DNP PROJECT : DATA COLLECTION AND ANALYSISImplementation Plan/ProceduresPhase 1: Program Development (Months 1-3)� Conduct comprehensive literature review on evidence-based practices for culturally tailored hypertension self-management� Collaborate with community stakeholders and minority health organizations to understand sociocultural determinants and barriers� Design culturally relevant, linguistically appropriate education curriculum with interactive multimedia resources� Recruit and train a diverse team of bilingual, culturally competent nurses and community health workersPhase 2: Participant Recruitment (Month 4)�

Tobacco control and stress reduction Data interpretation is a critical component of the research process, one which is necessary to ensure that the data has program significance -- i.e., can provide useful guidelines for changes in policy or to add to the existing research -- and also to ensure that the data simply meets basic statistical criteria for validity. In the case of the smoking cessation program profiled in the

Self-reflection For a successful completion of any program, data analysis and results dissemination is a crucial part of the processes. Data analysis is the processes of project reporting that involves inspection, cleansing, transformation, and modeling of the data collected with the aim of establishing information that is useful in suggesting the possible conclusions and in providing insights to support the decisions made (Ott & Longnecker, 2015). Dissemination on the other hand

Sundborg et al. (2012) conducted a quantitative study, which examined the preparedness of nurses to provide care for women who are exposed to intimate partner violence (p.1). The study was carried out on the premise that intimate partner violence (IPV) has significant effect on women's health. Therefore, nurses need adequate preparations to identify such victims and provide suitable interventions. While the study provides significant insights relating to nurses' preparedness in

Nursing Diagnosis Care Plan Assessment Data Analysis a) Patient is a 65-year-old male Mexican-born retired bus driver with a relevant past medical history of atrial fibrillation and deep vein thrombosis treated with Coumadin who presents with hematuria. Patient sought care after witnessing blood in his urine and feeling generally weak. In addition, the patient has history of hypertension, stroke, DVT, BPH, gout, depression, anxiety, chronic bronchitis and a remote history of chicken

Data Mining in Health Care Data mining has been used both intensively and extensively in many organizations.in the healthcare industry data mining is increasingly becoming popular if not essential. Data mining applications are beneficial to all parties that are involved in the healthcare industry including care providers, HealthCare organizations, patients, insurers and researchers (Kirby, Flick,.&Kerstingt, 2010). Benefits of using data mining in health care Care providers can make use of data analysis in