementing a stillbirth review in the real world is not linear, and assumptions are often not met. Therefore, the logic model proposed in this study should be interpreted with flexibility when designing a stillbirth review process. The generated learnings from the stillbirth review processes inform the action plans and allow facilities to consider where the changes should happen to improve the quality of care in the facilities, enabling positive short-term and medium-term outcomes. Funding: Kellogg College, University of Oxford, Clarendon Fund, University of Oxford, Nuffield Department of Population Health, University of Oxford and Medical Research Council (MRC).

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