US-based providers lose an estimated $260 billion to $270 billion annually due to poor financial risk management and lack of infrastructure to support data-driven business decisions. For every dollar claimed, private and public payers on average offer a reimbursement of 86 cents to providers, resulting in a negative margin of 14% per dollar per patient. Large integrated hospitals incur operating expenses of between $200 million and $700 million annually to embrace value-based payment programs that require an interoperable IT ecosystem that consists of an integrated electronic medical record (EMR), a payer-agnostic revenue cycle management platform, and a cross-functional supply chain management solution.

Healthcare data analytics solutions collect data from these underlying sources and normalize evidence at patient, provider, and payer levels. They allow healthcare end users to identify gaps in care early and to intervene with evidence that quantifies how to save money, increase revenue, and improve outcomes. As a result, the US healthcare data analytics market is growing rapidly as all types of healthcare organizations rely on IT-enabled data management, business intelligence, and quality reporting capabilities to transform their clinical performance, operational agility, and financial competitiveness.

Early adopters have shown the intent to move beyond traditional use cases of analytics to pioneer advanced applications such as imaging analytics, genomics analytics, social vulnerability index classification, automated claims preadjudication, and real-time supply chain management reporting. Consequently, more than 150 companies are offering both modular and plug-in based analytics solutions in the US marketplace.

Of these, 70 have demonstrated adequate levels of technological sophistication to meet the current and future industry needs;
40 out of 70 companies have an industry-leading ability to offer advanced clinical, financial, or operational analytics for a wide range of customers, including payers, providers, life sciences, and government agencies. These 40 companies are broadly classified as leaders and challengers.
-- Companies scoring high on both growth and innovation are considered leaders. They have a history of being at the forefront of innovation.
-- Companies scoring higher on innovation but delivering lower growth, and those that are implementing visionary innovation around specific analytics capabilities but embracing slower growth, are considered challengers.

Finally 14 out of 40 companies have been profiled to demonstrate their visionary capabilities in the US healthcare analytics market.
-- Leaders: Six companies are positioned higher on the growth and innovation indices as they cumulatively manage or process data of 90% of US patient population, yield positive margins with revenue worth $4 billion to $5 billion from data analytics solutions, and invest as much as $1 billion every year to build progressive capabilities around data analytics
-- Challengers: These companies have grown at a slower pace compared to leaders but have demonstrated a strong appetite to incorporate more advanced technologies such as artificial intelligence (natural language processing and machine learning) and blockchain to personalize clinical diagnosis, automate financial risk management, and consider patients’ social determinants of health. Some continue to innovate new strategies to optimize performance of one specific healthcare vertical.

The Frost Radar reveals the market positioning of companies in an industry using their Growth and Innovation scores as highlighted in the Frost Radar methodology. The document presents competitive profiles on each of the companies in the Frost Radar based on their strengths, opportunities, and a small discussion on their positioning. Frost & Sullivan analyzes hundreds of companies in the industry and benchmarks them across 10 criteria on the Frost Radar, where the leading companies in the industry are then positioned. Industry leaders on both the Growth and Innovation indices are recognized as best practice recipients.

Author: Koustav Chatterjee