Page 34 - IMDR Journal 2025

Research Article
5."Leveraging Large Language Models for Patient ensuring patients receive quick treatment. By maintaining
Engagement The Power of Conversational AI in Digital continuous engagement, chatbots help build stronger
Health” patient-provider relationships. Additionally, they facilitate
Published in arXiv preprint, 2024 post-visit follow- ups, ensuring that patients stay informed
about their treatments and preventive care, ultimately
Authors: Bo Wen, Raquel Norel, Julia Liu, Thaddeus
Stappenbeck, Farhana Zulkernine, Huamin Chen This leading to better patient satisfaction and retention.
research paper explores how large language models (LLMs) ● Predictive Analytics Predictive analytics uses AI-driven
like ChatGPT and GPT-4 are transforming patient statistical models to forecast future patient needs based on
engagement through conversational AI in digital health. It historical data. AI can detect high-risk patients and make
examines real-world applications of LLMs in patient relevant healthcare suggestions by studying their behavior,
communication, highlighting their ability to provide medical history, and demographic trends. This enables
personalized healthcare advice, automate appointment healthcare providers to send targeted messages, such as
scheduling, and support mental health interventions. The reminders for screenings, vaccinations, or chronic disease
study discusses the advantages of AI-powered chatbots over management programs. Predictive analytics not only
traditional digital health solutions, emphasizing their enhances engagement but also helps in early disease
capacity to process unstructured conversational data and detection, reducing hospital readmissions and improving
generate context-aware responses. It also discusses the overall patient health outcomes. This proactive approach
ethical and regulatory problems of using LLMs in strengthens the relationship between patients and healthcare
healthcare, such as concerns about data privacy, providers.
disinformation, and the possibility of AI bias. The authors Enhancing Operational Efficiency
propose best practices for integrating LLMs into healthcare
marketing strategies, including human oversight, AI improves healthcare marketing efficiency by automating
transparency in AI- generated recommendations, and secure repetitive tasks, such as email marketing, campaign
data handling protocols. Future advancements in natural performance analysis, and customer segmentation. AI-
language understanding (NLU) are expected to enhance powered systems provide real-time insights into campaign
chatbot capabilities, making them more effective in patient effectiveness, allowing healthcare organizations to make
quick adjustments for better outreach. AI takes care of
retention and personalized engagement. The study
boring, repetitive tasks. This gives marketing teams more
concludes that LLM-driven conversational AI has the time to focus on big-picture ideas—like how to better
potential to revolutionize digital healthcare marketing by connect with patients. It also helps healthcare providers use
offering more interactive, responsive, and intelligent patient their time, money, and staff more wisely.
communication solutions.
When things run more smoothly, it’s easier to reach the right
patients and offer better care. Operational Benefits:
AI IN HEALTHCARE MARKETING: ● Streamlined Marketing Operations AI tools optimize
IMPROVING PATIENT ENGAGEMENT marketing workflows by analyzing real-time campaign
AND RETENTION performance and automating decision-making. Healthcare
organizations can use AI-powered dashboards to monitor
Artificial intelligence (AI) is fast altering healthcare
key performance indicators (KPIs) and refine marketing
marketing by improving patient engagement and retention
strategies accordingly. AI also helps in automated audience
through personalized strategies and data analytics. This
research investigates the many uses of AI in this domain, segmentation, ensuring that promotional efforts are targeted
emphasizing its advantages, limitations, and future toward the right demographics. By leveraging machine
potential. learning, healthcare marketers can predict the success of
different campaigns, adjusting maximize impact. These
The Role of AI in Personalizing Patient Engagement streamlined operations enhance the effectiveness of patient
AI technologies are pivotal in creating personalized patient engagement efforts while reducing the time and costs
experiences, which are essential for effective healthcare associated with manual marketing processes.
marketing. By analyzing vast amounts of data from sources ● Data-Driven Decision Making AI enables healthcare
such as electronic health records, patient feedback, and marketers to make informed decisions by processing vast
online interactions, AI can uncover intricate patient amounts of patient data. By studying age groups, habits, and
preferences and needs. This enables healthcare providers to how people respond, healthcare teams can plan better. They
tailor their marketing initiatives to resonate deeply with can send the right message to the right person. This helps
specific patient segments avoid wasting time or money. It makes sure marketing
Key Applications efforts actually work. Hospitals and clinics can also learn
from how patients reply or act. This helps them talk in ways
● AI Chatbots AI chatbots play a critical role in improving
patient communication across various platforms like SMS that feel more personal and clearer. When people feel
and WhatsApp. These chatbots provide real-time responses, understood, they are more likely to stay connected and come
offer appointment reminders, and suggest services based on back for care. Improving Patient Retention Strategies
individual health records. They can address routine The doctors can stay connected with the patients by sending
inquiries, easing the pressure on healthcare workers and reminders, follow-up messages, and useful health tips. This

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