The explosion of generative AI in healthcare—largely due to the exponential growth of medical data, a shortage of healthcare providers and advancements in technology, according to the World Economic Forum (WEF)—holds so much promise. Though it may seem daunting, especially with many headlines focusing on negative aspects, there are many beneficial uses for AI in healthcare as well.
Healthcare leaders are using AI for everything from forecasting emergency department volumes for staffing to predicting which treatments might be most effective for certain patients. And it’s not just healthcare execs who see the potential—patients are on board, too.
A Pew Research Center survey found that 38% of patients feel using AI to diagnose diseases and recommend treatments would lead to better health outcomes, 40% think AI would reduce the number of mistakes made by healthcare providers and 51% think AI would improve the problem of bias and unfair treatment.
Whether it’s reducing paperwork, diagnosing ailments and developing treatment plans, optimizing clinical trials or communicating with patients, AI is doing a lot of good. Here are 10 ways AI is making a positive impact in healthcare.
1. Interpreting and diagnosing
One of the most significant advantages of AI in healthcare lies in its ability to enhance diagnostic speed and accuracy to support clinical decisions. AI rapidly processes vast amounts of data, enabling healthcare providers to diagnose and treat diseases more effectively, and provides evidence-based recommendations to help them make well-informed decisions during patient care.
Radiologists are using natural language processing (NLP) to augment their work and improve the interpretation of scans. By analyzing X-rays and MRIs, AI identifies patterns and anomalies that may be overlooked by humans, leading to earlier and more precise diagnoses. The president and CEO of imaging at GE Healthcare, Jan Makela, notes that they get images 30% faster, with higher quality and resolution thanks to AI.
2. Accelerating research breakthroughs and drug development
Conventional drug development and approval processes take over eight years and cost around $2 billion. AI-generated drugs and clinical trials revolutionize this process by analyzing vast amounts of data in a snap.
Generative AI and machine learning also play a role in creating safer, more effective drugs and minimizing drug development costs. Many startups use generative AI to forecast the properties of novel proteins and drugs and predict interactions, which in turn optimizes new candidates for drugs, according to CB Insights analyst Anjalika Komatireddy.
3. Conducting more efficient clinical trials
AI’s predictive algorithms play a vital role in enhancing clinical trials by identifying ideal trial sites and principal investigators (PIs) for recruiting target patient groups. These models leverage past trial performance data to predict site and PI effectiveness. NLP synthesizes medical literature, aiding investigators in designing successful trial strategies.
A case study in WEF’s new Insight Report illustrates that AI enables quick identification of new trial sites and investigators, reducing waiting times for clinical trials from weeks to just hours. This streamlined process eliminates potential delays and saves time and resources, contributing to more efficient and cost-effective clinical trials.
4. Predictive, personalized and precise care
By considering a patient’s medical history, genetic makeup, lifestyle and environmental factors, AI algorithms can assess risk factors and predict medical outcomes to create personalized treatment plans.
5. Real-time remote patient monitoring
AI-powered wearable devices like FitBits and smartwatches continuously monitor patients’ health and transmit real-time data to providers. This can help alleviate unnecessary hospital visits and help with timely interventions by alerting users and healthcare professionals when potential issues arise.
6. Advancing medical technologies
Robotic surgical equipment outfitted with AI helps OR doctors in many ways, including decreasing physical fluctuations and providing updated information during an operation.
7. Predicting and controlling outbreaks
AI is even used by epidemiologists to analyze data and flag early warning signs to lessen the impact of infectious disease outbreaks.
8. Improving patient communication and engagement
AI chatbots and virtual health assistants are proven to answer patient queries, provide information and offer support as well, if not better, than humans.
A study conducted by NYU researchers assessed the feasibility of using ChatGPT or LLMs to answer the extensive questions within electronic health records. The researchers found that patients could not distinguish between AI and human-generated answers, concluding that LLMs can be effective in streamlining patient communications.
AI gets good bedside manner marks as well. A study published in JAMA found that responses from ChatGPT were actually preferred to those given by a physician about 79% of the time and were rated significantly higher for both quality and empathy.
9. Automating workflows and reducing administrative burden
One of AI’s greatest values lies in transforming clinical workflows. Tom Lawry, the national director for AI, health and life sciences at Microsoft, sums it up nicely: “AI adds value in only one or two ways: It adds value by automating the way work is done or augmenting the way work is done.
Salveen Richter, lead analyst for the U.S. biotech sector at Goldman Sachs, states that ChatGPT could not only aid administrative tasks from drafting insurance approvals to scheduling appointments but also “aid healthcare professionals by conveniently summarizing scientific literature, as well as improve patient engagement and education by answering patient questions in a conversational manner.”
By automating or augmenting repetitive tasks, AI greatly reduces the administrative burden on clinicians and staff and frees up time to focus on more important work that impacts patient outcomes.
10. Improving access to care
AI-driven data analytics provide healthcare leaders with insights into patient populations so they can identify at-risk groups and optimize care delivery to meet specific community needs.
Chatbots and virtual health assistants further improve accessibility to healthcare resources. Thanks to AI-powered telemedicine platforms, many patients are receiving medical consultations and care remotely, eliminating the need for physical travel to healthcare facilities and making healthcare more accessible to those in remote or underserved areas.
Though there are challenges to be understood and overcome, AI is significantly improving the healthcare landscape. Still, we’ve only just begun to realize the benefits. The future surely holds more remarkable AI-based innovations. Forbes