Applying artificial intelligence (AI) in medicine is no longer a far-fetched idea. Details of these health care innovations capture the headlines and make people feel hopeful about what the future holds for better well-being. Here are some examples of how AI could help people stay healthier and avoid undesirable circumstances that hurt their quality of life.
Increasing Patient Medication Adherence
A doctor might prescribe a medicine for a patient, but that doesn’t equal compliance. Some people forget to take their pills regularly. Others intentionally don’t take them, perhaps due to fear or a lack of education about a particular medication’s associated benefits.
Advances related to artificial intelligence in medicine could reduce those possibilities. One company uses AI to identify high-risk patients that need to refill their prescriptions soon or are past-due for doing that. It then provides opportunities for personalized interventions that get to the heart of a patient’s failure to follow orders.
The organization found that a dual-intervention approach whereby a call center representative and pharmacist contacted those people caused a notable uptick in prescription refills. More specifically, the patients who received both calls were 52% more likely to go to pharmacies to replenish their medications within two weeks.
People outside of the medical industry might think it’s not a big deal when patients don’t follow doctors’ orders. However, researchers frequently find links between a lack of medication adherence and unwanted consequences, including more hospital admissions and office visits and reduced control of chronic conditions.
Spotting Warning Signs Before Patients Notice Symptoms
The use of artificial intelligence in medicine also enables a more proactive approach to good health. Before the technology existed, patients might have only visited their providers once symptoms became so bothersome that they couldn’t wait any longer to act. By then, though, a condition might be in a phase that’s harder to treat effectively.
However, an algorithm could monitor a patient at home and alert their doctors to changes that could indicate a worsening illness. The use of electronic health records (EHR) also facilitated this use of AI.
Keeping a digitized record of a patient’s status during and outside of office visits helps providers stay more informed. Then, doctors spend more time interacting with patients in meaningful ways while reducing the minutes spent getting details about a symptom.
That’s crucial since some patients need treatments before they experience noticeable symptoms. Applying artificial intelligence in medicine like this helps doctors stay up-to-date on what happens with their patients’ conditions — even when those people are at home.
Reducing Incorrect Diagnoses
Physicians have years of specialty experience, but they sometimes make mistakes when identifying a patient’s illness. This reality causes frustration for everyone involved and can waste precious time. Misdiagnosis also happens more frequently than you might think — to between 12 and 20 million people per year, according to some estimates.
Doctors face the challenging task of studying all the available information about a patient, then using their best judgment to identify the problem and choose a treatment plan. Artificial intelligence tools could detect patterns that humans don’t initially see. Those insights give providers a more thorough picture of the situation, which could improve their decision-making abilities.
Artificial intelligence in medicine also works well when a patient complains of a problem that a doctor cannot confirm during an office visit. For example, they might mention, “Sometimes my heartbeat feels funny when I’m lying in bed.” That person may have an arrhythmia, but the chances of it occurring during the limited window of a physician’s examination could be slim.
AI-based diagnostic products have become so advanced that doctors can catch irregular heartbeats by asking a person to wear a specialized patch at home. Some of those devices work with an algorithm that received training on more than 90,000 electrocardiogram readings, then learned to recognize 10 different heart rhythm abnormalities.
Minimizing Shortages of In-Demand Drugs
Finding drugs to meet emerging needs is only half the battle. It’s also crucial to figure out how to synthesize those products fast enough so that the patients who need them can access them at reasonable prices.
A commercial product called Synthia uses AI to help scientists find the fastest and least expensive synthesis options for COVID-19 therapies. Only two drugs offered the necessary proof that they could fight the virus, but researchers are investigating 12 others.
The tool found new ways to make all but one of the dozen compounds. That means if one or more proves effective, teams can immediately start making the required supplies.
Such an advantage could have a tremendously positive impact on public health outcomes associated with the novel coronavirus or other serious illnesses. After all, even the most innovative drugs can’t reach their full potential if they’re out of reach to most people.
Tracking Behavioral Trends in People Who Use Mental Health Crisis Lines
The teams who staff phone lines used by people going through mental health crises are often the first to encounter callers’ distress. Many people going through hard times keep their true feelings hidden and only confide once they reach rock-bottom points. They may decide that reaching out to a stranger feels safer and less embarrassing than admitting an internal struggle to a loved one.
Thus, helpline workers must stay abreast of why callers reach out, when they do and what formats they use to connect. If a person in need feels that getting help is too cumbersome, or they get the wrong advice when seeking assistance, the outcomes could become disastrous.
A university project used machine learning to find patterns in the behaviors of people who utilized an Irish support line that often — although not exclusively — assists those dealing with mental turmoil. Researchers examined three years of telephone records and determined that the findings showed them valuable details about the service users availing of the help.
This undertaking could cause more progress when using artificial intelligence in medicine to optimize mental health. For example, if data shows that most people contacting helplines have never received mental health interventions, employees might walk them through the benefits of talking to their doctors about their troubles and possibly pursuing medication or therapy.
Using Artificial Intelligence in Medicine Is Worthwhile
Artificial intelligence is not an error-free technology, and it won’t replace health care providers’ expertise. However, examples like these reveal it pays off to keep exploring how AI could help people feel better and empower doctors to make more confident decisions.
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