The Growing Demand for AI Solutions in Health Care: Insights from Deloitte

The potential for hospitals to utilize artificial intelligence (AI) tools to address unmet needs, reduce costs, reduce clinician burnout, and more are explored in a new white paper from Deloitte. 

With 94% of C-suite executives recognizing AI as crucial to their success in the next 5 years, the demand for AI solutions is rapidly growing, notes Deloitte. Hospitals spend 56% of their total operating revenue on labor and financial pressures may be exacerbated by the end of pandemic funding. High turnover, supply costs, and administrative expenses were also cited as major struggles for health care systems that could be alleviated with AI. 

Deloitte explored the potential of AI technologies, used independently or combined, to create solutions for providers to drive quality care outcomes and revenue collection. Examples include predicting patient demand, optimizing operating room blocks, accelerating prior authorizations, revolutionizing supply management, automating appeal letter generation, predicting staffing needs, and identifying health equity gaps. Other use cases exist to improve margins, boost efficiency, reduce clinician burnout, and enhance patient care with generative AI and automation.

Scaling AI within hospital organizations has proven challenging, with issues stemming more from the ability to scale rather than the technology itself. Deloitte conducted a survey that found change anxiety, value identification, and data integration to be key challenges in AI implementation. As organizations progress in their AI initiatives, new barriers emerge, including maintenance of machine learning models and talent scarcity. Strong leadership and focused investment were highlighted as crucial to maintaining AI value and overcoming challenges that may not be immediately apparent. Some AI-driven health care organizations are already seeing benefits, such as improved throughput, increased hiring speed, streamlined financial processes, and significant cost savings.

Strategic next steps for reducing financial pressures with AI depend on specific goals and plans. Organizations can invest in AI business models and solutions to support clinicians and decrease margin pressures. Selecting use cases that deliver quick results and accelerate outcomes can help drive internal changes and benefits of AI. Adaptation of governance and AI operations, as well as elevating talent beyond technical skills, are crucial for the successful deployment and implementation of AI in organizations.

A Deloitte study noted the prevalence of AI bias within organizations may affect decision-making and damage trust. In sectors like health care, bias in algorithms can lead to reduced access and quality of care for certain communities. Organizations must understand how AI models impact outcomes for different groups and address potential risks like bias and privacy. Adopting an ethical AI framework can lead to better outcomes and increase confidence in AI solutions.

Deloitte also reviewed its current portfolio of AI-enabled solutions including partnerships and frameworks like ReadyAI™, ConvergeHealth™, HealthPrism™, designed to assist organizations at different stages of their AI journey. 

Reference

Deloitte. White paper on how AI can help hospitals strengthen their financial performance and reduce clinician burnout. 2024. Accessed March 26, 2024. https://www2.deloitte.com/us/en/pages/consulting/articles/artificial-intelligence-in-hospitals-financial-performance-clinical-burnout.html