Artificial intelligence is intelligence that’s exhibited by machines rather than humans or other animals. Artificial intelligence is also the study of intelligent agents and devices that perceive their environment and takes action to maximize its goal or instruction. Artificial intelligence is when a machine can mimic cognitive functions that are human-like such as learning and problem-solving. An advanced research in artificial intelligence seeks to create machines that can learn from themselves and further mimic cognitive reasoning. There are different schools of thought to the use of AI and the further advancement and if it’s crossing morals lines. In the healthcare industry, artificial intelligence is specifically useful because of the continuous need to sort through big data. Managing big data is very important in the healthcare industry, however, there are frequent setbacks that necessitate the need for more advanced tools such as Healthcare AI.
These problems associated with bid data can be summarized into two: Data complexity and the changing regulatory requirements.
Data Complexity: Big data is huge and complex as the name suggests and for this reason, health organizations usually struggle with navigating it. But this type of data is incomplete. Clinical data from sources like EMRs give a complete picture of the patient’s story. While developing standard processes that improve quality is one of the goals in healthcare, the number of data variables involved makes it far more challenging. You’re not working with a finite number of identical parts to create identical outcomes. Instead, you’re looking at an amalgam of individual systems that are so complex we don’t even begin to profess we understand how they work together (that is to say, the human body). Managing the data related to each of those systems (which is often being captured in disparate applications), and turning it into something usable across a population, requires a far more sophisticated set of tools than is needed for other industries like manufacturing.
Changing Regulatory Requirements: We’ve talked about Medicaid and the Affordable Care Act in the past and how important it is for healthcare organizations to be up to date and adhere to the ever changing yet strict rules and codes. Regulatory and reporting requirements also continue to increase and evolve. CMS needs quality reports around measures like readmissions, and healthcare reform means more transparent quality and pricing information for the public. The shift to value-based purchasing models will only add to the reporting burden for healthcare organizations.
Artificial intelligence does more helping ease the load with the two common problems mentioned above that are faced by healthcare organizations. It also helps further advancement in different areas of healthcare organizations and eases the load.
Some of the ways it does this are:
Early and precise Diagnosis: Artificial intelligence algorithms can analyze millions of samples quickly and efficiently and identify usage patterns. This is a very useful advantage when it comes to treating, preventing, and caring for patients with dangerous diseases. Detecting the symptoms on time and correct diagnosis can lead to an early and complete cure. A wrong or untimely diagnosis can be fatal and artificial intelligence has helped reduce the fatalities and improve efficiency. This has also lead to hospitals being able to provide dynamic care. As mentioned above, artificial intelligence can be used to diagnose illnesses but AI can also be used to identify the right treatment paths and adapt it to changes in patient health. This kind of dynamic care is useful in cases where a different path of treatment can be used in the same disease when it is in a baby as opposed to an adult. Artificial intelligence will help identify these nuances and provide the most effective treatment plan.
Artificial intelligence Health Assistants: Normally when patients feel ill they go to a doctor who gives them a diagnosis and prescriptions. Some patients instead of going to the doctor go online instead to WebMD and similar sites. This is sometimes a very bad decision as they could misdiagnose themselves and a potentially serious illness could get unchecked. With Artificial intelligence assistants, they could provide clinical and outpatient services to people in an efficient way. The AI-powered chatbot could ask patients their symptoms and with the information provide prescriptions and even advise patients on when to see a doctor. This reduces hospital visits giving doctors more time to attend to more serious cases and also provided individuals with accurate information.