AI’s Potential in Inpatient Clinical CareBy: Caregility Team
Traditionally, healthcare has been regarded as a laggard in embracing IT innovations, primarily due to the inherent complexity of care delivery and the stringent regulatory environment. However, this perception is undergoing a significant transformation. The widespread adoption of acute telehealth has played a pivotal role in this shift, providing care teams with valuable hands-on experience that has helped build trust in health technology. As a result, healthcare professionals have become more comfortable with and open to leveraging digital health tools in their daily practices.
This newfound receptivity to digital enablement has set the stage for a remarkable leap forward in the industry. This is evidenced by the recent surge of interest in artificial intelligence (AI) in healthcare. The proliferation of generative AI and the urgent need to find new solutions to the ongoing staffing crisis are further fueling interest in exploring AI’s place in clinical care.
Although headway has been made regarding operational use cases for machine learning-based AI in backend process improvements, healthcare teams are eager to identify and implement AI solutions that can enhance clinical workflows, produce more precise diagnoses, and improve patient outcomes. For the many hospitals equipped with synchronous, audio/video-based telehealth services at the bedside, infrastructure exists to introduce AI services at the point of care as well.
In the realm of virtual care, the evolution of intelligent telehealth endpoints has been remarkable. As telehealth has evolved from audio-only interactions to feature-rich video encounters, camera and microphone quality have improved to keep pace. One noteworthy development is the integration of edge computing capabilities into telehealth endpoints, enabling the support of AI applications. New multiplexing technology supports multiple cameras, allowing care teams to simultaneously support virtual patient engagement and video-based AI solutions.
In addition to high-fidelity camera and microphone arrays, new sensors such as radar technology are making their way into telehealth platforms. These sensors are capable of continuously capturing valuable clinical data while minimizing disruption to the care process. These advancements in telehealth are allowing care teams to infuse AI services such as Augmented Observation and Vitals Trending into bedside care processes, arming clinical teams with patient safety reinforcement tools that reduce pressure on staff and lead to better outcomes.
Promise and Precautions in Clinical AI
While the adoption of AI in healthcare holds immense promise, it also comes with its set of challenges and precautions.
In a recent interview with Healthcare IT Today editor John Lynn at the 2023 HLTH conference, Caregility Chief Product and Engineering Officer Kedar Ganta lauded AI’s ability to bring in ambient intelligence from audio, video, and sensor feeds, “whether it’s collecting vitals or documenting notes for the clinician.” This technology operates in the background, collecting vital patient information and supporting care processes without causing disruption.
Ganta does note, however, that amidst the excitement surrounding AI, the topics of trust and accountability often receive insufficient attention. Establishing patient and provider trust in AI systems is crucial. “This is where regulation comes into the picture,” says Ganta. “It’s a balance between over-regulating something versus promoting innovation.” Reliable data and transparency in AI solutions are essential for building trust, and the inner workings of AI algorithms should be shared with providers to enhance visibility into these factors.
Additionally, “providers should have the ability to override the AI decision” Ganta advises. Creating a regulatory framework and an independent body to oversee AI in healthcare is vital to address these concerns. As AI continues to reshape the healthcare landscape, these discussions about trust, regulation, and accountability are essential for harnessing the full potential of AI while safeguarding patient wellbeing.
As the healthcare industry continues to embrace these advancements, the future holds exciting possibilities for improved patient outcomes and experiences.