Delivery care in Quang Ninh province, Northern Vietnam : resources and access to safe care.

Every mother and child has the right to survive childbirth which requires skilled birth attendants together with referral and available emergency obstetric care (EmOC). The objective of the study was to describe delivery care routines at different levels in the health care system in Quang Ninh province, Northern Vietnam. The design was cross sectional using a structured questionnaire. Two districts in Quang Ninh province with 40 Community Health Centres (CHC), three district hospitals and one region hospital was included in the study, in total 138 (CHC n=105 and hospitals n=33) health care providers participated. In our study 20% (CHC) of the health care providers assisting deliveries at CHC were midwives and health care provider’s in our study further report to have assisted at less then 10 deliveries/year (81% of respondents at CHC). Findings show that the health care provider’s routines and care for women during labour and delivery vary and that there is a need for re-training and that women in labour should be cared for by health care providers with adequate training like midwifery. In our study CHC had poor resources to provide basic or comprehensive EmOC. Our findings indicate that there is a need for re-training in delivery care among health care providers and since the number of deliveries at CHC is few they should be handled by someone who is a skilled birth attendant. Our findings also show a variation in care routines during labour and delivery among health care providers at CHC and hospital levels and this also show the need for re-training and support from proper authorities in order to improve maternal and newborn health.

ANFIS BASED MODELS FOR ACCESSING QUALITY OF WIKIPEDIA ARTICLES

Wikipedia is a free, web-based, collaborative, multilingual encyclopedia project supported by the non-profit Wikimedia Foundation. Due to the free nature of Wikipedia and allowing open access to everyone to edit articles the quality of articles may be affected. As all people don’t have equal level of knowledge and also different people have different opinions about a topic so there may be difference between the contributions made by different authors. To overcome this situation it is very important to classify the articles so that the articles of good quality can be separated from the poor quality articles and should be removed from the database. The aim of this study is to classify the articles of Wikipedia into two classes class 0 (poor quality) and class 1(good quality) using the Adaptive Neuro Fuzzy Inference System (ANFIS) and data mining techniques. Two ANFIS are built using the Fuzzy Logic Toolbox [1] available in Matlab. The first ANFIS is based on the rules obtained from J48 classifier in WEKA while the other one was built by using the expert’s knowledge. The data used for this research work contains 226 article’s records taken from the German version of Wikipedia. The dataset consists of 19 inputs and one output. The data was preprocessed to remove any similar attributes. The input variables are related to the editors, contributors, length of articles and the lifecycle of articles. In the end analysis of different methods implemented in this research is made to analyze the performance of each classification method used.

The importance of considering the evidence in the MTP 2014 Amendment debate in India - unsubstantiated arguments should not impede improved access to safe abortion

With the objective to improve access to safe abortion services in India, the Ministry of Health and Welfare, with approval of the Law Ministry, published draft amendments of the MTP Act on October 29, 2014. Instead of the expected support, the amendments created a heated debate within professional medical associations of India. In this commentary, we review the evidence in response to the current discourse with regard to the amendments. It would be unfortunate if unsubstantiated one-sided arguments would impede the intention of improving access to safe abortion care in India.