Perceptions and utilization of primary health care services in Iraq: findings from a national household survey

<p>Abstract</p> <p>Background</p> <p>After many years of sanctions and conflict, Iraq is rebuilding its health system, with a strong emphasis on the traditional hospital-based services. A network exists of public sector hospitals and clinics, as well as private clinics and a few private hospitals. Little data are available about the approximately 1400 Primary Health Care clinics (PHCCs) staffed with doctors. How do Iraqis utilize primary health care services? What are their preferences and perceptions of public primary health care clinics and private primary care services in general? How does household wealth affect choice of services?</p> <p>Methods</p> <p>A 1256 household national survey was conducted in the catchment areas of randomly selected PHCCs in Iraq. A cluster of 10 households, beginning with a randomly selected start household, were interviewed in the service areas of seven public sector PHCC facilities in each of 17 of Iraq's 18 governorates. A questionnaire was developed using key informants. Teams of interviewers, including both males and females, were recruited and provided a week of training which included field practice. Teams then gathered data from households in the service areas of randomly selected clinics.</p> <p>Results</p> <p>Iraqi participants are generally satisfied with the quality of primary care services available both in the public and private sector. Private clinics are generally the most popular source of primary care, however the PHCCs are utilized more by poorer households. In spite of free services available at PHCCs many households expressed difficulty in affording health care, especially in the purchase of medications. There is no evidence of informal payments to secure health services in the public sector.</p> <p>Conclusions</p> <p>There is widespread satisfaction reported with primary health care services, and levels did not differ appreciably between public and private sectors. The public sector PHCCs are preferentially used by poorer populations where they are important providers. PHCC services are indeed free, with little evidence of informal payments to providers.</p

Software Defect Prediction Using Extreme Gradient Boosting(XGBoost) with Tune Hyperparameter

Software applications have become widely spread in an unprecedented manner in our daily lives, controlling some of the most sensitive and critical aspects within institutions. Examples include automated systems such as traffic control, aviation, and self-driving cars, among many others. Identifying software defects in these systems poses a challenge for most software-producing companies. In order to develop high-quality and reliable software, companies have turned to defect prediction using machine learning, relying on historical project datasets. This study aims to classify software defect prediction using machine learning techniques, specifically classification techniques. One of the classification techniques employed is eXtreme Gradient Boosting (XGBoost), a useful method for regression and classification analysis based on a gradient boosting decision tree (GBoost). XGBoost incorporates several hyperparameters that can be fine-tuned to enhance the model's performance. The employed hyperparameter tuning method is grid search, validated thereafter using 10-fold cross-validation. The hyperparameters configured for XGBoost include n_estimators, max_depth, subsample, gamma, colsample_bylevel, min_child_weight, and learning_rate. Based on the results of this study, it has been demonstrated that the utilization of algorithms with hyperparameter tuning can improve the performance of the XGBoost algorithm in accurately classifying software defects with high precision