Artificial Intelligence (AI) and cognitive computing to generate savings of over $150 billion for the healthcare industry by 2025, anticipates Frost & Sullivan.
According to the research firm, these technologies are mostly used in healthcare to deal with the complexity and growth of medical data. Some of the real-world benefits of AI-enabled solutions are automated disease prediction, personalisation of treatment pathways, intuitive claims management, and real-time supply chain management, which promise to ensure higher profitability and sustain competitive advantage for payers, providers and pharmaceutical enterprises. However, their uptake in healthcare IT has been slow due to strategic and technological challenges. So far, only 15-20 per cent of end users have been actively using AI to drive real change in the way healthcare is delivered, a report published by Frost & Sullivan reveals.
“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 personalised 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.”
Frost & Sullivan’s recent analysis, Artificial Intelligence Market—Key Application Areas for Growth in Healthcare IT, Forecast to 2022, examines key AI vendors as well as forecasts global revenue for primary healthcare IT segments that leverage AI to augment product functionalities. In addition, it assesses the competitiveness of 10 key markets that pioneered AI in healthcare. In total, this market is expected to grow to $6.16 billion at a compound annual growth rate (CAGR) of 68.55 per cent between 2018 and 2022.
According to the report, in the next three to five years, the status-quo is going to improve dramatically. Democratisation of AI is now made possible by big IT companies such as IBM Watson Health, Microsoft, Google, Philips, GE Healthcare, Amazon and Salesforce, which are offering cost-effective infrastructure support to modular and speciality-specific vendors, striving to help end users embrace precision diagnosis, treatment and follow-up for patients and their family members across the care continuum.
Currently, the United States is 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 has already established its dominance in AI, while Japan and India are gradually establishing footprints. Europe, on the other hand, is struggling to pioneer AI innovations due to restrictive data policies.
Healthcare IT companies that are eager to expand 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 utilisation data.
Combining patient-generated data with academic evidence to create personalised treatment options.
Employing clinical documentation improvement (CDI) to allow providers to help physicians and coders reduce individual burn-out. 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.
“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,” noted Chatterjee. “More importantly, one must realise that patientgenerated data which AI platforms interpret has multiple utilities for diverse healthcare stakeholders. Fully informed consent from patients coupled with 100 per cent compliance with stringent data usage regulation has to be ensured to remain relevant in the market.”
