Maternal mortality has fallen significantly in recent years, especially in countries that have emphasized the prevention of its main causes, such as hemorrhagic and infectious complications and hypertension , including in the Region of the Americas. In its final report on the Plan of Action to Accel...erate the Reduction of Maternal Mortality and Severe Maternal Morbidity, the Pan American Health Organization (PAHO) reported a continuing downward trend in maternal mortality, with an 18.1% reduction in the maternal morbidity ratio during the period 2010-2015 . From a pathophysiological perspective, death events are a common end result of a wide spectrum of complications leading to multi-organ dysfunction. However, there is a group of women in this situation who survive, despite the seriousness of their condition. This high number of patients––who were in serious condition
but did not die––reflects the actual health conditions in an institution or a country. For this reason, there is a need to create indicators to estimate morbidity in women due to diseases and incidents that occur during pregnancy, childbirth, and the puerperium. To this end, we propose conducting epidemiological surveillance of an indicator that includes women who survived after presenting a potentially fatal complication during pregnancy, childbirth, or the puerperium, reflecting quality medical attention and care (5, 6). This indicator
is maternal near-miss (MNM), which refers to extremely severe maternal morbidity––cases of a severity that
brings women very close to the death event. After adjusting the definition to a specific population and time,
MNM is defined as a case in which a woman nearly died, but survived a complication that occurred during
pregnancy, childbirth, or within 42 days of termination of pregnancy
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The World Health Organization (WHO) is releasing the second edition of its Global Accelerated Action for the Health of Adolescents (AA-HA!) guidance. The document aims to equip governments to respond to the health and well-being challenges, opportunities and needs of adolescents.
The guidance pro...vides the latest available data on adolescent health and well-being. It also outlines an updated list of core indicators that data should be collected on. Globally, road injury was the top cause of death for adolescent males in 2019. Among female adolescents, the leading causes of death were diarrhoeal diseases among the younger group (10-14 years) and tuberculosis (TB) in the older group (15-19 years).
Over the last 20 years, mortality rates have declined among adolescents globally, with the largest decline in older (15–19 years) adolescent girls. For non-fatal diseases, the burden has not improved over the past two decades, with the main causes of ill health in this category being: mental health conditions (depressive and anxiety disorders, childhood behavioural disorders), iron deficiency anaemia, skin diseases and migraine.
Adolescent well-being depends on a range of factors, including healthy food, education, life skills and employability, connectedness, feeling valued by society, safe and supportive environments, resilience, and the freedom to make choices. To take an appropriately holistic approach, the guidance outlines how to take crosscutting action to support adolescent health and well-being, with mutually reinforcing interventions across sectors, such as health, education, social protection, and telecommunications. Targeted efforts are also required to engage adolescents, as they trust health systems less than adults do and are especially vulnerable to modern-day trends, like online bullying and gaming.
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A training package for building capacity of healthcare teams in health facilities for continous quality improvement of maternal and newborn healthcare. The focus is on the care of mothers and newborns at the time of child birth since a large proportion of maternal deaths, newborn deaths and stillbir...ths happen around that time.
The 4-Step POCQI (Point of care Quality Improvement) package includes Coaching manual and Learner manual that present a demystified and simple model of quality improvement at the level of health facilities using local data to identify quality gaps, analyse underlying causes and improve health care practices in their own specific context without much additional resources.
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