Healthcare’s 2024 Imperative: a Pragmatic Approach to AI Innovation

AI, Healthcare
3 minute read

Artificial intelligence (AI) and automation took center stage at three major healthcare conferences this year as leaders shared the innovations they’re exploring and their road map for AI advancement. But behind the scenes, continued budget pressures call for careful scrutiny around where to invest and how.

These dual pressures—focusing on innovation to stay ahead of the curve while paying careful attention to the organization’s bottom line—call for a pragmatic approach to AI deployment. It’s an area where Consensus is uniquely positioned to provide insight, given the discussions we’re having with clients around making the right decisions on AI investment.

For instance, attendees of the J.P. Morgan Healthcare Conference largely agreed that it’s too soon to apply AI—in particular, generative AI—to automation of clinical care. It’s a case of “too much risk, too soon,” given the potential to negatively impact quality of care, the patient experience and clinical satisfaction.

More recently, as presenters at both ViVE and HIMSS shared the types of use cases being explored for large language models—including within Epic—some, like Hackensack University Medical Center CEO Robert Garrett, also discussed the need for guardrails for AI innovation. There is also “a heightened interest in ensuring AI in healthcare is credible,” according to John Halamka, MD, president of Mayo Clinic Platform.

But at a time when healthcare organizations need practical solutions for easing the impact of workforce shortages and managing the intense pressure to strengthen health equity, the need for organizations to leverage the real-world value of AI is critical.

Here are top considerations for healthcare leaders:

  • Look for ways to leverage AI to strengthen information exchange with smaller providers. No matter how large or well-resourced a health system may be, making the right care decisions ultimately depends on its ability to exchange information with organizations that weren’t eligible for EHR implementation incentives. These include some post-acute facilities, burn clinics, birthing centers, home health agencies and substance use disorder clinics. Today, progressive health systems are leveraging AI and natural language processing (NLP) to extract unstructured data from digital cloud faxes, including handwritten images. It’s an innovative approach that leverages existing technology to close gaps in information exchange and, ultimately, health equity—and it’s an affordable approach.
  • Lean into NLP and AI to strengthen referral processes. When physicians make referrals to specialists, the latest NLP and AI advancements, combined with digital fax technology, ensure that no one worries about what will happen to their electronically faxed referral request. The best solutions transform unstructured documents into structured, searchable data that EHRs can digest. Then, the structured data is automatically matched to the right patient’s record so providers can quickly act on the information.
  • Automate to take administrative pressure off staff, but do so in ways that don’t cause friction. Generative AI is increasing in popularity in various industries, including healthcare. But, healthcare organizations are rightfully skeptical about its reliability and security, and are seeking to comprehend its actual capabilities amidst all the buzz. As the technology is becoming more accessible, organizations are still understanding its full potential. For instance, generative AI could lift the patient communication burden from resource-constrained healthcare teams while opening the door to better education for patients on managing their health condition. It could also strengthen patient loyalty and trust by providing an “always on” resource for addressing patient queries. Among the top four generative AI solutions healthcare leaders plan to implement, solutions for automated, highly personalized patient communications rank second, according to a KLAS survey.

Exploring ways to leverage AI at your organization? Let’s continue the conversation.