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Figure 4: Dataset template for stillbirths. A template for the development of data collection forms for datasets of stillbirths.

Image Text (High Precision): 1000 500 Autopsy Care Intrapartum Intrauterine Maternal Number Perinatal Placenta Placental Quality abortion analyses anemia anomaly antenatal antepartum assisted associated attendance availability available birth births careli characteristics characteristicsage chromosomal clinical comments completed complication condition conditions death deaths delivery dystocia elective estimate evaluation evaluations examination female fetal fetuses fundal fundat genetic gestation height histopathology history hypertension infection infections institution institutions macroscopic macroscopy malnutrition malpresentation measures menstrual mother multiples obstetrician operative period plurality pregnancies prepregnancy present preterm previous professional prolonged provision rate registrants reprod review signature skilled spontaneous terminations traditional transit ultrasound unattended utilization vaginal verbal visits weeks weight

Other Images from "Making stillbirths count, making numbers talk - Issues in data collection for stillbirths":


Figure 1 Stillbirth determinants. A framework of ...

Figure 3 Stillbirth rates by reporting criteria. ...

Figure 4 Dataset template for stillbirths. A temp...

Figure 5 Causes of death in stillbirth. Expandabl...

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Abstract

BackgroundStillbirths need to count. They constitute the majority of the world's perinatal deaths and yet, they are largely invisible. Simply counting stillbirths is only the first step in analysis and prevention. From a public health perspective, there is a need for information on timing and circumstances of death, associated conditions and underlying causes, and availability and quality of care. This information will guide efforts to prevent stillbirths and improve quality of care.DiscussionIn this report, we assess how different definitions and limits in registration affect data capture, and we discuss the specific challenges of stillbirth registration, with emphasis on implementation. We identify what data need to be captured, we suggest a dataset to cover core needs in registration and analysis of the different categories of stillbirths with causes and quality indicators, and we illustrate the experience in stillbirth registration from different cultural settings. Finally, we point out gaps that need attention in the International Classification of Diseases and review the qualities of alternative systems that have been tested in low- and middle-income settings.SummaryObtaining high-quality data will require consistent definitions for stillbirths, systematic population-based registration, better tools for surveys and verbal autopsies, capacity building and training in procedures to identify causes of death, locally adapted quality indicators, improved classification systems, and effective registration and reporting systems.


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