AI and analytics in healthcare: Bringing back humanity with technology

The future of healthcare is data-driven, bolstered by analytics and fueled by artificial intelligence (AI) and machine learning (ML). And with technologies like generative AI filling headlines, they promise to significantly enhance care, with new connections among primary care physicians, their patients, and other clinicians and specialists.

Combining the predictive power of analytics with the computing power of AI can improve patient outcomes and health equity and even secure the holy grail of interoperability, where different healthcare systems and platforms connect, collaborate, and share data seamlessly.

But before enterprises across the ecosystem can capitalize on AI and analytics and realize interconnected care, they need a solid vision alongside solid data and analytics foundations.

The complexity of the healthcare industry brings with it significant, long-held challenges:

• Battling health inequity: Disparities in care access and provision across different populations result in poor patient outcomes for many
• Realizing value-based care: The struggle to define and measure value between payers, providers, and other key stakeholders has held back the shift from volume to value-based models
• Plugging workforce shortages: A shortage of workers is blocking access to care
• Managing rising costs: Health System Tracker found that between 2001 and 2021, healthcare costs increased faster (3.3%) than the cost of all goods and services (2.2%), making affordability a major concern
• Easing increasing pressures: The number of people with chronic diseases and comorbidities is rising. Combined with aging and growing populations, payers and providers are under pressure to deliver effective, ongoing care

These challenges have seemed insurmountable. But now, with technology advances, there are finally effective solutions. Read the full article on Medical Economics.