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Survey by The Health Management Academy Reveals Accelerating Use of AI to Overcome Workforce Challenges 

What You Should Know: – Given the severity of labor shortages and staffing constraints facing health systems nationwide, C-suite executives are turning…

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This article was originally published by HIT Consultant

What You Should Know:

– Given the severity of labor shortages and staffing constraints facing health systems nationwide, C-suite executives are turning to artificial intelligence (AI) to fill gaps and improve productivity, according to a recent survey conducted by The Health Management Academy (The Academy) with support from Outbound AI.

– Almost half of executives (47.5%) report their health system is currently using AI solutions for the workforce, while all others (52.5%) report their health system is currently evaluating or considering AI solutions for the workforce.

AI-Driven Solutions to Workforce Challenges

Executives selected to participate in the survey were verified as having a high degree of familiarity with strategic decisions surrounding AI solutions at their respective health systems, as recognized by an average score of 9.35 on a 10-point scale, wherein 10 denotes “very familiar.” The Academy used both quantitative and qualitative methods to capture insights and perspectives from a total of 40 executives at 40 leading heath systems spanning multiple geographic regions, sizes (measured by net patient revenue) and academic medical center status. Titles included Chief Information Officer, Chief Medical Information Officer, Chief Financial Officer, Chief Technology Officer, Chief Transformation Officer, and Chief Digital Officer, among others. The Academy received financial support from Outbound AI, a Seattle-based solution provider specializing in Conversation AI built for healthcare.

Key findings are as follows;

1. Back Office is Focus of AI Adoption To Date

Survey findings indicate that the typical progression of AI investments is: (1) back office, (2) clinical operations, and (3) clinical care. Back office most often includes revenue cycle, human resources and/or supply chain management, areas proven to result in “quick financial wins through cost savings.” More than three-quarters (78.0%) of executives report their health system is currently using or evaluating AI for revenue cycle management.

2. Nursing is Key Target for AI Among Clinical Workforce

Additional survey data show that although only 15.0% of executives report their health system is currently using AI for nursing, an overwhelming 82.5% report their health system is currently evaluating or considering AI for nursing. As one executive notes: “We are prioritizing where we can impact the biggest labor pain points. This is mostly in nursing.”

3. Near-Term Investments in AI for the Workforce Expected to Increase

The industry will likely see an acceleration of investments in AI solutions for the workforce. Among executives who report their health system is currently using AI solutions for the workforce, 84.5% expect a moderate to significant increase in the next one to three years.

4. Growing Interest in Conversational AI Solutions

When asked whether their health system uses conversational AI, most executives answer, “yes, we have chatbots.” While chatbots have gained traction, it is important to acknowledge they are only one of many use cases for conversational AI. Despite this knowledge gap, over one-quarter of executives (27.5%) report their health system is currently using conversational AI solutions, while all others (72.5%) report their health system is currently evaluating or considering conversational AI solutions.

5. Executives Scope Multiple Sources to Evaluate AI

Though opportunities to leverage existing technologies and partnerships are prioritized, executives are receptive to forming new relationships. The survey indicates that executives focus on real-world case studies and return-on-investment (ROI) data. They also seek recommendations from their peers. The five most important factors executives evaluate are:

– Interoperability with EHR

– Privacy and security

– Ability to augment EHR capabilities

– Anticipated return on investment

– Expected value (hard and soft) across 3+ years

artificial intelligence


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