A Neural Network Analysis of Treatment Quality and Efficiency of Hospitals

Objectives: Due to the escalating healthcare expenditure and the number of hospitalizations, it is becoming increasingly important for healthcare organizations to evaluate the cost and improve the quality and efficiency of treatment. Method: We deploy neural networks to examine the strategic association between hospitalization experience and treatment results. The healthcare data for the years 2009-2012 are downloaded from the Statewide Planning and Research Cooperative System (SPARCS) of the New York State Department of Health (NYSDOH). We operationalize the hospitalization experience using the indicators facility ID, procedure description, type of admission, patient disposition upon discharge, APR severity of illness, source of payment, and age group; and the treatment result using indicators hospital length of stay and APR risk of mortality Results: Our findings show that there are significant differences in length of stay and mortality rates depending on the treatment procedure. Treatment result shows a strong association with procedure and with the patients’ disposition upon discharge. Interestingly, under similar health conditions, patients who are under the public healthcare system tend to have longer length of hospital stays than others. Conclusions: We offer a portfolio of factors to be considered in evaluating patient health outcomes from hospitalization. We emphasize the need for efficient utilization of investment in healthcare, be it public or private

Preventive Healthcare: A Neural Network Analysis of Behavioral Habits and Chronic Diseases

The research aims to explore the association between behavioral habits and chronic diseases, and to identify a portfolio of risk factors for preventive healthcare. The data is taken from the Behavioral Risk Factor Surveillance System (BRFSS) database of the Centers for Disease Control and Prevention, for the year 2012. Using SPSS Modeler, we deploy neural networks to identify strong positive and negative associations between certain chronic diseases and behavioral habits. The data for 475,687 records from BRFS database included behavioral habit variables of consumption of soda and fruits/vegetables, alcohol, smoking, weekly working hours, and exercise; chronic disease variables of heart attack, stroke, asthma, and diabetes; and demographic variables of marital status, income, and age. Our findings indicate that with chronic conditions, behavioral habits of physical activity and fruit and vegetable consumption are negatively associated; soda, alcohol, and smoking are positively associated; and income and age are positively associated. We contribute to individual and national preventive healthcare by offering a portfolio of significant behavioral risk factors that enable individuals to make lifestyle changes and governments to frame campaigns and policies countering chronic conditions and promoting public health

Big data analytics in healthcare: promise and potential

Objective To describe the promise and potential of big data analytics in healthcare. Methods The paper describes the nascent field of big data analytics in healthcare, discusses the benefits, outlines an architectural framework and methodology, describes examples reported in the literature, briefly discusses the challenges, and offers conclusions. Results The paper provides a broad overview of big data analytics for healthcare researchers and practitioners. Conclusions Big data analytics in healthcare is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs. Its potential is great; however there remain challenges to overcome

Determinants of Startup Funding: The Interaction between Web Attention and Culture

Technology empowers entrepreneurs to pursue alternative funding through platforms like crowdfunding. This research explores significant startup funding factors using Crunchbase. Controlling for common factors (acquisition/funding-rounds/IPO), the research uniquely focuses on web attention - the visibility on social media - and its impact on funding. It also examines the moderating influence of startup’s home country culture (individualism/collectivism). Findings show stronger positive impact of web attention on startup funding for collectivist countries. While individualistic investors value personal goals, collectivists value collaborative goals - inclinations that align with crowdfunding behavior. Therefore while increasing web attention, crowdfunding efforts can be targeted towards collectivist countries

The Role of Information and Communication Technologies in Global Sustainability: A Review

This article discusses ways in which ICTs contribute to several aspects of global sustainability. We examine how economic development, education, energy, environment, and transportation at the country level benefit from ICTs, along with several orders of effects on global sustainability. We also examine rebound effects. The anecdotal and theoretical research suggests that the impact of ICTs is felt primarily in sustainable development. We thus identify the key challenges to be addressed in bringing about an ICTs-based sustainable world. Studying the macro impacts of ICT investments can also guide countries in setting policy and making selective investments in ICTs that will promote global sustainability