Future of AI Use in Healthcare: The Pros and Cons

Once the stuff of science fiction, artificial intelligence (AI) is real, and it’s here to stay. AI tools like natural language processing (NLP) and machine learning (ML) can help doctors make treatment decisions and uncover small health problems before they turn into difficult-to-treat chronic conditions.

But AI is still a fairly young technology, which means that all the kinks haven’t quite been worked out yet. Even so, artificial intelligence shows promise when it comes to transforming healthcare, and it’s only going to improve with time.

Wondering how AI use in healthcare could benefit your practice? Check out our free webinar, “Using AI To Improve Efficiency Throughout Your Small Business Operations,” which delves into the perks of AI, popular AI tools your practice can use, and the future role AI will play in the healthcare industry.

How AI Is Being Used in Healthcare Today

AI technology has been around for years, but with the advent of conversational AI models like ChatGPT, its popularity has exploded in the healthcare sector. According to a 2021 study by health insurer Optum, 85% of healthcare executives have a strategy for AI, and about half of those surveyed currently use AI to address challenges in the industry.

Artificial intelligence can do some of the things human doctors can do, but faster, cheaper, and with impressive accuracy. Here’s how healthcare providers are using AI to improve patient outcomes, discover new treatments, and improve the efficiency of their medical practices.

Diagnosis

Nearly every doctor asks, “How can I make better diagnoses for my patients?” 

About 400,000 hospitalized patients suffer from preventable harm due to wrong or delayed diagnoses every year. More than 100,000 of them die from complications that could have been prevented had a doctor diagnosed them earlier.

Most doctors do their best to diagnose patients correctly, but it’s all too easy to make mistakes. Heavy caseloads mean doctors don’t have hours to spend chatting with everyone to get their full medical history. 

Some medical conditions are nearly impossible to diagnose until it’s too late. Acute kidney injury (AKI), for example, is notoriously hard to catch early on. In 2019, DeepMind Health and the Department of Veterans Affairs developed a machine learning AI tool that could predict AKI up to 48 hours in advance.

Doctors can use AI for medical imaging, too. AI tools can help them make sense of X-Rays, ultrasounds, CAT scans, and other patient data, allowing them to quickly make a more accurate clinical decision.

Some AI tools may even be able to diagnose patients before they’ve seen a healthcare provider. Developed by a team from Harvard Medical School, Buoy Health is a digital health chatbot that listens to symptoms and gives feedback as to what might be wrong. The tool then tells patients whether they can self-treat at home or need to visit a doctor for care.

While AI cannot replace doctors completely in diagnostic medicine, AI tools can supplement doctors’ training to provide earlier diagnoses and better patient care.

Practice Management and Marketing

In a busy healthcare practice, doctors may meet with dozens of patients per day. Organizing and keeping track of each patient’s electronic health record can be a headache for providers. With AI, doctors can cut down on administration, giving them more time to spend with patients.

But doctors aren’t the only ones in a practice who can benefit from AI use in healthcare. Nurses and other staff can use AI to share to-do lists, send patients reminders about treatment plans, and stay on top of unpaid bills.

Many practices have issues with no-shows. If someone doesn’t come to their appointment, the practice loses money if it can’t rebook the slot in time. Practices can use AI to predict potential no-shows and send appointment reminders to patients.

Administrative AI tools, such as all-in-one charting, allow doctors to keep each patient’s data in one easily accessible place. This software can help them customize their workflow to each patient and provide more personalized care.

AI-based medical documentation software can significantly boost productivity and cut the amount of time spent on administrative tasks by hours per day. The software delivers patient records in real-time and automatically turns patient conversations into notes.

AI can help doctors market their practice and manage its reputation, too. Most people check online reviews before choosing a doctor, which means practices with few or bad reviews could be missing out on new customers.

While Weave Reviews has helped healthcare practices for years by monitoring online reviews and streamlining management, advancement in AI has made reputation management even easier. Weave’s Response Assistant helps reduce the time it takes to respond to patient reviews by creating custom, relevant responses to patient reviews by using generative AI technology. This allows you to streamline your reputation management process giving you more time to tend to patients in your practice. 

