Tuesday, November 5, 2024

From symptom to treatment: Navigating the patient journey with AI

With health systems worldwide grappling with mounting pressures tied to workforce shortages and staff burnout, emerging technologies – specifically artificial intelligence (AI) integrated with virtual triage and care referral – are emerging as powerful tools to streamline patient care, improve outcomes, and reduce costs. As a medical advisor focused on AI applications in healthcare, I have been integrally involved in research and development that is transforming the patient journey, with a particular focus on care acuity alignment and early detection of critical conditions.

Recent research has broken new ground in two areas: care acuity alignment with respect to care de-escalation and escalation, and early detection of leading chronic diseases, including heart attack, stroke, pulmonary embolism, pneumonia, and asthma.


Aligning care with patient acuity levels


AI plays a crucial role in helping patients navigate the complex healthcare landscape, especially when they are uncertain about their care needs. AI has value for patients who are unclear about whether they need care in the first place, and if they do, what level of care is appropriate. Through virtual triage encounters, AI-powered systems can assess symptoms, generate potential diagnoses, and recommend appropriate levels of care acuity.

A recent study published in the International Journal of Healthcare evaluated the impact of AI-based virtual triage and care referral (VTCR) on patient care intent and seeking in an ambulatory setting. Researchers analyzed 8,088 online encounters to understand how VT influenced patient behavior in engaging various levels of care acuity. The technology is designed to evaluate patients’ care intentions and to help align patients with the appropriate care that is needed based on their clinical presentation. VTCR was found to reduce unnecessary in-person visits and promote virtual care among patients seeking care in a leading ambulatory care system.

Among the results:
  • A 19.1% increase in patients opting for virtual care options such as e-visits and telephone consultations.
  • 12.5% decrease in outpatient care seeking, including in-person and video consultations.
  • 35% of all patients altered their care seeking behaviors following VT recommendations, and among patients whose care intent differed from VT, 50% altered their care seeking in alignment with the recommendation of VTCR.

VTCR technology reduces patient uncertainty by providing clear guidance on whether self-care at home is sufficient, if a visit to their regular physician is necessary and sufficient, or if urgent care and emergency department attention is required. The AI explains its recommendations, helping patients understand the rationale behind the suggested care path.


Early detection of critical conditions


One of the most promising applications of AI in healthcare is its ability to facilitate early detection of potentially life-threatening conditions. Recent research has focused on five high-morbidity, high-mortality conditions: heart attack, stroke, asthma, pneumonia, and pulmonary embolism.

Findings revealed a significant disconnect between patients’ self-perceived acuity levels and the actual urgency of their conditions as determined by AI-based virtual triage. Substantial numbers of individuals did not intend before triage to seek the level of urgent care that they needed clinically.

By identifying these discrepancies, AI can prompt patients to seek appropriate care sooner, potentially saving lives and reducing long-term health consequences. For conditions like stroke and heart attack (myocardial infarction), where time is critical, early intervention facilitated by AI VTCR could mean the difference between long-term disability and a full recovery.


Enhancing clinical decision-making


For healthcare providers, AI-powered virtual triage systems offer valuable insights that can expedite and improve clinical decision-making. By providing a ranked list of potential diagnoses based on the patient’s reported symptoms, AI gives clinicians a head start in their assessment.

It saves time and helps to organize information, offering a clinical workflow advantage by potentially expediting the ordering of therapeutics and delivery of care to the patient. This efficiency not only benefits the healthcare system but also ensures patients receive timely, appropriate care.


Challenges and considerations


While the potential of AI in healthcare is vast, its implementation comes with challenges. Healthcare providers and administrators may initially approach AI with skepticism, requiring education and transparency about the technology’s capabilities and limitations. It is crucial to prioritize patient safety in AI design. For instance, some systems are built to slightly “over-triage” to emergency departments, erring on the side of caution rather than risking under-diagnosis of serious conditions.

Looking ahead, several exciting developments in AI-powered healthcare are on the horizon:Integration of objective clinical data: 
  • As more patients use devices like pulse oximeters and blood pressure monitors at home, AI systems will incorporate this data to enhance diagnostic accuracy and care recommendations.
  • Improved language models: Advancements in large language models (LLMs) will increase the fluidity and power of AI in healthcare applications as well as increasing patient comfort and satisfaction with VTCR.
  • Expanded condition coverage: AI systems will become more adept at identifying and managing rarer conditions and mental health issues.
  • Addressing socially stigmatized conditions: AI may provide a more comfortable platform for patients to discuss sensitive health issues like sexually transmitted diseases or substance abuse.
  • Focus on chronic disease management: As the leading source of morbidity and mortality in most nations, an increasing focus on chronic diseases in AI-based VTCR will play a larger role in long-term patient care and monitoring.
  • Tackling healthcare access and resource inequities: AI-powered virtual triage can improve healthcare access for underserved, high inequity populations, addressing long standing disparities in care.

We are at the beginning of the healthcare journey with AI-based VTCR. As AI continues to evolve, its ability to align care with patient needs, detect critical conditions earlier, refer patients for needed care, and support clinical decision-making will increase dramatically.

AI is poised to revolutionize the patient’s and the clinician’s journey, from initial symptom assessment to long-term care management. By leveraging VTCR technology to improve care acuity alignment and early detection of serious conditions, healthcare providers and plans can enhance patient outcomes, reduce costs, and create a more efficient, equitable healthcare system for all. For senior healthcare executives, embracing and integrating these AI technologies will be crucial in staying at the forefront of patient care and operational efficiency and organizational performance in the coming years.

