Enabling Higher-Quality Patient Care
Of the many use cases for AI in Healthcare, the biggest drivers center around empowering providers to deliver better, more cost-effective care for patients. AI-powered clinical decision support (CDS) tools can aid in developing accurate, appropriate and actionable diagnostic or treatment recommendations – an important outcome considering overtreatment/undertreatment of care can account for up to 30 percent of healthcare costs. CDS can also help reduce clinician burnout, enhance the clinician experience and increase productivity.
Revolutionizing Clinical Research and Discovery
AI is improving clinical trials– supporting diversity in recruitment and innovation in operations to ensure all populations have equitable access to breakthrough medical technology faster than ever before. Real-world data coupled with ML and natural language processing (NLP) can help providers enhance clinical trial design, feasibility and execution; reach underrepresented populations; compress study timelines; and improve life cycle management.
Building Healthcare Supply Chain Resiliency
Historically, the healthcare sector lacked the ability to predict when a product might become short. Longitudinal visibility across the supply chain, where providers can see demand signals, point-of-use information and supplier resiliency metrics, is vital to accurately manage forecasting and predict supply shortages that can compromise quality patient care (think of the COVID-19 pandemic where shortages of personal protective equipment left clinicians, nurses and other healthcare workers ill-equipped to care for patients).
Predictive models driven by data shared between suppliers and providers combined with ML can help provide this much-needed longitudinal visibility. Armed with these insights, suppliers can anticipate increased demand for planning production, managing inventory and preventing shortages – in and out of a pandemic.
Optimizing the Healthcare Workforce
Staffing shortages in healthcare continue to create challenges, and if today’s trends continue, one study projects more than 6.5 million U.S. healthcare professionals will permanently leave their positions by 2026, while only 1.9 million will step in to replace them – leaving a national industry shortage of more than 4 million workers.
Workflows automated with AI capabilities can help extend scarce labor resources, reduce work fatigue and burnout, and enable operational and cost efficiencies.
