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AI to Save Healthcare Industry over USD 150 Billion by 2025

By HospiMedica International staff writers
Posted on 01 Oct 2018
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Image: AI in healthcare is expected to generate savings of USD 150 billion by 2025 (Photo courtesy of Shutterstock).
Image: AI in healthcare is expected to generate savings of USD 150 billion by 2025 (Photo courtesy of Shutterstock).
Artificial Intelligence (AI)-enabled solutions offer real-world benefits such as automated disease prediction, personalization of treatment pathways, intuitive claims management, and real-time supply chain management to ensure higher profitability and sustained competitive advantage for payers, providers and pharmaceutical enterprises. In spite of these benefits, their uptake in healthcare IT has been slow on account of strategic and technological challenges, with only 15-20% of end users actively using AI to bring about a real change in the way they deliver healthcare.

However, this is expected to change dramatically over the next three to five years. AI in healthcare is expected to grow at a compound annual growth rate (CAGR) of 68.55% between 2018 and 2022 to reach USD 6.16 billion. AI and cognitive computing which are being currently used in healthcare mainly to deal with the complexity and growth of medical data are expected to generate savings of over USD 150 billion for the healthcare industry by 2025.

These are the latest findings of Frost & Sullivan, (Santa Clara, CA, USA), a global management consulting company.

Large IT companies such as IBM Watson Health, Microsoft, Google, Philips, GE Healthcare, Amazon and Salesforce are now making the democratization of AI possible by offering cost-effective infrastructure support to modular and specialty-specific vendors, and striving to help end users embrace precision diagnosis, treatment and follow-up for patients and their family members across the care continuum.

The US is currently the global hub of healthcare AI due to its strong performance across seven AI maturity metrics by Frost & Sullivan: investment, incubator, infrastructure, patent, talent, global collaboration, and end-user adoption. China is already a dominant player in AI, while Japan and India are gradually establishing their footprints. On the other hand, Europe is struggling to pioneer AI innovations due to restrictive data policies in the region.

According to Frost & Sullivan, healthcare IT companies keen on expanding their business will find growth opportunities in:

Applying AI on imaging to drive differential diagnosis, which was not possible with legacy systems. They can also identify regional disease hot spots through smart assessments of historical healthcare utilization data;

Combining patient-generated data with academic evidence to create personalized treatment options;

Employing clinical documentation improvement (CDI) to allow providers to help physicians and coders reduce individual burnout. CDI’s impact on claims and denial management is critical;

Employing AI-powered revenue cycle management (RCM) platforms that seamlessly interface with providers’ incumbent payer mix and auto-adjust claims content based on each payer’s coding and reimbursement criteria.

“AI in healthcare IT allows many providers to pursue precision medicine approaches based on the real-time integration of a patient's genomic, clinical, financial, and behavioral data to improve outcomes,” said Koustav Chatterjee, Industry Analyst, Transformational Health. “For maximum impact, AI algorithms also consider the latest academic research evidence and regulatory guidelines before recommending personalized treatment pathways to high-risk, high-cost patient populations. AI is also used to expedite the process of clinical trial eligibility assessment and generate prophylaxis plans that suggest evidence-based drugs. However, physicians remain the key decision maker and should be the final authority on any AI-driven care plan.”

“To be successful, healthcare IT providers need to devise AI-based business models that fetch real benefits in the form of tangible return on investment (ROI) to end users,” added Chatterjee. “More importantly, one must realize that patient-generated data which AI platforms interpret has multiple utilities for diverse healthcare stakeholders. Fully informed consent from patients coupled with 100% compliance with stringent data usage regulation has to be ensured to remain relevant in the market.”

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