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AI-led analytics have the ability to efficiently and effectively make an impact on quality of care across the global healthcare industry

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Shub Bhowmick, CEO and Co-founder, Tredence in an interaction with Express Healthcare talks about the role of AI-led analytics in providing the value-driven health

COVID-19 has sped up the need for innovation in healthcare. More than ever, data and actionable insights are essential. Tell us how AI-led analytics is contributing to value-driven health and how it could help to transform health outcomes.

Clearly, the pandemic has exacerbated the already existing challenges in health care, highlighting the need for innovation and insights to spark change and improve outcomes across the entire healthcare spectrum. Analytics can make this difference.

AI-led analytics, in particular, have the ability to efficiently and effectively make an impact on quality of care and cost of care across the global healthcare industry. While analytics have been supporting change and innovation in health care for many years, we often see what we call a “disparate data” issue. A recent study showed that nearly one-third of data worldwide is produced by the healthcare industry, however, many healthcare providers are data-rich but insights-poor. Data often gets stuck in silos and disparate systems, making it difficult, if not impossible, for healthcare providers to drive decision intelligence and faster value creation. Notably, these data disparities result in a whopping $309 billion loss annually to the U.S. economy.

While data has helped providers address challenges throughout the pandemic and prior, it is absolutely critical that data represents diverse population and that it is used to manage the full lifecycle, from data ingestion to data quality to data cataloging to data provisioning. Cutting-edge analytical insights can combat healthcare-related uncertainties and cost- and care-related challenges with scalable AI solutions.

Improving time-to-value and self-service analytics for different user personas can simplify practice management and help organizations achieve their strategic goals based on data. AI-led analytics also enable organizations better understand the populations they serve with predictive models and support specialty lines of business.

Finally, last mile adoption—or the gap between insight creation and value realization—is critical to solving the dual issues of patient/clinical care and cost of care across the system. Fortunately, AI and ML can impactfully address that challenge with custom industry insights. When organizations are open to innovation, there is a much clearer path to value-based care.

What motivated you to create a dedicated healthcare analytics entity HealthEM.AI? How is HealthEM.AI helping healthcare providers with decision intelligence and in tackling data-related problems in healthcare?

HealthEM.AI has been an idea, a philosophy, and, most importantly, an opportunity to change our mindset. After investing a wealth of time and energy and bringing in new leadership in this area, we were thrilled to announce the launch, because it allows us to enter new markets and territories and opportunities. This innovation in healthcare is close to my heart and something that I’m incredibly passionate about, particularly its ability to solve real-world problems.

The pandemic has put tremendous pressure on the healthcare industry, causing data disparities costing billions of dollars. I think now is absolutely the right time for a solution that offers scalable analytical interventions to combat all of the issues and challenges that surround the cost of delivering quality care while enhancing overall results. In a nutshell, HealthEM.AI simplifies complex medical and practice management data such as claims, EMR, labs vitals from all points of care, streamlines vast amounts of information, and proceeds to help organisations realize their strategic goals based on insights and predictions from their data. This is a result of recognizing industry challenges and aiming to efficiently bridge the gap between direction and decision.

In addition, HealthEM.AI provides a real opportunity to be creative and to be open to innovative thinking in healthcare. We have the entrepreneurial mindset and have seen how AI/ML analytics has impressively transformed other domains such as CPG and retail, which can provide lessons that extend to other industries as well.

At HealthEM.AI, we believe that the foundation is key and that we must solve the basic problems before jumping into complex issues. Finally, it is important to address issues with a focus on value-based care and a value-based mindset, for employees and organisations alike.

Specifically, how is HealthEM.AI addressing the dual challenges of patient care and cost of care?

This dual focus is what HealthEM.AI is all about, since patient care and cost of care are the biggest challenges for the healthcare industry.

Artificial intelligence and machine learning-led data analytics can significantly impact both patients and healthcare organizations, enabling greater value-based care. For example, data analytics can identify at-risk populations, highlight inefficient or wasted use or resources (network leakage, high-cost chronic cohorts), track performance such as cost and outcomes at an individual or organization level, and streamline performance through its real-time intelligence. Healthcare systems can use the information they glean to maximize revenue through better allocation of resources and bolster patient and clinical care.

Additionally, such information can serve to provide feedback on practitioners and their care to effect improvements in patient experience. Value-based care initiatives can also impact performance and increased use of best practices. Electronic health records (EHR), for instance, share details that can help providers reduce costs by reducing unneeded procedures.

Learning to better predict risk helps with both cost of care and patient care. When you know which patients are at risk and can provide early interventions, the cost savings are massive. Reducing hospitalizations and intensive care visits is crucial to solving these challenges. Likewise, patients receive the personalized care that can help them live longer and better.

Finally, better data makes it easier for organizations to collaborate and work together to solve problems that will exist past the pandemic.

How are you planning to nurture a product-first culture at HealthEM.AI? What are your plans to build a broader ecosystem around HealthEM.AI accelerate innovation and value for clients?

As a solution-oriented company, product development is a natural and logical extension of our expertise, which is supported by our partner ecosystem, which is focused on co-developing and building solutions. HealthEM.AI will help customers adopt a data-driven culture to counter the pervasive uncertainties associated with cost and outcomes; it manages the overall innovation funnel and moves ideas into impactful actions with pre-built AI accelerators and toolkits.  All of this highlights our product-first culture and provides room to grow and innovate in the future.

Ultimately, HealthEM.AI opens greater opportunities for ingenuity and the adoption of more innovative thinking in healthcare. With a full slate of services and solutions, we continue to bring value to each client and to a broader range of industries across the globe.

The health care industry produces an enormous amount of data and is expected to grow at a 48 per cent rate year over year. However last-mile adoption of analytics has always been a challenge in healthcare. Can you share how HealthEM.AI can bridge the gap between directions and decisions?

That is our ultimate focus at HealthEM.AI—sparking that real difference between idea and action. What we have learned over time is that identifying the right problems to solve is often even more challenging than determining how to solve then. There is a lot of low-hanging fruit and opportunity in health care because of the excess spending and sometimes inefficient cost processes. Further, many of the current outcomes leave a lot to be desired as well, providing a long runway for growth and action.

Everything we do at HealthEM.AI consists of a data-based, product-first approach with actionable analytics. Our products are designed to complement those within current organizations, rather than require a “rip and replace” start from scratch.

Healthcare organisations require scalable AI solutions that truly understand industry and patient problems. By tackling the recognised issues with data, providing the full lifecycle of data management and delivering on cutting-edge analytical insights, HealthEM.AI is designed to transform the healthcare industry by solving the last-mile challenges of patient care and cost of care.

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