Objectives To provide descriptive information on behavioral health (BH) productivity and billing practices within a pediatric primary care setting. Methods This retrospective investigation reviewed 30 months of electronic medical records and financial data. Results The percent of BH provider time spent in direct patient care (productivity) was 35.28% overall, with a slightly higher quarterly average (M = 36.42%; SD = 6.46%). In the 646.75 hr BH providers spent in the primary care setting, $52,050.00 was charged for BH services delivered ($80.48 hourly average). Conclusions BH productivity and billing within pediatric primary care were suboptimal and likely multifactorially derived. To promote integrated primary care sustainability, the authors recommend three future aims: improve BH productivity, demonstrate the value-added contributions of BH services within primary care, and advocate for BH-supporting health care reform.
This paper presents results of two years of investigations on three types of wastewater stabilization pond treatment systems, purifying a raw urban wastewater, in the arid climate of Marrakesh. The systems tested were: two lined water hyacinth ponds, two lined facultative ponds and one anaerobic pond. During the course of the experiment, organic load, nutrients and parasitical load were studied. Results show that the macrophytic ponds were more efficient to reduce organic load (90% of TSS and 78% of COD) that the microphtic ponds; these ones were more efficient to eliminate nutrients (NTK 71%, NH4 60%, Ptotal 80% and PO4 62%). The anaerobic pond presents a lower efficiency, less than 40% for organic and less than 20% for nutrients. About sanitary concerns, all of the year, the macrophytic and microphytic pond effluents correspond to B category (WHO, 1989). The anaerobic pond yields B category effluent except in autumn when it corresponds to C category.
This paper focuses on privacy and security concerns in Big Data. This paper also covers the encryption techniques by taking existing methods such as differential privacy, k-anonymity, T-closeness, and L-diversity. Several privacy-preserving techniques have been created to safeguard privacy at various phases of a large data life cycle. The purpose of this work is to offer a comprehensive analysis of the privacy preservation techniques in Big Data, as well as to explain the problems for existing systems. The advanced repository search option was utilized for the search of the following keywords in the search: “Cyber security” OR “Cybercrime”) AND ((“privacy prevention”) OR (“Big Data applications”)). During Internet research, many search engines and digital libraries were utilized to obtain information. The obtained findings were carefully gathered out of which 103 papers from 2,099 were found to gain the best information sources to address the provided study subjects. Hence a systemic review of 32 papers from 103 found in major databases (IEEExplore, SAGE, Science Direct, Springer, and MDPIs) were carried out, showing that the majority of them focus on the privacy prediction of Big Data applications with a contents-based approach and the hybrid, which address the major security challenge and violation of Big Data. We end with a few recommendations for improving the efficiency of Big Data projects and provide secure possible techniques and proposed solutions and model that minimizes privacy violations, showing four different types of data protection violations and the involvement of different entities in reducing their impacts.
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