Introduction
In the fast-evolving landscape of healthcare, the emergence of conversational AI technology stands out as a powerful ally in driving productivity and efficiency.
In this blog, you'll find:
How the healthcare landscape is evolving
An understanding of the significant challenges healthcare will encounter in the next ten years
How Conversational AI can revolutionize traditional healthcare facilities to prepare for the future
The evolving landscape of healthcare in 2030
According to McKinsey Consulting 2022 analysis, the healthcare Costs will be outpacing the economic growth.
In the next five years, healthcare spending could rise by 7.1% annually, surpassing the anticipated economic growth of 4.7%. By 2027, U.S. healthcare costs could be $590 billion higher than pre-COVID-19 estimates, with inflation and staff scarcity playing significant roles. It's predicted that the U.S. will face shortages of over 200,000 nurses and 50,000 physicians. This imbalance may strain access to healthcare and worsen health disparities. Additionally, addressing COVID-19 and related issues could add $220 billion in costs over the next five years. The strain on healthcare providers may intensify, impacting margins and worsening the situation. The government's ability to cover these rising costs may be limited, as the 2022 Medicare Trustees report suggests a negative trust fund balance by 2028.
Source: Mckinsey Consulting
A $370 billion risk to industry profit pools by 2027 seems like a big problem for healthcare. However, there is over a trillion dollars of value available in the healthcare system that hasn't been used yet. This could push the industry to find ways to be more productive, especially with cost pressures and a shortage of workers. Using technology to increase productivity could help meet demand, improve access, and lower costs. Below table shows the EBITA (earning before interest, tax, depreciation, and amortization) metric for valuation and comparison.
As healthcare costs continue to rise, it's becoming increasingly challenging for the industry to manage affordability. To thrive in this environment, organizations must restructure their financial, workforce, and business models. This includes embracing innovation and technology, making smart deals, and seeking out every transformational opportunity. By doing so, they can create a new path forward that balances costs and capabilities, allowing for a successful and sustainable business footprint by 2030.
How can Conversational AI help address patient challenges in traditional healthcare systems?
1) Patients demand more time from healthcare givers.
And there are just not enough professionals to fulfill that demand. With conversational AI that gap can be bridged by offloading some of the conversations to AI.
By leveraging advanced AI algorithms, these systems can understand and respond to natural language queries, allowing patients to communicate with virtual assistants as they would with a human healthcare professional. For Ex: The AI models can be trained on proprietary knowledge to assist with specific protocols. These models can also be trained to perform a specific task.
Traditional healthcare systems often struggle with patient adherence and follow-up, leading to suboptimal health outcomes. Conversational AI can bridge this gap by providing patients with tailored information, reminders, and guidance, fostering better self-management and adherence to treatment plans.
Conversational AI can enhance accessibility to healthcare services in underserved or remote areas by providing virtual assistance and support. With Conversational AI, individuals can access healthcare resources through voice or text-based interfaces. This technology allows people with limited access to traditional healthcare facilities to seek information, guidance, and support at their convenience.
2) Revolutionary Conversational AI can remove language barriers
Conversational AI can facilitate consultations by lowering language barriers. Through chats, healthcare providers can assess and diagnose patients even if these are LEP (Limited English Proficiency) patients, eliminating language barrier to healthcare. This is especially helpful for individuals in areas where there is a diverse population and English Proficiency may be lacking.
It can also provide personalized health information, reminders, and preventive care tips. Through chatbots or virtual assistants, individuals can receive relevant and timely healthcare guidance, improving their overall health literacy and empowering them to take better care of their well-being.
How can Conversational AI help address operational challenges in traditional healthcare systems?
Conversational AI can address operational challenges in traditional healthcare systems by providing 24/7 support to patients, automating routine tasks, streamlining administrative processes, and enabling remote patient monitoring. It can help in managing chronic conditions, reducing hospital readmissions, and improving overall patient outcomes. Additionally, it can be used for delivering interactive and personalized training modules for healthcare professionals, ensuring that staff members are well-equipped with the necessary knowledge and skills to provide optimal care.
The toughest challenge of staff shortage
According to the U.S Chamber of commerce, the projected job opening for registered nurses (RNs) is 193,100 per year until 2032. However, for the decade between 2022-2032, the United States expects only an additional 177,400 nurses to enter the workforce, which is less than what is needed to fill one year of projected openings.
Primary reasons of staff shortage are:
Lower retention rates
A 2022 study of over 50,000 RNs and licensed practical nurses/licensed vocational nurses revealed nurses felt the following "a few times a week" or "every day:"
• a sense of depletion (56.4%)
• emotional exhaustion (50.8%)
• fatigue (49.7%)
• burnout (45.1%)
Education Gap
Educational institutions are unable to enroll and train enough nursing students due to a shortage of educators. This limits the pipeline of new nurses.
Current work schedule scenario for the nursing staff
A study was conducted to evaluate the performance and efficiency of nursing staff. Nurses working in 36 medical-surgical units were asked to participate in research activities aimed at assessing how they allocate their time, their location and movement patterns, and their physiological responses. The study revealed three key areas for enhancing nursing care efficiency: documentation, medication administration, and care coordination. Implementing technological advancements, optimizing work processes, and improving unit organization and design can lead to significant improvements in how nurses utilize their time and deliver care safely.
Retirement
The number of Americans over 65 is at an all-time high. By 2030, all Baby Boomers will be retired, resulting in a greater demand for healthcare services. Many nurses are also retiring, with around one million nurses aged 50 and above and almost 60 percent of nurses over 40. Additionally, over 20 percent of nurses plan to retire in the next five years, further reducing the available nursing faculty.