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Monday, November 4, 2024

Can artificial intelligence contribute to improved clinical reasoning?

Researchers from the University of Minnesota Medical School, Stanford University, Beth Israel Deaconess Medical Center and the University of Virginia analyzed the efficacy of GPT-4, an artificial intelligence (AI) large language model (LLM) system, as a diagnostic tool to assist physicians’ diagnoses. The study, published in JAMA Network Open, found that physicians’ access to GPT-4 as a diagnostic aid did not result in significantly improved clinical reasoning compared to physicians left with conventional resources, including UpToDate and Google.

“The field of AI is expanding rapidly and impacting our lives inside and outside of medicine. It is important that we study these tools and understand how we best use them to improve the care we provide as well as the experience of providing it, Andrew Olson, M.D., a professor at the University of Minnesota Medical School and a hospitalist with M Health Fairview. “This study suggests that there are opportunities for further improvement in physician-AI collaboration in clinical practice.”

The study analyzed 50 total U.S.-licensed physicians across family, internal and emergency medicine. The median diagnostic reasoning score per case was 76% for the group with AI access, and 74% for the group only referencing conventional resources. The AI group spent an average of 519 seconds per case, compared with 565 seconds per case for the conventional resources group.

Researchers were able to conclude that access to GPT-4 did not significantly increase physicians’ diagnostic reasoning, although, on its own, the LLM did surpass the performances of both clinicians using conventional diagnostic online resources, and clinicians assisted by the program. These findings could prove the necessity of further research to understand how clinicians should be trained to use these tools.

Independently, the LLM demonstrated higher performance than either physician group, thereby indicating the need for training and development to achieve the full potential of physician-AI collaboration in clinical practice. At the forefront of these efforts, the four institutions behind the study announced a collaboration on a bi-coastal AI evaluation network, ARiSE, designed to further evaluate generative AI outputs in healthcare

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Friday, November 1, 2024

Physician-patient communication during initial consultation affects outcomes for chronic pain patients

A study from the University of Illinois Urbana-Champaign, published in the Journal of Health Communication, looked at 200 adults with chronic neck or back pain, and reported that effective physician-patient communication during the initial consultation can have significant implications toward patients’ overall outcomes. According to Charee Thompson, the communications professor behind the study, patients were better equipped to manage their uncertainties, including fears, anxiety and confidence in their own ability to cope with their condition, as a result of effective communication during their first consultation.

“We found that providers and patients who perceive themselves and each other as competent medical communicators during consultations can alleviate patients’ negative feelings of uncertainty, such as distress, and increase their positive feelings about uncertainties, such as their sense of hope and beliefs in their pain-management self-efficacy,” Thompson said in a university release. “Providers and patients successfully manage patients’ uncertainty through two fundamental medical communication processes—informational and socioemotional, each of which can have important clinical implications.”

Patients’ ability to both accurately describe their symptoms to physicians, and verify their understanding of physicians’ explanations and instructions, were determined to be important parts of the process. In addition, clinicians asking appropriate questions, providing clear explanations and confirming that patients understand their explanations and instructions, are crucial for the significant portion of the population currently suffering from chronic pain. According to a CDC report, 20.9% of U.S. adults—roughly 51.6 million individuals—experience chronic pain, as of 2021.

The study considered the theory of uncertainty management, which hypothesizes that people, when faced with uncertainty about a health condition, will appraise it and make a decision about whether it would be beneficial, or a threat, to obtain more information. Patients may look for new information about a new symptom they’re experiencing in order to mitigate their anxiety, or they may choose to avoid any information, so they can maintain hopeful uncertainty, which could also be considered blissful ignorance.

The study looked at several clinics and programs that treat diseases and injuries of the brain, spinal cord and nervous system. The sample population ranged in age from 18-75, and about 59% were female. Prior to the consultation, patients filled out surveys rating their experience, management, and level of uncertainty regarding their own pain. Then, patients and physicians completed post-consultation surveys rating themselves, and each other, on communication skills.

On both the pre- and post-consultation surveys, patients were asked to rate their level of uncertainty regarding several specific aspects of their pain, and they were asked to rate whether they were catastrophizing. Feelings of hopelessness and distress in patients were reduced when they agreed with their physicians that the other person was an effective communicator.

“Patients’ ratings of their providers’ communication competency significantly predicted reductions in their pain-related uncertainty and in their appraisals of fear and anxiety, as well as increases in their positive uncertainty and pain self-efficacy,” Thompson said. “Providers’ reports of patients’ communication competency were likewise associated with decreases in patients’ pain-related uncertainty and marginally significant improvements in their positive appraisals of uncertainty.”

Thompson clarified that, although the study emphasized the importance of the providers’ communication skills, and the effect they have on patient outcomes and emotions, communication is a two-way street, and patients’ communication skills are similarly important.

“Consultations mark what may be a long, challenging diagnostic and treatment journey for these patients, and they could benefit from learning about therapies and strategies to help them manage their pain and uncertainties,” Thompson explained. “Giving them the tools and language to communicate their symptoms and concerns to providers could make their interactions more productive. Learning about the uncertain nature of pain may validate their fears and anxieties, while awareness and education about the various treatment options and therapies such as cognitive behavioral therapy could enhance their coping and dispel feelings of helplessness and fear.”

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