Today, Data, Analytics, and AI are at the core of decision-making for every organisation across the industry. While the degree of adoption and maturity varies, data analytics is being leveraged to drive transformative changes and is challenging the status quo of how organisations run their operations.
In this edition, we have with us Mayank Kumar, Director of Data Science at UnitedHealth Group, to talk about Analytics and AI within the Healthcare Industry and his journey so far.
UnitedHealth Group is a leading force in the healthcare industry, committed to shaping the future of health and well-being. As a diversified health and well-being company, UnitedHealth Group operates at the juncture of healthcare delivery, technology, and innovation, targeting to create a more connected and effective healthcare system. At the core of UnitedHealth Group’s mission is a dedication to improving access to quality healthcare and enhancing the overall health experience for individuals and communities.
Innovation is a hallmark of UnitedHealth Group’s approach, as the company actively explores and implements cutting-edge technologies to address the evolving needs of the healthcare landscape. By leveraging data analytics, digital health solutions, and strategic partnerships, UnitedHealth Group stands at the forefront of driving transformative changes in healthcare delivery and management. We have with us Mayank Kumar, Director of Data Science with Business Touch Magazine, to talk about his journey with UnitedHealth Group.
Introduction
Mayank Kumar is a professional with a background in Information Technology, holding a graduation degree. With over 13 years of experience, he specialises in Artificial Intelligence, Data Science, and Analytics. His expertise lies in the Healthcare and Life Science Industry, primarily focusing on the US marketplace.
Mayank Kumar started his career with Cognizant Analytics Practice, supporting various Life Science and Pharma companies with marketing analytics, defining salesforce strategy, and inventory forecasting.
In 2012, Mayank Kumar became one of the early members during the establishment of analytics. Over the years, he has played a pivotal role in UHG’s transformation from an operations-driven organisation to a technologically advanced and AI-driven enterprise. Mayank has witnessed and actively contributed to integrating analytics as a core component in various decision-making processes within the organisation.
Throughout his tenure at UnitedHealth, Mayank Kumar has been involved in claim analytics, healthcare fraud, waste and abuse analytics, and provider analytics. His contributions have been instrumental in addressing critical challenges for the enterprise, demonstrating his commitment to enhancing the organisation’s analytical capabilities.
Initial Challenges & Key Opportunities
In Data, Analytics & AI, Healthcare is a complex and regulated space. Hence one of Mayank’s biggest challenges had been understanding the art of the possible from a feasibility, end-user consumption, system limit, and regulations perspective.
Secondly, as Mayank started his journey, he observed that organisations in healthcare primarily operated through traditional methods. Recognising a pivotal opportunity, the companies had the potential to transform into data-driven entities.
For example, as one of the largest insurance companies in the United States, UnitedHealth possessed a wealth of data, presenting a unique chance to gain insights into member and service provider pain points. This positioned them strategically to drive substantial changes to enhance the healthcare experience. Dual-sided challenges and opportunities in educating the leadership about the untapped potential areas where analytics could provide significant value were observed.
During his tenure at UnitedHealth, Mayank has assisted various operational segments in prioritising inventory to improve return on investment (ROI), enhancing audit accuracy, and transitioning from rule-based healthcare fraud, waste, and abuse detection to more advanced outlier-based dynamic detections. Navigating these challenges represented a crucialstep in positioning UnitedHealth as a forward-thinking and data-driven organisation within the emotional landscape of the healthcare industry.
New Initiatives & Strategies
Mayank Kumar undertook various initiatives during his tenure, enhancing the framework for Fraud, Waste, and Abuse detection. His collaborative efforts aimed at optimising the detection process, ensuring its integration at the forefront of the system. Additionally, the team spearheaded initiatives to minimise provider abrasion and proactively identifyservice providers’ operational challenges.
Throughout his tenure at UnitedHealth, a substantial portion of their efforts was directed towards improving medical cost savings throughput, reducing operational costs, and optimizing investments in analytics. This involved the establishment of a robust analytic framework seamlessly integrated with operating systems, facilitating AI-driven decision-making. The team’s commitment to efficiency extended to reducing the time required for analytical deployments at scale, with a strategic emphasis on ensuring that the generated insights were easily consumable by end users.
Greatest Achievements
According to Mayank, the two key achievements were successfully bridging the divide between analytical output and operational output by laying the foundation for seamless connectivity between the analytics platforms and core systems. This initiative aimed to enhance the integration and utilisation of analytical insights within the operational framework. Secondly, they addressed the challenge of presenting insights from the analytical systems in a user-friendly manner for end users.
Recognising that core operating systems were not inherently designed to accommodate analytical insights, they focused on developing strategies to make the insights more consumable and readily accessible for end users. This dual-pronged approach underscored their commitment to optimising the interface between analytical processes and operational functionalities within the organisational structure.
Leadership Style
Mayank Kumar emphasises the critical role of leadership in cultivating a high level of engagement within the team and ensuring sustained focus on delivering value. Recognising the top-down influence on organisational culture requires stressing the importance of each leader incorporating a localised version to align the team’s culture with overarching goals and vision. Upholding values include persistence, a constant desire to learn, a relentless pursuit of improvement, and a willingness to challenge the status quo for the better.
Acknowledging and appreciating teams embodying these values is a regular practice. Whether celebrating small or significant victories, Mayank highlights accomplishments within the industry and other organisational domains. This recognition serves a dual purpose – challenging the team to aspire for more substantial achievements and fostering a sense of accomplishment.
Importance Of Innovation
Within the realm of AI and technology, one must emphasise the pivotal role of innovation as a cornerstone for staying ahead of industry trends. Rather than treating innovation as a separate entity, the focus should be on integrating it seamlessly into the team’s daily workflow. The approach involves challenging the status quo, encouraging team members to question existing methods, and fostering a mindset that explores how new technologies can enhance solutions to business challenges. As part of the organisational culture, there should be deliberate allocation of time for ensuring high quality and exploration in work. This commitment ensures that the delivered output represents the optimal and most innovative approach possible, fostering a culture of continuous team improvement.
Goal For 2024
In the upcoming 12-18 months, Mayank’s commitment is to concentrate efforts on stabilising and scaling the existing business victories achieved in 2023. The primary focus will involve supporting engagements to reduce operational costs and enhance constituent experience. Technologically, there will be a significant emphasis on instilling operational discipline in creating analytical value, agile delivery, and developing and deploying analytical frameworks at scale.
In addition to these priorities, a substantial focus would go towards exploring advancements in GenAI and Large Language Models, exploring AI opportunities in automation, and delving into Graph Analytics. The objective is to thoroughly investigate and refine these technologies and their respective use cases. This strategic approach reflects a dedication to operational excellence and technological advancement.