The high cost of running the healthcare facility
According to McKinsey Consultancy, the clinical labor shortage could create $170 billion (about $520 per person in the US) in incremental costs in 2027, primarily from wage growth as resources become scarce (graph below). In addition, labor shortages could stymie growth of individual health systems and lead to access risks from site-of-care closures and increased wait times. And we know that when access to care contracts, disadvantaged communities are often disproportionately impacted, a blow to health equity efforts.
Conversational AI is a game-changer that holds immense potential for transforming the cost-saving challenge in traditional healthcare facilities. With its advanced capabilities and round-the-clock availability, AI-powered chatbots can revolutionize patient care by significantly reducing operational costs and thus keeping the organization ready for cost and labor challenges.
AI is revolutionizing online scheduling in healthcare by leveraging various data points to make it more meaningful for patients. By aggregating past patient preferences, such as preferred providers or appointment times, AI algorithms can provide personalized recommendations that align with their preferences.
Moreover, AI can consider a patient's current position in their broader care journey. For example, if a patient is due for a follow-up appointment after a specific procedure, AI can prioritize scheduling options accordingly.
Provider specialty relevance is another factor that AI considers. By analyzing a patient's medical history and condition, AI can match them with providers who specialize in the relevant field. This ensures that patients are scheduled with the most appropriate healthcare professionals for their specific needs.
AI also considers appointment availability and geography data. By analyzing real-time data on appointment availability, AI can offer patients options that align with their desired date, time, and location. This reduces the hassle of manual searching and improves convenience for patients.
Overall, by leveraging AI capabilities, routine tasks like online scheduling become more efficient, personalized, and tailored to each patient's unique preferences, ultimately enhancing their overall healthcare experience. AI Assistants can help with several operational aspects:
24/7 Availability: Conversational AI can provide round-the-clock support and information to patients, reducing the need for human staff to always be available.
Automated Appointment Scheduling: AI-powered chatbots can schedule appointments, remind patients of upcoming visits, and even handle cancellations or rescheduling, reducing the workload on administrative staff.
Medical History Collection: Chatbots can gather patients' medical history and symptoms before appointments, saving time during consultations and reducing the need for additional staff support.
Answering General Inquiries: AI chatbots can address common questions from patients regarding services, hours of operation, billing, and more, reducing the volume of calls to human staff and saving time.
Assisting Healthcare Professionals: AI can assist healthcare providers in retrieving relevant patient information quickly, suggesting treatment options, and keeping track of protocols, streamlining the workflow and saving time.
Improving Efficiency in Billing and Claims Processing: Conversational AI can help with providing billing information, insurance details, and assist in claims processing, reducing errors and streamlining the financial aspect of healthcare facilities.
Patient Monitoring
Conversational AI can be used to collect and analyze patient data, providing continuous monitoring of vital signs and other health metrics. This proactive approach can help nursing staff identify potential issues early, preventing costly hospital readmissions and complications.
Training and education
Conversational AI can be used to provide educational resources and training materials for patients and nursing staff. By empowering patients with self-care knowledge and assisting staff with ongoing education, conversational AI can contribute to improved health outcomes and reduced errors, thereby reducing costs associated with preventable complications.
By leveraging conversational AI, educational institutions can create virtual teaching assistants and interactive learning platforms that supplement traditional education methods. These AI-powered assistants can provide personalized instruction, simulations, and on-demand resources, thereby expanding the capacity to educate and train nursing students. This technology-driven approach not only alleviates the burden on educators but also enhances accessibility, flexibility, and scalability in nursing education, paving the way for a larger influx of qualified nursing professionals to meet the growing healthcare demands.
What specific features or capabilities of conversational AI have been proven to positively impact patient satisfaction levels?
By embracing conversational AI, healthcare facilities can not only enhance patient experience but also streamline their operations, leading to substantial cost savings and ultimately making quality healthcare more accessible to all.
Northwell Health's Wide Implementation of Health Chats Leads to Improved Patient Satisfaction and Cost Savings.
Northwell Health integrated Conversa Powered AI with their care management tool to manage and elevate patient experience, called as “Northwell Health Chats”. As Northwell introduces Health Chats system-wide, they will track care quality, costs, and patient satisfaction. With Northwell Health Chats, they have achieved a 97% patient satisfaction rate and lowered post-acute care expenses in certain hospitals. Northwell's management is especially focused on cost savings from decreased outreach calls, as the chatbot engages patients and gathers necessary information efficiently.
“Conversa’s conversational AI powering Northwell Health Chats enables us to improve care coordination, patient satisfaction and our ongoing patient relationship, resulting in the improved well-being of our customers while reducing costs. This high-tech, high touch, scalable approach benefits our patients, our nurses and our health system”, concludes Joseph Schulman, SVP Regional Executive Director at Northwell Health.
Sensely, a healthcare technology company, has developed a virtual nurse assistant powered by conversational AI. This AI-driven solution is designed to support patients in managing chronic conditions, such as diabetes, heart disease, and mental health disorders. The virtual nurse assistant can engage in natural conversations, provide educational resources, track symptoms, and offer personalized coaching and reminders to help patients adhere to their treatment plans and maintain a healthy lifestyle.
These case studies demonstrate the transformative potential of conversational AI in healthcare, improving patient experiences, enhancing access to care, and streamlining healthcare operations while maintaining a human-centric approach.
Relic Care is innovating and building Conversational AI for Healthcare. Targeted towards Healthcare Facilities, currently there are a few pre-built roles offered as AI Assistants. These include an Emotional Counsellor, Dietitian, Physiotherapists and a Facility Manager. Apart from these roles, there are Language Service Roles - AI Interpreter and AI Translator. Custom Roles can be built on demand.
If you want to revolutionize your facility with Conversational AI - Drop us a line.
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