Healthcare in the United States is facing several problems. The costs are going up. There are not enough workers, especially nurses. The population is getting older, and patients expect more from their care. Hospital leaders, doctors, and IT managers are turning to artificial intelligence (AI) and new technology to help solve these problems. Recent studies show both chances and challenges in using AI. AI could save the healthcare system hundreds of billions of dollars each year.
This article talks about how AI can save money, where investing in AI will have the most impact, and how AI can help healthcare workers do their jobs better and faster.
Healthcare costs in the U.S. keep rising for many reasons. There are fewer nurses available, more elderly patients need care, and people want better and quicker service. AI and other computer learning tools might help lower these costs without making care worse.
A McKinsey report based on a survey of 200 health leaders worldwide says AI could save between $200 billion and $360 billion every year in healthcare. This depends on how AI is used—from automating paperwork to helping doctors make decisions. David M. Cutler and others in a research paper also mention this big economic potential.
Almost 90% of health leaders say AI and digital changes are very important. But 75% say their organizations have not yet put enough money or planning into using these technologies fully. This shows that many healthcare providers still have a lot to do to keep up.
Health leaders see two main areas where AI investment can make the biggest difference: virtual health platforms and digital front doors. About 70% of the leaders in the McKinsey survey say spending in these parts will improve healthcare services a lot.
Virtual health includes telemedicine, remote patient monitoring, and online doctor visits. AI helps deliver care outside of hospitals and clinics. Since many executives expect big results here, virtual health is becoming a key part of healthcare plans.
Virtual health can reduce the strain on hospitals. It helps when there are fewer workers by letting doctors treat more patients remotely. It also meets patient needs for easier and faster care. AI supports virtual health by helping check symptoms, manage patients remotely, and watch health data from devices like wearables or smart home tools. This can help find health problems sooner.
Digital front doors are websites and apps where patients can book appointments, see health records, contact doctors, and pay bills. These tools make it easier for patients and reduce the work in offices.
AI can help with simple tasks like answering questions, sending appointment reminders, and guiding patients to the right care. AI chatbots and virtual helpers work all day and night to lower phone calls and lessen front desk work. This lets staff spend more time with patients.
Other important investment areas are robotics and advanced data analysis, with over 80% satisfaction among those who invest. Robots help in surgeries, moving items, and repeating tasks in hospitals with accuracy. Advanced analytics uses AI to study lots of medical data, help make diagnoses, and predict patient risks for better treatment plans.
Even though AI offers many benefits, many healthcare groups in the U.S. find it hard to invest and use AI fully.
More than half of health leaders say money is a big problem for speeding up AI use. Smaller clinics and community centers often do not have enough cash. Big hospital systems also have to share their money among many needs and maintain old IT systems.
Old electronic health record (EHR) systems make it hard to add new AI tools. These systems may not handle real-time data or AI methods well. Leaders say updating technology, especially moving to cloud systems, is necessary to get AI benefits.
Good data is very important for AI to work. About one-third of leaders say poor data quality is a problem. Missing or incorrect patient records and data stored separately reduce the accuracy of AI. Improving data sharing and management is a priority.
About 30% of leaders say they have trouble hiring skilled workers with AI and healthcare IT experience. This slows down AI projects. To fix this, health systems are working with AI companies and tech firms.
Many leaders are careful about using AI, especially generative AI that creates text or pictures. It can help with patient education or paperwork, but worries about privacy, accuracy, and legal issues make some hesitant. Following laws and managing risks are important.
One of the fastest benefits of AI is automating tasks in offices and clinical settings. Automation cuts down on paperwork and makes work faster.
AI phone systems and answering services help with patient calls, appointment bookings, and insurance questions. Companies like Simbo AI use conversational AI to handle common patient requests without needing a person. This lowers waiting times, saves staff effort, and improves how patients feel.
Automation tools work 24/7 through virtual helpers and chatbots on phones or websites. Patients can get answers or set up visits outside office hours. This is helpful for offices with few staff or many calls.
In clinical care, AI helps by letting staff share tasks, focus on urgent patient alerts, and make documentation easier. Karl Kellner says AI can save 15 to 30% of nursing time during a 12-hour shift. This can help lessen the nurse shortage by making the current workers more effective.
Health systems that change how work is done instead of just adding AI on top of old processes get better results. This needs teams to work differently with more cooperation and flexibility.
Cloud platforms help by connecting different data sources and giving health IT teams flexible tools. These platforms make it easier to use and update applications to fit users’ needs.
Cloud use also helps with cybersecurity and following privacy rules, which are very important when automating workflows with AI.
Using AI and digital changes in healthcare is hard and needs many resources. Many U.S. health groups team up with tech companies, cloud providers, and other healthcare organizations to speed up AI use.
Working together helps get new technology faster, share costs, and bring in special skills. Jack Eastburn says partnerships help organizations move quicker and save money in ways one group alone might not manage.
Smaller clinics and regional health systems benefit from these partnerships since they might not have enough money or size to invest in AI on their own.
Despite the challenges, interest in AI and digital tools is strong among U.S. health leaders. Those who invest in virtual health, digital front doors, advanced analytics, and workflow automation report good results early on.
The AI healthcare market was worth $11 billion in 2021 and is expected to grow to $187 billion by 2030. This shows more healthcare organizations will use AI in many areas, clinical and administrative alike.
Healthcare providers need to balance careful and ethical AI use while working to lower costs and improve care. Leaders are advised to update technology, improve data quality, and build teams with different skills to run AI projects well.
By focusing on these steps and investing in the right areas, healthcare leaders and IT professionals in the United States can create a future that helps patients, healthcare workers, and the whole health system.
Health systems are grappling with rising costs, clinical workforce shortages, an aging population, and heightened competition from nontraditional players.
Digital and AI transformation is crucial for meeting consumer demands, addressing workforce challenges, reducing costs, and enhancing care quality.
Nearly 90% of health system executives view digital and AI transformation as a high or top priority for their organizations.
Budget constraints and outdated legacy systems are the top barriers hindering digital investment across health systems.
AI, traditional machine learning, and deep learning are expected to yield net savings of $200 billion to $360 billion in healthcare spending.
Executives believe virtual health and digital front doors will yield the highest impact, with about 70% anticipating significant benefits.
Around 20% of respondents do not plan to invest in AI capabilities in the next two years despite recognizing its high potential impact.
Partnerships can accelerate access to new capabilities, increase speed to market, and achieve operational efficiencies in health systems.
Building cloud-based data environments enhances data availability and quality, and facilitates the integration of user-focused applications.
Generative AI can impact continuity of care and operations, but there are concerns regarding patient care and privacy that need to be managed.
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