Part II: Frontline tech with a human touch
By Julie Dibble
Editor and Senior Writer
Once the stuff of sci-fi lore, artificial intelligence (AI) is now very much in the waiting room—and the exam room—of modern healthcare. From chatbots that triage symptoms to predictive algorithms that guide diagnoses and treatment plans, AI is reshaping the way providers and patients interact in real time. It’s not just changing how care is delivered—it’s also redefining the rhythm of frontline medicine, as clinical intuition meets machine intelligence.
In this second installment of our blog journey through AI’s impact on healthcare, we’re taking a look at how providers and patients are interacting with this enigmatic third party.
Predicting Population Health
Population Health Management (PHM) has gained traction in the past decade as a key component of value-based care models that incentivize payment and reimbursement based on patient outcomes, experience, and efficiency. PHM focuses on a given population of patients, rather than each individual, to collectively prevent and address conditions common to that group. The viability of PHM depends on big data, which enables more accurate analysis of patients and their risk factors for disease.
This is where predictive AI shines.
By aggregating massive amounts of patient data—such as medical histories, social determinants of health, and genetic predispositions—AI can forecast the incidence of disease within a population more accurately than ever before. Prevention programs, patient education, and enhanced screenings can then be implemented with precision (read: efficiency), increasing the odds for positive outcomes. Meanwhile, treatment plans and protocols for managing chronic disease can be optimized for entire populations and subpopulations, rather than for one patient at a time.
While the full effects of such efforts will only become evident in the long term, AI’s impact on the logistics of PHM has been more immediate. The administrative burden of chronic disease management within a population is immense. AI’s ability to coordinate care and streamline workflows has the potential to improve care plans for patients, helping them obtain treatment more quickly.
A . . . Eye?
In many cases, AI technology can “see” things that the human eye and brain miss, which may mean—un-hyperbolically—life or death for patients. Brain scans, bone X-rays, pathology analyses, skin lesion classifications, colonoscopies, and cardiovascular scans are just some of the precision diagnostics that have been accurately performed by AI. Using deep learning, generative AI processes complex data input from such images and reports to provide insight.
Clinicians across several specialties have reported that using AI at some point during diagnosis can be helpful, save time, and sometimes catch risk factors and anomalies that they otherwise would have missed. Radiologists, for example, may delegate the first pass of a scan to AI for initial measurement of fat and muscle mass when assessing whether a tumor is present. Cardiologists have been able to utilize the technology to assess calcium levels in coronary arteries—a major predictor for stroke within the next 5 or even 10 years.
Similarly, researchers at Mayo Clinic have found that AI can automate the time-consuming process of measuring kidney volume—an important diagnostic process that, when done by humans, involves detailed analysis of several slides that can take 45 minutes per patient. Reducing the duration of the process to mere seconds greatly streamlines the assessment and treatment of polycystic kidney disease.
Technology That Cares
The uses of AI in healthcare are not limited to the back of the house. Several organizations and providers have brought AI chatbots to the front lines of patient care, using these tools as one of the initial contact points for patients. In this form, conversational AI interacts with patients by gathering their intake information and answering general questions.
Patients can even take AI with them on the go, as it’s integrated into many of the ubiquitous health monitoring devices that top today’s accessory trends. Gleaning insights from wearable devices, the tech analyzes habits, sleep, exercise, and general wellness to either report back to a provider (if the device is medically monitored) or simply make predictive forecasts about risk factors.
The Human Touch
The proverbial elephant in the room, of course, is whether AI will replace providers in healthcare. The short answer is “no,” according to the American Medical Association (AMA). In general, healthcare stakeholders are enthusiastic about the possibilities of AI but are still cautious about relying solely on tech over touch. Calling the tool “augmented intelligence,” the AMA stresses that the use of AI is enhancing and assisting healthcare professionals, not replacing them.
Whether it’s a nurse consulting an AI tool for quick care-path recommendations or a patient using a virtual assistant to manage chronic conditions between visits, the line between human and digital support is becoming increasingly blurred. The promise? More personalized, efficient, and proactive care. The challenge? Ensuring that technology enhances—but does not replace—the deeply human side of healing.
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Julie Dibble brings nearly 20 years of strategic and creative content development to her role on the Encompass team. While her expertise and experience span several industries and platforms, she primarily applies her skills in the realm of market access, policy, and the inner workings of the US healthcare landscape to a variety of projects for Encompass’s clients and partners.
