Background In our competitive health care environment, measuring the experience of family members of patients in the intensive care unit to ensure that health care providers are meeting families’ needs is critical. Surveys from Press Ganey and the Centers for Medicare and Medicaid Services are unable to capture families’ satisfaction with care in this setting. Objective To implement a sustainable measure for family satisfaction in a 12-bed medical and surgical intensive care unit. To assess the feasibility of the selected tool for measuring family satisfaction and to make recommendations that are based on the results. Method A descriptive survey design using the Family Satisfaction in the Intensive Care Unit 24-item questionnaire to measure satisfaction with care and decision-making. Results Forty family members completed the survey. Overall, the mean score for families’ satisfaction with care was 72.24% (SD, 14.87%) and the mean score for families’ satisfaction with decision-making was 72.03% (SD, 16.61%). Families reported that nurses put them at ease and provided understandable explanations. Collaboration, inclusion of families in clinical discussions, and timely information regarding changes in the patient’s condition were the most common points brought up in free-text responses from family members. Written communication, including directions and expectations, would have improved the families’ experience. Conclusion Although patients’ family members reported being satisfied with their experience in the intensive care unit, there is room for improvement. Effective communication among the health care team, patients’ families, and patients will be targeted for quality improvement initiatives.

The European Union multi-disciplinary Personalised RNA interference to Enhance the Delivery of Individualised Cytotoxic and Targeted therapeutics (PREDICT) consortium has recently initiated a framework to accelerate the development of predictive biomarkers of individual patient response to anti-cancer agents. The consortium focuses on the identification of reliable predictive biomarkers to approved agents with anti-angiogenic activity for which no reliable predictive biomarkers exist: sunitinib, a multi-targeted tyrosine kinase inhibitor and everolimus, a mammalian target of rapamycin (mTOR) pathway inhibitor. Through the analysis of tumor tissue derived from pre-operative renal cell carcinoma (RCC) clinical trials, the PREDICT consortium will use established and novel methods to integrate comprehensive tumor-derived genomic data with personalized tumor-derived small hairpin RNA and high-throughput small interfering RNA screens to identify and validate functionally important genomic or transcriptomic predictive biomarkers of individual drug response in patients. PREDICT's approach to predictive biomarker discovery differs from conventional associative learning approaches, which can be susceptible to the detection of chance associations that lead to overestimation of true clinical accuracy. These methods will identify molecular pathways important for survival and growth of RCC cells and particular targets suitable for therapeutic development. Importantly, our results may enable individualized treatment of RCC, reducing ineffective therapy in drug-resistant disease, leading to improved quality of life and higher cost efficiency, which in turn should broaden patient access to beneficial therapeutics, thereby enhancing clinical outcome and cancer survival. The consortium will also establish and consolidate a European network providing the technological and clinical platform for large-scale functional genomic biomarker discovery. Here we review our current understanding of molecular mechanisms driving resistance to anti-angiogenesis agents, the current limitations of laboratory and clinical trial strategies and how the PREDICT consortium will endeavor to identify a new generation of predictive biomarkers.

The organizational structure for the Master of Science in Nursing's online program at Sacred Heart University offers a remarkably different innovative faculty model. Full-time, doctorally prepared faculty reside in several different states and teach online but are fully integrated and immersed in all aspects of the college of nursing. This untraditional model, which has proven to be successful over time using best practices for online education, is replicable and offers an innovative option for online learning.

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