How can AI help advance healthcare industry

Healthcare is one of the world’s largest, most important and most dynamic markets, with global spending reaching $9 trillion in 2020. While providers would like to deliver care to everyone for as little as possible, they’ve had to deal with complex business processes, rigorous approval regulations, high insurance costs and care delivery complexity. The next wave of artificial intelligence solutions, epitomized by the emergence of OpenAI, has the potential to address the limitations.

4 ways AI can help advance the healthcare industry
The healthcare industry often functions inefficiently, meaning patients don’t always receive needed treatment. However, emerging AI solutions have the potential to change the landscape significantly. These products could be the most important technological advancement since the turn of the millennium. They can analyze large (hundreds of billions of words) and complex data models (hundreds of billions of parameters), then offer simple, intuitive interfaces. Consequently, enterprises can quickly assimilate the technology into their organizations.

Here are four ways that AI can benefit the industry in the near future.

1. Improve patent engagement
One rapidly evolving area is the doctor-patient relationship, which has been morphing from a once-a-year visit to ongoing collaboration. The shift promises to advance patient care and outcomes, but it creates a lot more work for doctors. Because of recent technology advances, patients are equipped with more information, which of course, leads to more questions. Doctors can sometimes struggle to respond to them all.

Interactive virtual assistants are one option for improving the situation. The software does more than point a user to a string of URLs whenever they ask a question. These systems can provide short written responses, highlighting trends, benefits and shortcomings. For instance, if a person isn’t feeling well, they can log their symptoms with the virtual assistant and receive a list of potential diagnoses, as well as guidance on what steps to take next.

2. Advance treatment
Technology is also changing the treatment process. New Internet of Things devices provide patients with personal health information, like their heart rate, blood flow and glucose level, on a continuous basis.

Individuals are busy, and their actions are imperfect. Chatbots can remind patients to check their vital signs and take their medication. Additionally, the systems can notice anomalies and trigger actions, such as informing a person with diabetes that their glucose level is low, so they eat. These products also send alerts to medical staff if any changes should concern them, enabling providers to remotely evaluate the situation and decide on the next steps.

3. Streamline business processes
Healthcare is a forms-intense business. New AI tools can automate administrative tasks, such as processing insurance claims or determining coverage. Scheduling has also become more challenging, given the growing influx of information. Intelligent digital technology can consolidate current processes. Rather than an army of administrators serving as gatekeepers between doctors and patients, the right digital tools enable individuals to book appointments via their phones, lowering costs and improving responsiveness.

4. Simplify research
The volume of research now being conducted has increased significantly. There aren’t enough hours in the day for an expert to check all of the clinical trials, studies, comments and related information sources. Recent technical advances offer potential within the research process. AI solutions can improve participant recruitment, inform patients about clinical trials and assist them in determining their eligibility and speed up sign-up. This tech can also analyze large amounts of medical data and identify patterns that humans might miss.

There Are Still Potential Problems With AI
While emerging AI solutions are tools to increase healthcare provider efficiency, they’re still manufactured machines and not omnipotent systems. So, hospitals need to supplement their use with the human touch.

Algorithms are not doctors
One challenge with incorporating AI tools is defining the line between advice from an experienced doctor and a generic computer-generated recommendation. Typically, there’s little-to-no human oversight of AI responses. Any data model is a best guess and only as good as the volume of data collected and the tuning of its algorithms. Ideally, they get better with more input, but they never reach 100% certainty.

Data bias is a related issue. No matter how diligent data scientists are, bias arises in many ways. For instance, it may stem from a sample group that underrepresents certain demographics or the architects implicitly or explicitly favoring a certain outcome.

Additionally, every person reacts differently to medical problems and treatments. Doctors have more experience navigating such nuances; AI does not. So, healthcare companies need to meld the technology and doctors’ knowledge to provide each patient with their best diagnosis and treatment plan.

Data security concerns
The more data an AI model has, the better its results. However, consumers have been resistant to data collection, and laws have been put in place to protect their privacy. For instance, the Health Insurance Portability and Accountability Act (HIPAA) demands that healthcare companies keep patient information confidential. The law applies not only to caregivers but also to their partners. So, it becomes incumbent upon AI suppliers to collect, store and use patient information in an anonymized manner.

Healthcare delivery is complex, time-consuming and costly. New AI solutions have the potential to help providers address their various pain points. With these tools in an early stage of development, there’s time to put thought into how—and how quickly—this next round of advances can get assimilated into the healthcare organization. Forbes