NTT DATA’s Artificial Intelligence Solution Predicts Risk for Early Onset of Chronic Diseases
Tuesday, 15 September, 2020

NTT DATA, a recognized leader in global technology services, today announced that its artificial intelligence (AI) solution can make early predictions of patients at-risk of certain chronic diseases, which may be critical in enabling early and effective prevention. The solution utilizes massive amounts of health plan, pharmaceutical, clinical and lab data to train advanced AI models to derive a risk score for the onset of chronic diseases.

NTT DATA conducted a proof of concept to estimate the onset risk of chronic illnesses including type 2 diabetes, coronary heart disease, Chronic Liver Disease (CLD), Chronic Obstructive Pulmonary Disease (COPD), stroke and arthritis using noninvasive data, because in many cases, they can be effectively controlled with early detection and intervention. This can be particularly important today as currently available information indicates that people who have serious underlying medical conditions might be at higher risk for severe illness from COVID-19.

The at-risk patient predictions for chronic conditions were accomplished by using a Bayesian model that allows healthcare organizations to combine prior information about a population with evidence from a sample to guide the statistical inference process. An aggregate dataset comprised of medical diagnoses, medical procedure/services, medications, health checks and lab results from more than 5 million patients across 13 million claims was leveraged to understand the disease progression.

“For years doctors, scientists, organizations like WHO and CDC, and many community groups have been on a crusade to combat the constant growing threat of chronic diseases across the globe. In high-income countries, chronic diseases have long been the leading causes of death and disability', stated Shashi Yadiki, President, Health Plan Segment, NTT DATA Services. “Globally, more than 70% of deaths are due to chronic diseases, in the United States it is more than 87%. At NTT DATA, we are committed to building state of the art technology solutions to help combat these challenges.”

""Chronic diseases kill 40 million people every year, 70% of the planet's deaths, according to the WHO. And, at an early age, they especially affect developing countries. Therefore, in Latin America, fighting chronic diseases is crucial, both from the point of view of prevention and in terms of improving the quality of life of patients", commented Alejandro Morán, global head of Public Sector and health, everis. "The use of artificial intelligence is a key technology for the future in the face of this challenge".

NTT DATA strives to harness the potential benefits of AI through activities of its global digital offerings, technology trends analysis (NTT DATA Technology Foresight), and AI Center of Excellence, an initiative that is responsible for developing and disseminating AI technology. In addition, the company actively promotes research and development of AI to improve the technology and its application including explainable AI.

NTT DATA’s AI predictive model for early detection may assist patients across the world adopt preventive measures to help avert chronic disease before onset. Timely preventive measures may result in better patient care outcomes and have the potential to save millions for dollars for both health plans and patients.

Hidenori Chihara, Executive Vice President, Head of Public Sector 2 said, “In Japan, which faces an aging society, increasing medical costs is a big issue due to an increase in chronic diseases associated with aging. NTT DATA has long been working on this issue by developing an AI solution that predicts the risk of developing lifestyle-related diseases based on the results of medical checkups. In the future, NTT DATA will contribute to solving global issues by integrating this technology with NTT DATA Services' AI engine for disease prediction and sublimating it as a more accurate prediction service by utilizing medical and health data other than health checkup results.”