Beginning with AMGA in March and wrapping up with AHIP in June, healthcare leaders are grappling with game-changing, industry-shifting challenges, inside and out. As your trusted data activation partner, we at Lightbeam have compiled our take on the top takeaways so far. More to come.
I. The Real Cost of Staffing Challenges and Burnout
Staff shortages and caregiver burnout continue to concern healthcare industry leaders. According to the recently published KLAS Arch Collaborative report, burnout rates among physicians and nurses are declining slightly, but they remain above pre-pandemic levels, with staffing shortages emerging as a primary factor. Based on KLAS data collected from more than 20,000 physicians and 32,000 nurses between January 2022 and August 2023, the report also found that clinicians want improved staffing and better alignment from leadership, greater electronic health record (EHR) efficiency, and better pay.
Meanwhile, those who report they are starting to feel burned out cite concerns about efficiency, while those who are completely burned out cite concerns related to their organizational operations more broadly. Moreover, the severity of clinician burnout and the likelihood of their leaving the organization are strongly correlated.
Top factors contributing to clinician burnout:
| Issues | % of Physicians | % of Nurses |
|---|---|---|
| Staffing shortages | 56% | 65% |
| Too many bureaucratic tasks | 54% | 29% |
| A chaotic work environment | 28% | 39% |
| No control over workload | 39% | 18% |
| After-hours workload | 45% | 11% |
Burnout is consistent across work environments, but it differs by organization type. The report concludes that physicians and nurses working in community health systems are the most affected, likely because these organizations experience higher turnover rates that result in increased workloads and less support.
Besides staffing shortages, lack of role-based EHRs personalization and the need for EHR education are key factors. Too many repetitive tasks and an abundance of errors also contribute to the burnout. Given this sobering reality, digital transformation and smart AI integration have been top priority topics during this conference season. As agentic AI/AI agents replace GenAI moving forward, healthcare organizations will need a portfolio management approach to AI to manage effective integration.
II. The Status of Healthcare AI Adoption: What’s Next?
AI spending in healthcare and life sciences is projected to grow from $11.6 billion in 2024 to $19 billion by 2027, with a five-year compound annual growth rate (CAGR) of 16.6%, per Gartner. That is astronomical spend that demands a strategic understanding of organization priorities and the tools that will enable them.
Except for their interest in a few ambient listening use cases, most CIOs, CTOs, CDOs, and CAOs state that AI offerings from eager AI startups are “solutions looking for problems” with little relevance for their most pressing challenges. Healthcare providers are frustrated as they attempt to “cut through the noise” and find relevant, purposeful use cases for AI in healthcare that deliver value and ROI, especially with all the disproportionate hype around GenAI and LLMs.
They are disappointed because they have not seen the value and results associated with these GenAI efforts which have not proven its efficacy except for ambient clinical intelligence (ACI) or ambient listening. As a matter of fact, only 43% of all healthcare organizations who have invested in AI have seen any or significant ROI from their investment.
III. Increasing Interest in and Adoption of Agentic AI and AI Agents
Given the diminishing returns from Gen AI/LLMs, agentic AI/AI agents are becoming increasingly attractive and relevant. We are approaching an era where AI will be synonymous with agentic AI/AI agents and hybrid and multimodal AI as part of an integrated approach. This year, venture firms and the GenAI startups they have spawned will be rapidly moving their investments into AI agents to reposition their brands as agentic AI innovators vs. GenAI integrators. Here is a summary of the differences:
Table 1. Key Differences (Attributes/Features) between Agentic AI/AI Agents and Gen AI/LLMs and Primary Use Cases in Healthcare.
As AI deployment matures, a hybrid or multimodal portfolio management will most likely deliver the greatest payback, value, and ROI that have eluded early GenAI adopters. Stay tuned and follow Lightbeam as we expand our advanced, purpose-built platform with the power of AI—customized to alleviate administrative burden and transform patient outcomes.
As always, I welcome your comments and feedback via email at ade@lightbeamhealth.com.
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