In recent years, there has been mounting interest in artificial intelligence (AI) in the healthcare industry. Technocrats believe that healthcare providers must work to become technologically aware so they can provide optimal care for patients. In this article, we looked at how AI use is shaping the healthcare industry, including its impact, implementation challenges, and current and potential applications.
5 Ways AI Use is Impacting the Healthcare Industry
The use of AI within the realms of the field of medicine is growing rapidly. By 2025, the market is expected to be worth US$28 million worldwide, which could mean more advancements. At present, AI systems are used for:
1. Prescription management
The National Institute of Health currently uses the AiCure app, which helps it monitor a patient’s intake of medication. When installed on a smartphone, the device’s camera automatically verifies if a patient is diligently taking his/her medication. Most of the patients who AiCure have critical illnesses, are part of clinical trials, or often forget to heed his/her doctor’s advice.
2. Health monitoring
Wearables or health trackers are now widely used by many individuals to monitor their heart rate and other health statistics. Wearables like FitBit, Garmin, and Apple Watch can notify their users if it’s time for their exercise. Users can share the data their wearables collect with AI systems and their doctors for regular health monitoring.
3. Drug discovery
Clinical trials take years to finish, which just won’t do in case there’s a crisis (e.g., when there’s a disease outbreak). AI can speed up this process. An example would be during a recent Ebola virus outbreak. An AI-powered program helped scan for existing medicines that could be reformulated to help combat the virus. After only a day, the program found two medications that were then used.
Meanwhile, natural language processing (NLP), a subset of AI, is also proving useful for:
4. Clinical documentation
NLP can quickly identify missing information from a patient’s clinical records that can be vital for accurate analysis and treatment provision.
5. Coding
Instead of manually encoding data into electronic health records (EHRs), AI-powered systems can instead be used. That would not only hasten the process but also lessen errors. Developers can program the systems to spot and correct potentially inaccurate information automatically.
In the future, it won’t be surprising to see AI personalize healthcare services and predicting illness outcomes. Before that happens, however, the technology needs to address a few challenges.
Understanding the Challenges of AI in Healthcare
Why are we not seeing widespread AI adoption in healthcare? Here are some possible answers:
1. Regulations
If you look at other industries, it is easy to see AI in action. The main reason is that it is easy to gather and access the information necessary to develop an algorithm for other sectors such as manufacturing. When it comes to the healthcare industry, meanwhile, accessing data is pretty challenging because it is highly regulated.
For example, applying the predictive capability of AI to ultrasound technology requires a massive volume of images to analyze to train an ultrasound device properly. Ultrasound images like any other EHR are privacy-protected by strict Health Insurance Portability and Accountability Act of 1996 (HIPAA) regulations. Developers would need to seek the permission of each patient to use his/her information as input.
2. Data integrity
AI systems are highly dependent on the quality of the data they receive as inputs. As such, a capable device would need information that has been verified and declared accurate before use as training input. Many AI system vendors struggle when it comes to gathering high-quality datasets. It doesn’t help, too, that most EHRs are not filled up directly using computers. They rely on manually completed forms that are then digitized later on, which can be subject to misinterpretation and other human errors. These errors can affect the AI algorithm, causing devices to malfunction.
3. Industry conservatism
While some patients are more open-minded about technology use, many are still wary about entrusting their medical records to machines. Many people worry that their digitized documents can be mishandled and manipulated by unscrupulous individuals, giving them more problems.
Final Thoughts
AI can push the boundaries in the healthcare industry. It offers solutions to many of the pain points of healthcare providers, including how to provide diagnoses faster, hasten the process of drug creation, lower costs, and improve accuracy. However, while it may take years for AI to be fully harnessed in the healthcare sector, its impact is already undeniable.
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