Blogs
Welcome to our blog section on Artificial Intelligence (AI)! Here, we will explore in-depth one of the fastest and most exciting technological fields of the modern era.
Blogs
01/11/2023
The US healthcare consumer experience (CX) is highly fragmented, leaving patients feeling disconnected and dissatisfied. The Accenture Global Healthcare Consumer Study showed that 66% faced negative experiences. Notably, 78% of patients who switched providers did so due to navigation issues. Healthcare IT leaders are challenged by fragmented patient journeys, exacerbated as new technologies complicate patient interactions and involvement in their care.
Amidst this landscape, healthcare providers and payers are confronted with the urgent need to ensure an exceptional CX for patients. Jeff Sturman, the senior vice president and chief digital officer of Memorial Healthcare System in Florida, emphasizes: "We must establish a multichannel approach for patient communication". Sturman also states: "Consumers cannot be expected to rely solely on contact centers for assistance. Our communication methods need to encompass texting, chat options, and appropriate automation. Most significantly, we should aim to enhance self-service capabilities."
In the realm of healthcare, contact centers are grappling with a mounting influx of calls from patients and plan members. Take Memorial Health System as an example, receiving an overwhelming 100,000 calls a month from patients, as highlighted by Sturman. This surge in calls places significant strain on the system, leading to frustration and dissatisfaction among patients, caregivers, and agents.
When patient calls go unanswered or experience significant delays, individuals might hang up without securing essential appointments or obtaining critical information regarding test results or procedure coverage. These experiences result in delayed care and poor patient access, contributing to adverse health outcomes and elevated healthcare costs. Additionally, these setbacks may drive patients toward more convenient care options, causing organizations to lose patients to competing services that offer smoother, more efficient experiences.
Furthermore, healthcare contact center agents lacking the proper tools to assist callers quickly become burned out, leading to higher turnover rates. In a 2022 survey by the International Customer Management Institute, 57% of contact center professionals reported increased turnover within their organizations compared to the previous year. To address these challenges, automation plays a crucial role in keeping up with consumer inquiries and optimizing the efficiency of available staff, rather than just containing staffing costs.
The key to transforming and optimizing patient experiences in healthcare contact centers lies in leveraging cutting-edge technologies like generative AI. This advanced AI system revolutionizes the way patient calls are managed, significantly reducing wait times, optimizing call resolutions, and improving overall patient access. It's a pivotal solution to enhance patient interactions and streamline operations within healthcare contact centers, catering to the ever-evolving needs of both patients and staff.
The healthcare consumer experience faces multiple challenges — disconnected systems, staff shortages, and ever-rising patient expectations. While these issues seem deeply entrenched, leaders in the healthcare industry acknowledge that technology is no silver bullet for instant resolution. However, the emergence of generative artificial intelligence (AI) in various sectors, particularly within healthcare, holds the promise of transformation, especially in the contact center domain.
Generative AI and its advanced large language models (LLMs) have significantly progressed in automating tasks involving language comprehension, interaction, and analysis. As contact centers serve as vital hubs for healthcare conversations, integrating generative AI can revolutionize the efficiency of these spaces. While AI has been utilized for several years in healthcare contact centers to enhance self-service and agent efficiency, the adoption of generative AI signifies a monumental leap forward.
AI and machine learning capabilities amalgamate patient information from multiple sources, including texts, call logs, and electronic health records, presenting it in an easily digestible format. Generative AI has the remarkable ability to analyze data across various formats and knowledgebase articles, crafting precise responses to patient queries. This not only streamlines communication but also saves time previously spent navigating through fragmented data sources. It significantly bolsters the accuracy and effectiveness of self-service bots on voice and digital platforms.
Furthermore, generative AI can evaluate patient/member language and tone, offering suggestions to agents on what to say and how to say it. This feature is particularly advantageous for inexperienced agents handling unfamiliar topics. Additionally, it aids in auto-summarizing call transcripts, a task that typically consumes substantial time. Moreover, AI's analytical prowess on call transcripts allows for performance evaluation and actionable feedback to enhance agent interactions.
Automating routine yet time-consuming tasks, such as appointment scheduling and password resets, liberates agents to focus on consumers with more complex needs. This shift toward personalized interactions significantly heightens satisfaction for both consumers and agents, boosting the likelihood of successful outcomes.
By enabling self-service features on voice and digital channels, healthcare contact centers can dramatically reduce call volumes. This decrease in workload not only eases the pressure on contact center agents but also substantially improves the overall patient experience.
At Memorial Healthcare System, integrating generative AI, automation, and multichannel options into the contact center operations has significantly reduced the "speed to answer" time to just 43 seconds from over two and a half minutes a year ago, states Sturman, senior vice president and chief digital officer.
Leveraging digital tools to meet the expectations of healthcare consumers is not just a differentiation factor but a pivotal element in shaping the future of healthcare.
The advent of generative AI marks a significant advancement for enterprises. The concept of software producing and delivering content to patients and plan members was once unthinkable. The success and sustainability of generative AI in healthcare, particularly in contact centers, hinge on how platforms empower organizations to rapidly and securely build, train, monitor, and update models.
Essential to this approach are "human-in-the-loop" systems where generative models undergo training and simulation before being deployed to consumers. Robust monitoring and observability tools play a pivotal role in detecting edge cases, potential issues, or inefficiencies. Moreover, AI's self-evaluation capabilities offer faster and more thorough recommendations for optimizing and rectifying different automations across the contact center.
Generative AI holds the promise of delivering impressive conversational AI and robust agent support tools, enabling improved outcomes and enhanced experiences. For healthcare organizations, it's crucial to leverage these capabilities efficiently, effectively, and responsibly to ensure a seamless and responsible transition to this innovative technology.
DrAid™ for Patient EMR Analytics, a revolutionary module automating Electronic Medical Records (EMR) analysis, offering valuable insights to healthcare providers. By utilizing cutting-edge technology, it generates automatic medical reports and provides smart patient-record search and summarization based on ChatGPT (Generative AI). It enhances patient outcomes with personalized treatment recommendations, clinical decision support, and real-time alerts for timely interventions.
Waste time no more and learn about DrAid™ for Patient EMR Analytics now to identify how the generative AI platform can become the doctors' assistant!