This series explores legal issues related to physician burnout and potential solutions. Our first post addressed how healthcare organizations can foster the psychological safety and emotional wellbeing of their physicians. Clients regularly report that charting and documenting, and communicating with patients via EMR is a substantial contributor to physician burnout. Here, we discuss artificial intelligence as a potential way to attract, support and retain clinicians overwhelmed by ever-growing to-do lists, allowing them to focus on delivering clinical care.
Our team advises clients evaluating potential AI solutions in healthcare on a range of topics, including AI governance principles, and ongoing risk mitigation and monitoring. AI can reduce physician workloads, and below we cover several potential high-impact options to mitigate physician burnout. In considering how to integrate AI into its structure, healthcare organizations must be mindful of the related risks, including bias, patient privacy and consent, data security, and an evolving legal and regulatory landscape. Healthcare organizations should adopt best practices to ensure their use of AI remains reliable, safe, and legally compliant.
AI Options that May Reduce Provider Workload
Early successes in the use of AI within the healthcare industry have shown that AI has great capacity for streamlining manual or repetitive high volume tasks, supporting physicians in complex data interpretation and decision-making, and reducing time consuming administrative burdens. Here are the leading examples:
1. Enhancing Patient Care Navigation.
AI can make a significant impact in patient interaction and care navigation. For example, AI-powered symptom checkers and patient outreach efforts can help patients identify when they need to seek care and then navigate that care journey with AI tools that can interpret patient queries, direct patients on where to seek care, virtually register patients for appointments, and conduct pre-appointment screenings. The goal is to create a seamless care encounter, reducing patient questions, and minimizing unnecessary hospital or emergency room visits.
2. Improving Remote Patient Interaction and Communication.
AI tools can further reduce the number of patient questions by helping patents to better understand the care they are receiving as they receive it. For example, automated clinical laboratory result reporting has shown promising results in helping patients understand their test results and reduce follow-up questions and calls following an appointment. Further, by integrating AI-driven chatbots and virtual assistants, healthcare organizations can offer 24/7 communication channels that address patient queries and provide health information without the need for direct human intervention.
These AI tools can be programmed to understand and respond to a wide array of patient questions in multiple languages, making healthcare more accessible across patient populations. Furthermore, AI can personalize communication by analyzing patient data to deliver tailored health reminders, medication prompts, and follow-up care instructions, thereby improving patient engagement and satisfaction. This continuous, personalized communication fosters a deeper connection between patients and their care teams, ultimately contributing to better health outcomes and reducing the strain on healthcare providers.
3. Streamlining and Improving Quality of Patient Encounters.
Ambient notetaking software can assist physicians by drafting encounter notes and more efficiently completing patient charting by capturing patient-physician conversations and converting them into structured documentation. This reduces time-consuming clerical work, allowing physicians to focus more energy on patient interaction and decision-making. Also,AI tools that monitor patient health data remotely and identify those in need of preventative care can shift the physician’s treatment approach from reactive to proactive. This both improves patient health outcomes and streamlines physician workflow by helping to prioritize patient needs and reduce unnecessary appointments.
4. Supporting and Validating Physician Decision-Making
AI can help physicians sift through data and process information faster while offering predictive insights or additional points of consideration. In particular, AI algorithms based on deep learning have shown early successes in assisting radiologists with complex imaging interpretation and pathologists and oncologists with analyzing biopsy samples. Other examples include clinical decision support systems integrated with electronic health record systems to provide real-time, evidence-based treatment recommendations to physicians as well as AI tools that help to risk-stratify patients for targeted population health and chronic disease management. Deploying AI as a supplement to physician decision-making not only reduces strain on physicians but also elevates the standard of patient care.
5. Optimizing Mid-Level and Clinical Staff Support
Of course, the foregoing benefits of AI extend beyond physicians and can also be used to support mid-level providers and administrative staff who shoulder their own demanding workloads. For example, AI tools can help automate the drafting of treatment plans as well as personalized education and follow-up care instructions. In utilizing AI tools across the clinical workflow, organizations can not only optimize the support physicians receive from non-physician providers and staff, but also more efficiently and evenly distribute the workload for all team members.
Addressing Legal Risks for Chosen AI Solutions
While the benefits of AI in healthcare are immense, it is crucial to address concerns related to the accuracy, reliability, and ethical use of AI tools. AI applications must be trained to interpret patient information accurately and provide appropriate care instructions. Protecting patient confidentiality, controlling bias, and adhering to regulatory considerations are paramount. Organizations should implement a work plan to test, validate, and ensure AI applications' safety, reliability, and compliance with regulatory standards, including HIPAA and other state and federal privacy laws. Moreover, it is essential to validate AI applications in real-world settings and continuously evaluate their performance to ensure their reliability and safety.
To effectively manage these challenges, many of our clients have found it helpful to implement an AI governance framework that engages key stakeholders responsible for AI adoption goals, establishes clear governance and operational standards, and strategically collaborates on data curation, vendor selection, and contract negotiation. Such a structure should include representatives from legal, compliance, clinical operations, and other relevant domains to devise a comprehensive risk management strategy that emphasizes the significance of strategic partnerships and smart vendor management. By adhering to these principles, healthcare organizations can protect the organization's interests, enhance patient care, and maintain the confidentiality and security of patient information while ultimately supporting physicians and reducing burnout.
Conclusion
AI has already shown exciting potential in combatting physician burnout by streamlining patient interactions and care, supporting decision-making, optimizing mid-level and staff support, and reducing administrative burdens. It is worth carefully considering the ways AI can be incorporated into your organization’s workflow – each healthcare organization has unique needs and the relative nascency of AI offers opportunities to creatively problem solve and even collaborate with emerging platforms to shape AI tools to better meet those needs. However, it is crucial to approach the integration of AI tools with caution, ensuring that they are reliably, safely, legally and ethically used. Addressing the complexities of physician burnout requires wielding all tools available, and when leveraged correctly, AI can have a meaningful impact on provider retention, performance, and satisfaction.