Behaviors That Eliminate Health Disparities for Racial and Ethnic Minorities: A Narrative Systematic Review

Within the health care provider-health care recipient relationship the communication must be culturally competent to eliminate barriers to equitable health care for all Americans. This assertion has conceptual grounding in Public Law 106-129 (the Health Care Research and Quality Act of 1999) and Public Law 106-525 (the Minority Health and Health Disparities Research and Education Act of 2000). This narrative systematic review examines this assertion by using selection and exclusion criteria to gather interventions, assessments, and testimonies conducted from 2000-2007. Reports that were not eliminated via these criteria were analyzed to determine the effect of specific practices that were undertaken in interventions, assessments, and testimonies. Which practices does research propose as indispensable to efforts to eliminate health disparities for racial and ethnic minority health care recipients? Findings indicate that culturally competent behaviors by providers and recipients promote effective intercultural communication that eliminates health care disparities, and removes obstacles to care

One Size Does Not Fit All: Meeting the Health Care Needs of Diverse Populations

Proposes a framework for meeting patients' cultural and linguistic needs: policies and procedures that support cultural competence, data collection, population-tailored services, and internal and external collaborations. Includes a self-assessment tool

Predicting Pancreatic Cancer Using Support Vector Machine

This report presents an approach to predict pancreatic cancer using Support Vector Machine Classification algorithm. The research objective of this project it to predict pancreatic cancer on just genomic, just clinical and combination of genomic and clinical data. We have used real genomic data having 22,763 samples and 154 features per sample. We have also created Synthetic Clinical data having 400 samples and 7 features per sample in order to predict accuracy of just clinical data. To validate the hypothesis, we have combined synthetic clinical data with subset of features from real genomic data. In our results, we observed that prediction accuracy, precision, recall with just genomic data is 80.77%, 20%, 4%. Prediction accuracy, precision, recall with just synthetic clinical data is 93.33%, 95%, 30%. While prediction accuracy, precision, recall for combination of real genomic and synthetic clinical data is 90.83%, 10%, 5%. The combination of real genomic and synthetic clinical data decreased the accuracy since the genomic data is weakly correlated. Thus we conclude that the combination of genomic and clinical data does not improve pancreatic cancer prediction accuracy. A dataset with more significant genomic features might help to predict pancreatic cancer more accurately

ILR Faculty Research in Progress, 2014-2015

The production of scholarly research continues to be one of the primary missions of the ILR School. During a typical academic year, ILR faculty members published or had accepted for publication over 25 books, edited volumes, and monographs, 170 articles and chapters in edited volumes, numerous book reviews. In addition, a large number of manuscripts were submitted for publication, presented at professional association meetings, or circulated in working paper form. Our faculty's research continues to find its way into the very best industrial relations, social science and statistics journals.ResearchinProgress_2014_15.pdf: 17 downloads, before Oct. 1, 2020

Shared Value in Emerging Markets: How Multinational Corporations Are Redefining Business Strategies to Reach Poor or Vulnerable Populations

This report illuminates the enormous opportunities in emerging markets for companies to drive competitive advantage and sustainable impact at scale. It identifies how over 30 companies across multiple sectors and geographies design and measure business strategies that also improve the lives of underserved individuals