A model of integrated health care in a poverty-impacted community in New York City: Importance of early detection and addressing potential barriers to intervention implementation.

Disruptive behavior disorders (DBDs) are chronic, impairing, and costly behavioral health conditions that are four times more prevalent among children of color living in impoverished communities as compared to the general population. This disparity is largely due to the increased exposure to stressors related to low socioeconomic status including community violence, unstable housing, under supported schools, substance abuse, and limited support systems. However, despite high rates and greater need, there is a considerably lower rate of mental health service utilization among these youth. Accordingly, the current study aims to describe a unique model of integrated health care for ethnically diverse youth living in a New York City borough. With an emphasis on addressing possible barriers to implementation, integrated models for children have the potential to prevent ongoing mental health problems through early detection and intervention.

A Machine Learning Methodology for Identification and Triage of Heart Failure Exacerbations.

Inadequate at-home management and self-awareness of heart failure (HF) exacerbations are known to be leading causes of the greater than 1 million estimated HF-related hospitalizations in the USA alone. Most current at-home HF management protocols include paper guidelines or exploratory health applications that lack rigor and validation at the level of the individual patient. We report on a novel triage methodology that uses machine learning predictions for real-time detection and assessment of exacerbations. Medical specialist opinions on statistically and clinically comprehensive, simulated patient cases were used to train and validate prediction algorithms. Model performance was assessed by comparison to physician panel consensus in a representative, out-of-sample validation set of 100 vignettes. Algorithm prediction accuracy and safety indicators surpassed all individual specialists in identifying consensus opinion on existence/severity of exacerbations and appropriate treatment response. The algorithms also scored the highest sensitivity, specificity, and PPV when assessing the need for emergency care. Here we develop a machine-learning approach for providing real-time decision support to adults diagnosed with congestive heart failure. The algorithm achieves higher exacerbation and triage classification performance than any individual physician when compared to physician consensus opinion.

Analysis of lung cancer screening results of 9265 urban residents in Urumqi from year 2014 to 2016 / 实用肿瘤学杂志

Objective The objectives of this study were to analyze the results of lung cancer screening from 9265 urban residents in Urumqi from year 2014 to 2016,and to evaluate the significance of early diagnosis and treatment of cancer for the lung cancer prevention.Methods A total of 31,177 people with high risk of lung cancer were assessed by cancer risk questionnaire surveyed from 40 to 69 years old residents in Urumqi.High-risk groups were assigned to low-dose spiral CT scan in Affiliated Tumor Hospital of Xinjiang Medical University.Results 9,265 people were scanned with low dose spiral CT and overall completion rate was 29.7％.There had 11.9％ detection rate in 1,005 people who were scanned positive pulmonary nodules.The detection rate was 31.9％ for 2,955 people who were scanned solid nodules(＜5 mm) and 2.5％ for 236 people who had the non solid nodules(＜ 8 mm).After screening,14 patients were diagnosed by pathology and the detection rate was 0.2％.The emphysema,pulnonary cysts,pulmonary bullae and other related lung disease were detected in 4,095 people and the detection rate was 44.2％.Conclusion The lung health status of Urumqi residents was found by a wide range of lung cancer screening,and the awareness of lung cancer prevention and control was greatly improved.It provided the basis for the establishment of effective prevention and treatment system,which was helpful to improve the early diagnosis and treatment rate of lung cancer.