The generative AI revolution in primary care

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Artificial intelligence will be nothing short of transformational in primary health care. Taking the long view, the clinical applications in family and primary care practices are boundless. Especially when it comes to diagnostics, the possibilities of artificial intelligence and machine learning to optimize existing processes, hasten treatment, and reduce strain on providers are vast. When primary care physicians have the full power of tested and verified AI solutions to diagnose and treat a wider array of conditions, they will become the true north star of the patient journey.

But while the applicability of AI in clinical settings continues to mature, AI’s capability to analyze vast datasets and generate meaningful insights still has immediate potential for primary care practices, particularly when it comes to engaging patients. By leveraging AI in the right ways, at the right points in the care journey, providers can deliver more personalized care, dramatically reduced no-show rates, lower rates of readmission, improved adherence to treatment plans, and a higher level of trust between patients and their doctors. All of that ultimately drives better clinical outcomes and better patient experience.

The current landscape

In an ideal value-based care model, a patient’s PCP is the center of their care universe. Rich, frequent interactions, robust screening, and full-fledged engagement has a direct throughline to better patient outcomes. But with patient panels numbering somewhere around 1,800 - 2,000 on average, doctors and primary care practices simply don’t have the capacity for boutique-style care. Exacerbating the situation are the myriad administrative burdens that doctors and nurses grapple with every day, and the amount of “hunting and gathering” they need to do to track down basic patient information several times per day.

While technology has made some inroads in addressing these issues, there's still a long way to go. Generative AI holds promise as a tool that can streamline processes, reduce administrative load, and personalize patient engagement. By learning from patient data, AI has the potential to transform patient interactions, making them more meaningful and effective.

AI’s role in personalizing patient outreach

AI and machine learning have instant utility when it comes to unpacking the vast stores of often-unstructured conversational patient data accumulated by health care systems, hospitals, and doctors’ offices. Beyond the clinical data maintained in a patient’s medical history, each patient has a trail of data that can speak to sentiment of past interactions, preferences in terms of outreach style and medium, past points of friction, and more. By harnessing this data, AI tools can help doctors better understand—and even anticipate—patient needs and behaviors and deliver more personalized and effective preventive care.By doing so not only engages patients but also fosters a sense of trust and loyalty, encouraging them to remain active in managing their health.

What’s more, AI can seamlessly analyze patient histories and preferences, tailoring outreach accordingly. Using predictive modeling and machine learning, providers will be better able to prioritize needs, identify patient populations at risk, automatically implement the best outreach strategies, and optimize outcomes. And with all of that work humming along in the background, physicians can focus on what matters most: the time they’re spending with their patient.

By automating this level of personalization, providers can reach patients in the way they want to be reached. AI-driven personalization extends beyond mere communication. It's a robust tool for building long-term patient loyalty and trust. By delivering consistent, attentive, and tailored interactions, AI allows providers to create personalized care pathways and dramatically reinvent how they spend their time with patients.

Harnessing AI for enhanced interactions across settings

Artificial intelligence can play a crucial role in personalizing digital touchpoints. But it can also enhance person-to-person interactions, either inside the walls of a health care practice or during live telehealth appointments. When AI and machine learning models have access to past conversational data, physicians and nurses can get instant, high-level snapshots of need-to-know information at the point of care. By checking a patient profile before an appointment, for example, a doctor can learn that Mrs. Henderson, at their 2:30 appointment, utilizes lip-reading to best understand conversations in addition to her hearing aids, or that Mr. Peña, at their 3:45 appointment, had an unusually long wait time when they were previously in the office for a visit. By analyzing past interactions and surfacing them at the right time, either on a tablet or computer, AI can help in crafting personalized patient profiles that demonstrate to patients that they are seen, heard, and cared for—at every touchpoint across the care continuum. This personal touch can make a significant difference in how patients perceive their care and engage with health care providers. Furthermore, the insights and value gained from AI-driven engagement accumulates and optimizes over time, evolving with patient preferences.

The clinical and economic impact of improved patient engagement

Enhanced patient engagement, particularly at the primary care level, has direct and profound clinical implications. Primary care physicians supported by AI-driven insights are better positioned to guide their patients through their health care journey, acting as stewards who ensure that each patient receives the care they need when they need it. When AI is applied to personalize patient care, it creates an environment where patients are more likely to maintain their health routines and attend follow-up appointments, thereby reducing the risk of readmissions. On a broader scale, when this level of personalized care is provided across the population, it translates to improved population health, with fewer hospitalizations and lower health care costs.

Artificial intelligence stands at the cusp of revolutionizing primary health care, with patient engagement being a critical early area of application.By building a foundation of trust through personalized care, AI will not only enhance patient-provider relationships but also set new standards for patient loyalty and active participation in health care, leading to reduced no-shows and readmissions. While AI-driven diagnostics and other clinical applications continue to develop, there is a wealth of opportunities in patient engagement that can be leveraged right now. The future of primary health care is one where AI enhances the human touch, leading to a more personalized, efficient, and effective health care journey for all.

Suzie Sfarra, is senior vice president, product, at CipherHealth.