Home 5 Clinical Diagnostic Insider 5 A 21st Century Response to the Cures Act

A 21st Century Response to the Cures Act

by | Nov 24, 2023 | Clinical Diagnostic Insider, Inside the Diagnostics Industry-dtet

Patients’ unfettered access to complex test results can lead to confusion and distress—but generative AI can help.

The implementation of the 21st Century Cures Act,1 which mandates that patients have timely access to their electronic health information, has opened up new avenues for accelerating patient care, communication, and education. Unfortunately, it has also led to challenges when patients receive results they don’t understand. Often, unfamiliar terms and confusing medical language cause unnecessary distress for the patient2—and may cost providers additional time responding to unexpected patient queries and follow-ups.

Patient communication challenges

Patient expert Michele Mitchell, who co-chairs the University of Michigan’s Patient and Family Advisory Committee, believes generative AI can play a valuable role in addressing a range of challenges raised by the Cures Act, including:

    • Complex medical jargon. “One common issue is that lab test results and medical reports often contain complex terminology that can be difficult for patients to comprehend. Generative AI can assist by translating medical jargon into plain language, making it easier for patients to understand their results.”

    • Lack of context. “Patients may receive test results without sufficient context about what those results mean for their health. AI-powered systems can reference a patient’s medical history to provide personalized interpretations of results that considers their unique health situation.”

    • Overwhelming information. “Patients can feel overwhelmed when presented with a large volume of health data. Generative AI can help by summarizing key findings and highlighting critical information, ensuring that patients focus on the most relevant aspects of their results.”

    • Communication gaps. “There can be gaps in communication between patients and healthcare providers when patients receive their results electronically. AI chatbots and virtual health assistants can facilitate real-time conversations in which providers can answer questions and provide clarification.” That’s why institutions such as Ochsner Health3, the University of California, San Diego,4 and the University of North Carolina5 are pioneering generative AI-supported patient messaging.

    • Follow-up recommendations. “Patients may not always receive clear instructions on what actions to take based on their test results,” says Mitchell—and this is especially true in complex health situations with competing or conflicting needs. “AI can generate personalized recommendations for follow-up care, such as scheduling appointments, adjusting medications, or making lifestyle changes.”

  • Accessibility. “Some patients may have disabilities or language barriers that make it challenging to access and understand their electronic health information. AI can provide accessibility features, such as text-to-speech or translation services, to make health information more inclusive.”

It’s clear that generative AI has the potential to facilitate more accessible, understandable, and actionable health communication—especially between laboratorians and patients, who often have little or no contact with one another. For busy labs with little time to spare, the support generative AI offers can save time without sacrificing patient communication, satisfaction, and outcomes.

Lightening the load

The technology’s benefits extend beyond communication into other vital aspects of patient-centered care in the clinical lab. Mitchell, who also works with the American Society for Clinical Pathology, the American Cancer Society, the American College of Radiology, and MyPathologyReport.ca on patient advocacy initiatives, highlights the ways electronic health records (EHRs) and patient portals such as Epic and MyChart leverage AI6 to benefit patients and providers:

    • Streamlining administrative tasks. “AI assists with automating tasks such as appointment scheduling, billing, and documentation, enabling healthcare providers to focus more on direct patient care.”

    • Personalized patient care. “By analyzing patient data and history, AI helps deliver personalized treatment plans and recommendations, ensuring that patients receive tailored care suited to their specific health needs and conditions.”

    • Remote patient monitoring. “AI-powered devices and applications allow for remote patient monitoring, allowing healthcare providers to track patient health metrics in real time and intervene promptly when necessary.”

    • Predictive analytics for preventive care. “AI algorithms analyze patient data to predict potential health concerns, identify at-risk populations, and prompt healthcare providers to implement preventive measures to reduce the likelihood of adverse health events.”

  • Optimizing workflows and resource allocation. “AI tools help optimize healthcare workflows, manage resources efficiently, and improve operational efficiencies, ultimately leading to better resource allocation and cost-effective healthcare delivery.”

By integrating AI into existing tools such as laboratory information systems and EHRs, laboratories can improve patient engagement and outcomes and support more efficient, effective healthcare delivery at every level.

A resource for patients and providers

The Cures Act has made it more important than ever for patients to understand their health and test results in context. Increasingly, tech-savvy patients are turning to generative AI with questions about their symptoms, diagnostic testing, and treatment options. Mitchell sees this as an opportunity for laboratorians to benefit from AI-based support while making themselves a more visible part of the healthcare team.

“Generative AI can create tailored educational materials and information for patients,” she says. “For example, it can generate patient-friendly explanations of lab tests, their purposes, and preparation instructions. This can help patients better understand the importance of their tests and how to prepare for them.” Similarly, AI can analyze and summarize complex findings, making it easier for laboratory professionals to communicate results clearly and concisely. “AI can even create visually appealing and easy-to-understand data visualizations for test results,” Mitchell continues. Enabling patients to grasp the significance of their results more intuitively can lead to more informed discussions with healthcare providers.

Patients who need further support can use AI-powered functions including links to external resources, automatic translation (including in real time) to overcome language barriers, and expanded availability. “AI chatbots can provide instant responses to patients’ questions about lab tests, results, and follow-up care,” explains Mitchell. “These chatbots can be available 24/7, improving accessibility and reducing the time patients must wait for information.”

By automating time-consuming tasks, AI can free up laboratory professionals to prioritize more complex work—and the support it offers becomes more refined over time. “AI systems can learn from patient interactions and continuously improve their ability to provide relevant information and respond effectively to patient needs,” says Mitchell. “This adaptive learning eventually leads to more effective communication, increasing patient engagement, understanding, and satisfaction.”

For laboratory professionals and administrators, the potential gains are even greater. “Ensuring the secure and private transmission of electronic health information is critical,” says Mitchell. “Robust encryption and authentication mechanisms can be integrated into AI-powered communication platforms. AI can also help healthcare organizations comply with privacy regulations.”

A promising technology

Patients derive significant benefit from direct contact with pathologists and laboratory medicine professionals, who can help them interpret their test results, understand their health conditions, and collaborate with care providers on treatment decisions. As lab workloads intensify and staffing pressures increase, lab leaders should consider generative AI’s potential to increase efficiency, facilitate communication, and improve the healthcare journey for patients and providers.

References:

    1. An Act to accelerate the discovery, development, and delivery of 21st century cures, and for other purposes. One Hundred Fourteenth Congress of the United States of America. January 4, 2016. https://www.congress.gov/114/bills/hr34/BILLS-114hr34enr.pdf.

    1. Gerber DE. 21st Century Cures Act: implementation without understanding implication? JCO Oncol Pract. 2022;18(2):85–87. doi:10.1200/OP.21.00436.

    1. Ochsner, an innovator in digital healthcare, is testing generative AI to draft message responses from healthcare workers to patients. Ochsner Health. September 18, 2023. https://news.ochsner.org/news-releases/ochsner-health-to-integrate-generative-ai-into-patient-messaging.

    1. S Bock. Introducing Dr. Chatbot. UC San Diego Today. June 15, 2023. https://today.ucsd.edu/story/introducing-dr-chatbot.

    1. UNC Health Works with Epic on Integration of Generative Artificial Intelligence (AI) Tools. UNC Health. May 23, 2023. https://news.unchealthcare.org/2023/05/unc-health-works-with-epic-on-integration-of-generative-artificial-intelligence-ai-tools/.

    1. Cool Stuff Now: Epic and Generative AI. Epic. October 13, 2023. https://www.epic.com/epic/post/cool-stuff-now-epic-and-generative-ai/.

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