AI in Healthcare

These are exciting times to be alive, with tools like artificial intelligence and machine learning creating unprecedented opportunities to elevate patient care, more proactively diagnose disease, and create more effective treatment plans across the healthcare industry.

We are still in the early days of artificial intelligence, however, many healthcare organizations have already experienced AI’s ability to analyze vast amounts of clinical data, recognize patterns, and make stunningly accurate predictions.

Already, 50% of healthcare executives use AI in some capacity, and 85% have a strategy to begin implementing medical AI. It’s important to note that artificial intelligence and machine learning algorithms are not meant to take healthcare jobs or replace doctors and other medical professionals. Instead, healthcare AI can supplement the efforts of members of the healthcare workforce, leading to improved health outcomes.

Keep reading for further insights about the future of AI in healthcare and how Weave’s advanced suite of practice management tools is creating a bright future for healthcare.

The Current Landscape of AI in Healthcare

Be prepared to see advances in healthcare begin to occur at the speed of light, as healthcare professionals become more comfortable with the concept of artificial intelligence.

Understanding AI’s Role

Artificial intelligence in healthcare is a somewhat broad term, including machine learning, natural language processing, and robotics.

1. Machine learning: Within the field of artificial intelligence is a concept referred to as machine learning. Here, a machine is “trained” to comb through vast amounts of unstructured data and healthcare data across various health systems to recognize patterns and make predictions.
   
   Having access to this advanced technology can be a major boon to population health, not only for applications like disease diagnostics and precision medicine but also for managing the resource needs of healthcare professionals.
    
2. Natural Language Processing: Referred to as NLP for short, Natural Language Processing focuses on training machines to understand human language through text and speech recognition.
   
   There are various applications for NLP, from translating patient notes and medical records to engaging in dialogue. Weave has been an early adopter, creating smart systems that interact with patients through features such as Email Assistant and Reviews Response Assistant.
    
3. Robotics: Machines can be trained across a variety of skill sets, and providers can take advantage of a broad range of applications here. For example, robots can be trained to perform various tasks for primary care doctors and patients alike, which allows seniors to live independently longer and promote patient safety in both home and hospital settings.
   
   While we’ve long heard of robotics being used to assist in surgery, this is just the tip of the iceberg. Robots can dispense medicine, serve as exoskeletons and medical devices for mobility, and even engage in conversation.

Real-World Applications and Success Stories

As AI systems continue to be adopted across the healthcare industry, success stories are amassing in terms of AI being instrumental for disease diagnosis, patient engagement, and operational efficiency.

One particularly powerful example comes from GE Healthcare using AI in hospitals. The company developed a Command Center that utilizes deep learning algorithms in a hospital setting to analyze patient records in real time, including patient flow, bed occupancy, and staffing levels. Performing data analysis with this information has allowed the Command Center to improve patient throughput, reduce wait times, and enhance patient satisfaction.

Johns Hopkins Hospital used this AI technology to achieve a 60% reduction in patient transfer times and a 70% decrease in time spent waiting for a post-surgical bed. Tools like Weave can be used to help analyze practice trends and make recommendations for patient scripts, revenue cycle management, and more.

Advanced Diagnostics and Predictive Analytics: AI is transforming diagnostics with algorithms that can interpret medical images faster and more accurately than human radiologists. For example, AI systems are now used in radiology to detect early signs of conditions such as cancer and neurological diseases, allowing for quicker intervention. Predictive analytics can also identify patients at risk of developing chronic conditions, enabling preventive measures and personalized care plans.

Personalized Medicine: AI-powered tools are advancing personalized medicine by analyzing genetic information, lifestyle factors, and medical history to tailor treatments to individual patients. This approach improves treatment efficacy and minimizes adverse effects by targeting therapies specifically suited to the patient’s unique profile.

Virtual Health Assistants and Chatbots: Virtual assistants and AI-driven chatbots are increasingly being used for patient engagement, answering questions, scheduling appointments, and even providing mental health support. These tools improve accessibility and provide patients with real-time support, enhancing the overall patient experience.

Robotics and Surgery: In surgical settings, AI-powered robotic systems assist surgeons in performing precise, minimally invasive procedures. These systems reduce the risk of complications, decrease recovery time, and improve surgical outcomes by providing enhanced precision and control.

AI in Population Health Management: AI applications in population health use big data to identify trends and patterns in large groups, enabling healthcare providers to develop targeted interventions. This can help manage chronic diseases, predict outbreaks, and allocate resources more efficiently to improve public health outcomes.

The most widely used AI applications in healthcare are those that enhance diagnostics and imaging, such as AI-powered radiology tools for detecting conditions like cancer and fractures from medical images. Machine learning algorithms in electronic health records (EHR) systems are also prevalent, helping predict patient outcomes, optimize treatment plans, and improve workflow efficiency. Additionally, AI-driven chatbots and virtual health assistants are commonly used to support patient engagement, appointment scheduling, and basic medical inquiries, making these among the most adopted AI technologies in healthcare. These expanded AI applications demonstrate the breadth of AI’s impact on healthcare, driving innovations that improve patient outcomes, streamline operations, and personalize care, marking significant progress in the journey towards more efficient and effective healthcare delivery.

The Benefits of AI in Healthcare

There’s a long list of benefits associated with using artificial intelligence in healthcare, from healthcare research and health monitoring to improving clinical workflows and achieving better medical diagnosis statistics.

Enhancing Diagnostic Accuracy

Being able to quickly and accurately diagnose disease is imperative in achieving better health outcomes. Here, artificial intelligence in healthcare can be leveraged to analyze medical images at scale, including radiology images, CT scans, X-rays, and ultrasounds.

