Artificial intelligence and generative AI platforms will play an integral role in advancing treatment programs, improving care models, and boosting the overall patient experience.
The healthcare technology market has long benefited from machine learning and AI-powered solutions. With the launch of generative AI, healthcare providers are now gaining access to groundbreaking technological capabilities that enable improved patient care programs, more efficient workflows, and impactful business insights. Meanwhile, artificial intelligence and machine learning systems continue to evolve and are quickly becoming a critical component of nearly every healthcare tech stack, from practice management and RCM solutions to the predictive analytic models used to diagnose illnesses and determine treatment plans.
One of the greatest things about emerging AI technology is that it is democratizing access to highly effective software platforms for medical groups of all sizes, including small independent practices that lack the IT budgets of large hospital networks and private equity-owned medical groups. The advancements we’ve seen with generative AI solutions during the past year will have a massive impact on healthcare systems.
The Impact of Generative AI On Patient Engagement Strategies
Generative AI chatbots have the capacity to enable much more meaningful patient engagement experiences, greatly enhancing ongoing connections between patients and their healthcare providers. Generative AI tools can be used to communicate with patients between visits, offering reminders on upcoming appointments and treatment plans. The use cases for these tools are far-reaching, including everything from ensuring medication adherence by patients to answering patient questions or addressing concerns—while also automatically reporting patient data to the healthcare provider and alerting care teams when a follow-up is needed.
This continuous engagement, enabled by generative AI platforms, will help maintain the patient-provider relationship and ensure patients correctly follow their treatment plans. The technology also will be able to promptly address any patient inquiries or issues that may arise, further contributing to improved patient outcomes and satisfaction.
The healthcare industry is already seeing generative AI platforms that are able to interact with patients more naturally than many previous automated tools, going beyond simple, scripted responses to frequently asked questions or pre-scripted logical flows that present the patient with a limited menu of response options (“Choose one of the following…”). Generative AI platforms can interact directly with a patient to schedule an appointment based on the patient’s needs and the provider’s availability. In this way, GenAI chatbots are helping to optimize treatment planning and foster more dynamic patient-provider relationships. As a result, patients are more likely to receive personalized, high-quality care that addresses their specific needs, ultimately leading to better health outcomes and increased patient satisfaction.
Leveraging AI-Powered Analytics to Streamline Daily Operations & Create More Efficient Workflows
Generative AI may be the new bright and shiny tool, but AI-driven predictive analytics and machine learning algorithms have been around for some time now, making truly breathtaking advances in the healthcare space. The technology has streamlined daily operations for hospitals and private practices and enabled more informed decision-making when it comes to patient care.
The key benefit of AI-powered analytics and machine learning technology is that it can analyze massive data sets and provide highly valuable insights on everything from revenue cycle management (RCM) details and claims submission trends to patient outcomes and patient engagement processes. Healthcare providers and executives implement these solutions to drive efficiencies across their organizations, but more importantly, the technology enables more informed decision making when it comes to patient care. When implemented correctly, it truly makes us all smarter.
The Inherent Challenges of AI within the Healthcare Industry
The biggest issue with AI technology within healthcare is centered on generative AI. The reality is that the technology is still new and many are concerned about its limitations. Last December, Klas Research surveyed healthcare executives and found that more than half were looking to implement a GenAI solution within the next year. At the same time, these executives reported that their biggest concerns around GenAI were accuracy and reliability.
A Generative AI platform is only as strong as the LLM (large language model) that powers it.
Before a healthcare organization can use the technology to their advantage, there must be guardrails in place to ensure the generative AI application is operating as intended and not putting patient data at risk or influencing diagnoses or treatment plans based on “bad” data.
When it comes to addressing these challenges, some will be resolved with advances to the technology. But it is also critical that the organizations implementing Generative AI have a framework in place to catch these problems when they happen.
The ASTP/ONC is actively working to ensure that AI technology is built responsibly and transparently across the industry. They established new certification requirements and a new position for Chief AI Officer. These are important steps that all healthcare technology organizations need to be mindful of to ensure that their solutions are built in compliance with the current regulatory framework.
The ONC’s HTI-1 Final Rule, which is a significant step in establishing responsible use of AI across the industry, states, “The HTI-1 rule has specific provisions to promote transparency and risk management of AI-based technologies used in health care delivery based on what we call the FAVES principles: fairness, appropriateness, validity, effectiveness, and safety.”
AI + Healthcare = A Bright Future for Patients & Providers
There are definitely reasons to be concerned about AI and generative AI implementations within various healthcare models. But the medical breakthroughs this technology will make possible across the healthcare landscape—and the positive impact it will have on practice management strategies—gives our industry much to look forward to. AI-powered tools will be used to analyze patient data and identify risks, gaps in care, and opportunities for intervention.
At a patient population scale, this same kind of data gathering and analysis can be applied to identify trends, risk factors, and opportunities for proactive interventions. Research teams and healthcare providers are already using the technology to help predict and identify cancer risks early in the diagnosis, giving patients a much-improved chance of survival.
In this new era of artificial intelligence, healthcare providers and their teams will have access to deeper insights that result in more informed decisions. What was once beyond our wildest imagination will become routine—patient outcomes will improve and daily operations will become more efficient. It is a future that will benefit everyone: healthcare providers, their staff, and the patients they serve.
