EXL announced that it has received a special award for its Analytics solution on ‘Preventive Hospitalization’ at the NASSCOM Big Data & Analytics Summit in Hyderabad on June 25, 2015. This solution was also included in the ‘NASSCOM Top 50 Excellence in Analytics’ report that was released at the Summit.
This solution helps healthcare providers identify patients at risk for hospital admission. It enables healthcare providers to anticipate or predict the needs of a patient and intervene through proactive care plans before the patient faces an emergency that necessitates hospital admission. This healthcare solution integrates more than 100 individual predictive models using techniques from the fields of statistics, econometrics, epidemiology, actuarial sciences and machine learning. These models are combined together using proprietary ensembling algorithms. According to the American Hospital Association, more than 71 million individuals in the United States are admitted to hospitals each year. A large portion of these admissions are deemed unnecessary or avoidable and cost healthcare providers upwards of $30 billion in unnecessary hospital admissions.
Vivek Jetley, Senior Vice President and Global Co-head of EXL Analytics said, “It is exciting to note that EXL has been recognized by NASSCOM for signifying excellence in analytics. It is a testament to our deep understanding of specific business challenges faced by industries and expertise in designing and applying precise Analytics solutions to create business opportunities for our clients.”
Ankor Rai, Senior Vice President and Global Co-head of EXL Analytics said, “EXL combines cutting-edge data science with deep domain expertise to deliver such powerful solutions to clients across multiple industries including healthcare. This solution from EXL has found wide applicability in the healthcare industry.” He added, “Such initiatives by NASSCOM provide a great platform to showcase how analytics-driven solutions transform legacy business processes and create dramatic impact.”
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