Responding quickly and thoughtfully to reviews helps your practice improve your online reputation, increase patient trust and loyalty, and ultimately drive revenue. Our AI Response feature ensures consistency and professionalism across all responses, protecting your brand’s reputation. With Weave’s Response Assistant, you can enhance your reputation management efficiency, boost brand awareness, and stay ahead of the competition. 

Treatment Planning

Making accurate diagnoses goes hand-in-hand with effective treatment planning. When doctors know what’s wrong, they’re better equipped to create a treatment plan for patients.

Thanks to AI, doctors can use precision medicine to develop personalized treatments based on patients’ lifestyles, environments, and genes. For instance, healthcare professionals may use AI-based Next Generation Sequencing (NGS) testing to quickly sequence a patient’s genome. With this information, doctors can prescribe treatment that increases the patient’s chance of survival. Doctors can use NGS to help patients with certain types of cancer.

iCarbonX is a big data AI tool that allows providers to analyze the medical data and health of patients in what the company calls a “carbon cloud.” Doctors can use the tool to create treatment plans that perfectly match a patient’s symptoms.

People with chronic conditions, such as high blood pressure and diabetes, need a treatment plan that’s simple to follow. AI software for diabetics makes treatment planning easy with predictive glucose readings, interactive coaching, and weight management tips. 

Another AI software, Twill, allows doctors to make personalized patient care recommendations based on the healthcare data of people with psoriasis and multiple sclerosis.

Drug Discovery

New drugs take many resources to develop. It can cost millions of dollars for a company to bring a treatment to the healthcare market, and the research stage may last for years, sometimes even for decades. 

Many promising treatments never make it out of the early testing phase. Only an estimated 5 out of 5,000 drugs that enter initial testing make it to human testing, and of those, only one out of five could be safe enough to make it to market. 

Costs like these can dissuade companies from investing in drug discovery. Why would a company invest in treatment for a rare disease, after all, if they’re not guaranteed to make a profit?

Companies can use artificial intelligence to kickstart the discovery process, reducing the time and cost of bringing new drugs to market. Thanks to AI, researchers may no longer need to spend as much time managing unstructured big data. Artificial intelligence can quickly scan, organize, and store data, allowing researchers to draw insights from complex datasets.

Researchers can use a generative AI algorithm to turn data into 3D models, audio, video, and text. This tool simplifies massive amounts of data and turns it into human-readable output.

AI use in healthcare allows companies to repurpose existing drugs to treat other medical conditions. This is far cheaper than running a clinical trial to produce a brand-new treatment from scratch.

Valo Health is an innovative company that’s using AI to transform the discovery of life-changing medicines. Using its Opal Computational Platform, Valo can collect data to identify common diseases and eliminate the need for animal testing.

Another pharmaceutical company, Reverie Labs, uses predictive analytics to help researchers develop effective cancer treatments.

San Francisco-based Atomwise uses a neural network called AtomNet to identify characteristics for clinical trials. The company claims that its neural network can scan between 10 and 20 million genetic compounds a day, allowing it to deliver results 100 times faster than traditional research methods.

Healthcare Administration

AI-based technology can improve the efficiency of practices by better organizing medical records and reducing the wait time for hospital beds. For example, Johns Hopkins Hospital partnered with GE Healthcare to create a predictive AI solution that helped staff assign patients to beds faster. 

Healthcare professionals can use AI to improve administration and clinical documentation organization. The software automates repetitive tasks, such as unadjudicated claims and eligibility checks, giving healthcare workers more time to spend with their patients.

AI has perks for healthcare employers, too. Spring Health is an automated mental health solution that directs employees to the right treatment options based on their symptoms. The company says that its software boosts morale and slashes turnover rates.

Practices are also starting to see the benefits of artificial intelligence for healthcare IT applications. An AI system can monitor healthcare organizations’ IT networks, provide alerts about potential security issues, and make suggestions on how to fix problems if something goes wrong.

Wearable Devices

Usage of wearable technology, such as smartwatches, fitness trackers, and biosensors, shows no sign of slowing down any time soon. Wearable device interest boomed during the COVID-19 pandemic as more patients sought ways to monitor their health without stepping foot into a crowded waiting room.