Having access to vast amounts of healthcare data can lead healthcare providers to be better able to detect diseases earlier with higher accuracy and efficiency. Many diseases are incredibly difficult to predict, but AI can change that with machine learning tools that offer earlier and more accurate predictions.

By analyzing millions of electronic health records, artificial intelligence can absorb and process health data at a capacity that simply isn’t possible by the human mind alone. Given that it can cost 12x more to treat a disease that had a delayed diagnosis, early diagnosis is key to saving lives and allowing healthcare costs to be administered more effectively.

The risk of human error in diagnostic accuracy cannot be overlooked either. According to one study 400,000 patients per year are harmed from wrong or delayed diagnosis, and another 100,000 lose their lives as a result of these mistakes. While AI cannot magically create a perfect batting average for medical professionals, AI systems can improve outcomes and potentially save lives.

Personalizing Patient Care

Patients have become overwhelmingly dissatisfied with the way they’re being treated across the board – from hospital visits to checkups at the dentist’s office. Topping this list of complaints is being treated in a way that feels rushed, or they’re “just another number.”

As the demands of running a clinical practice become more complex and healthcare budgets are stretched to the breaking point, it’s no wonder that doctors are trying to fit more patients into their workday.

While it’s understandable to keep an eye on the bottom line, medical providers don’t have to sacrifice care quality to see more patients. Properly utilizing healthcare AI can deliver the best of both worlds – seeing more patients while ensuring communication remains personal, compassionate, and empathetic.

For example, AI can be used in the area of medical records management to keep detailed information on a patient and get prompts from AI to discuss certain issues based on the contents of those files.

A healthcare provider can also monitor patient health records and use AI prompts to predict health risks and address them early. And finally, an office can use traditional machine learning to install intelligent chatbots across various patient touchpoints to communicate in real-time with patients, even before they visit a medical office.

Streamlining Operations and Reducing Costs

Artificial intelligence can go far beyond the medical aspects in the healthcare sector. There’s also a huge potential for healthcare organizations to leverage the practice management side of the healthcare equation.

Specifically, healthcare practices have a long list of administrative tasks to tackle each day, including appointment scheduling and confirmations, billing, and record keeping. AI tools can automate these administrative tasks, leading to operational efficiencies and cost savings for healthcare practices across the board.

For example, Weave’s suite of tools has helped countless medical practices reduce their administrative workload while delighting patients by using features that respond to patient inquiries, confirm and reschedule appointments, streamline insurance verification, and assist with taking payments for medical services.

Challenges and Considerations

While health AI is promising for improving health outcomes, it’s important to recognize that it’s not a perfect panacea and it also comes with risks and other considerations.

Navigating Data Privacy and Security

Every healthcare office must be diligent about safeguarding patient data, ensuring that it remains private and is not shared with third parties or other outsiders. Not only can this be devastating to a patient, but a breach also violates HIPAA.

Using artificial intelligence in healthcare can present a risk that data can be leaked. For example, if you add medical imaging to an AI database for the purpose of predicting a disease or formulating a diagnosis, you must be careful to ensure that any identifying patient information is stripped from the transmission.

To further complicate matters, the World Health Organization has identified another risk of relying on AI. There have already been reported instances of false, inaccurate, or biased predictions, and that can be incredibly harmful. While there is not a hard and fast solution to this issue, medical providers should avoid blindly issuing a treatment plan or diagnosis without first evaluating the data firsthand.

To keep your patients’ data private and protected, it’s recommended that healthcare practices encrypt their data, limit access across the healthcare organization, and implement authentication procedures to ensure that only those authorized to see the data are able to access it. Offices should regularly audit and assess their systems, as well as provide employee training, covering topics that include awareness and best practices.

Ensuring Equity and Accessibility

Whenever new technology becomes available, it is rarely adopted uniformly. It is important for the sake of global patient outcomes that new AI technology needs is accessible and equitable. Everyone deserves to reap the benefits of these advancements.

Approaches to mitigate this disparity could include creating community health centers that provide these AI-driven services either free or affordably. Telehealth expansion is another potential way to level the playing field. Telehealth initiatives can be inexpensive to deploy and make advanced healthcare solutions more accessible.

The Future of AI in Healthcare

Artificial intelligence in healthcare continues to evolve rapidly and we can expect further advancements in healthcare delivery, diagnostics, treatment, and medical research. Keeping an eye on emerging trends can help healthcare providers prepare for a future centered on technology and artificial intelligence.

Emerging Trends and Innovations

There are several exciting innovations on the horizon, including predictive analytics and advanced robotics. As more data is collected daily, AI algorithms are improving at analyzing unstructured data to create models that forecast outcomes, risks, and appropriate responses.

From a robotics perspective, we will continue to see improvements in robot-assisted surgical procedures, but we can also anticipate robots becoming more human, interacting with patients to help them with things from getting dressed to taking medication and even offering mental health services!

As AI becomes more ubiquitous in healthcare, we can expect it to touch every interaction with the patient – including when they pick up their smartphone to call or email your office. Weave is keeping a close eye on these innovations, also striving to be on the cutting edge of healthcare practices.

Preparing for a Tech-Driven Healthcare Future

Healthcare providers should be on the lookout for ways to integrate AI into their practices and focus on investing in the right tools while training their teams to embrace and utilize this new technology.

Using a tool like Weave can help in achieving this goal by equipping your team with powerful AI tools that elevate patient communication and practice performance.

Conclusion

There is still massive potential for AI in healthcare, particularly in areas like improved patient care and operational efficiency. To see how Weave plays a role in shaping the future of healthcare, schedule a demo.