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Background  Maternal near misses are increasingly used to study quality of obstetric care. Inclusion criteria for the identification of near misses are diverse and studies not comparable. WHO developed universal near miss inclusion criteria in 2009 and these criteria have been validated in Brazil and Canada.    Objectives  To validate and refine the WHO near miss criteria in a low-resource setting.    Methods  A prospective cross-sectional study was performed in a rural referral hospital in Tanzania. From November 2009 until November 2011, all cases of maternal death (MD) and maternal near miss (MNM) were included. For identification of MNM, a local modification of the WHO near miss criteria was used, because most laboratory-based and some management-based criteria could not be applied in this setting. Disease-based criteria were added as they reflect severe maternal morbidity. In the absence of a gold standard for identification of MNM, the clinical WHO criteria were validated for identification of MD.    Results  32 MD and 216 MNM were identified using the locally adapted near miss criteria; case fatality rate (CFR) was 12.9%. WHO near miss criteria identified only 60 MNM (CFR 35.6%). All clinical criteria, 25% of the laboratory-based criteria and 50% of the management-based criteria could be applied. The threshold of five units of blood for identification of MNM led to underreporting of MNM. Clinical criteria showed specificity of 99.5% (95%CI: 99.4%–99.7%) and sensitivity of 100% (95%CI: 91.1%–100%). Some inclusion criteria did not contribute to the identification of cases and therefore may be eligible for removal.    Conclusion  The applicability of the WHO near miss criteria depends on the local context, e.g. level of health care. The clinical criteria showed good validity. Lowering the threshold for blood transfusion from five to two units in settings without blood bank and addition of disease-based criteria in low-resource settings is recommended.

Applicability of the WHO Maternal Near Miss Criteria in a Low-Resource Setting