The wearable devices market was valued at $13.8 billion in 2020, and it’s projected to reach $37.4 billion by 2028. How can medical practices take advantage of the trend?

Wearable technology gives patients an in-depth look at their symptoms and overall health. These devices can alert patients of potentially dangerous issues, such as low blood sugar or high blood pressure, allowing them to seek health care promptly before small problems become hard to treat or life-threatening.

Fitness trackers from Garmin, Apple, and Fitbit help users take charge of their health. Patients can use these devices to keep track of steps, distance walked, exercise intensity, and daily calories.

Motiv and Withings offer wearable devices that track a user’s sleep activity. These devices can monitor oxygen levels and heart rate during sleep and prompt users to see a doctor if something seems wrong.

Women can use wearables to track their menstrual cycle and help them understand their fertility. For instance, the Ava bracelet uses machine learning to help women keep track of ovulation so they can either avoid or improve their chances of pregnancy.

Older adults can benefit from wearable technology too. Many seniors aged 65+ live alone and have no one nearby to help them should an emergency happen. Wearable devices with AI technology, such as the Silvertree Wristband, can automatically send an emergency alert to paramedics if the user falls. These devices also feature GPS tracking to help families find their loved ones if they get lost.

Pros and Cons of AI in Healthcare

Healthcare AI offers impressive benefits for patients and medical practices alike. Even so, this technology does come with a few potential drawbacks that practices should know.

Pros of AI in Healthcare

Any doctor who would like to make better diagnoses should consider adding AI to their practice. AI can give doctors a better picture of each patient’s medical history and genetic factors, making it easier for them to diagnose patients correctly. Doctors can use artificial intelligence to make custom treatment plans that they tailor to each patient.

AI can reduce the cost of healthcare, too. Instead of spending money to see a doctor in person, patients can use AI to check their symptoms and get trusted care advice without needing to leave home. AI also improves access to care, particularly for people who live in remote areas or are too frail to make the trip to the doctor’s office.

Another benefit is that AI use in healthcare saves time for staff at busy practices. Staff can use the technology to send patients automated reminders about appointments and billing. Practices can take advantage of AI to help out during staffing shortages, too.

Cons of AI in Healthcare

AI does have a few cons to consider. For one, machine learning models can be biased, particularly if they’re trained on majority demographics. That could affect drug research and treatment suggestions even if doctors do their best to avoid bias. 

AI bias can negatively affect people of color. One 2019 study found that an AI algorithm that many hospitals used showed bias when deciding which patients needed care. The algorithm developed this bias because it had been trained on spending discrepancies between black and white patients. Healthcare industry workers will need to keep a close eye on how they train AI tools to avoid problems like these.

Some healthcare workers worry that AI will take over their jobs. AI can do many of the same tasks that humans can, but better, so this could be a well-founded fear. However, AI is likely many years away from being able to handle surgery and other complex medical procedures unassisted. For now, practices will probably stick with AI for fairly simple tasks, such as scheduling and sending patients reminders about upcoming appointments.

Future Uses of AI in Healthcare

Where will AI use in healthcare go next? Artificial intelligence is constantly growing, so it’s tough to predict how the healthcare industry could use this exciting technology in the next few years.

AI adoption will likely continue to rise as the technology improves. More healthcare providers will rely on AI to automatically schedule patients, which could cut the amount of time spent on appointment requests.

More providers will probably adopt conversational AI, as well. These tools can chat with patients about symptoms, give them instructions to follow before procedures and provide directions for their appointment.

As NLP artificial intelligence becomes more sophisticated and better at understanding human language, more doctors will turn to it as a diagnostic tool. Hospital staff will use AI to triage patients and assign beds based on the order of priority. Hospitals could also use intelligent robots to help doctors perform surgery.

AI in healthcare comes with both pros and cons, but one thing is certain: This technology is here to stay, and it’s evolving at a lightning-fast pace. Practices must learn how to adapt alongside AI if they wish to stay relevant in the crowded healthcare marketplace.

To learn more about how AI use in healthcare can help your practice, sign up for a free webinar to talk to industry experts. Want to learn more about Weave Response Assistant, request a demo of Weave today!