Artificial intelligence, or AI, has proven itself as a key resource as hospitals seek to enhance their clinical decision making in a way that allows them to provide high quality care in a way that is still affordable to patients and payers alike. And while the clinical applications may seem like something from a sci-fi movie, AI has already helped improve quality of care for patients in some ways that would have previously been unthinkable only 10 years ago. This is evidenced by the fact that “as payment structures evolve, patients demand more from their providers, and the volume of available data continues to increase at a staggering rate, artificial intelligence is poised to be the engine that drives improvements across the care continuum”1. Here are 12 ways AI is currently helping hospitals satisfy the quadruple aim as they strive for continued improvements to patient care:
- Creating communication channels through computer interfaces. Computer interfaces have created a unique application for technology to serve as a means of communication for patients who have lost their ability to communicate verbally.
- Making radiology tools less invasive. Researchers hope to replace the need for tissue samples using artificial intelligence to offer non-invasive visibility into physical tissue in a way they have not been able to do so previously.
- Expanding care to previously underserved regions. AI has proven itself as a key element in the expansion of quality care to patients in remote locations in the hope that advanced medical devices will be able to replace the need for highly skilled clinicians to diagnose ailments. Additionally, AI hopes to deliver care with greater accuracy through machine learning and consequently expand care to previously underserved regions.
- Reducing downtime associated with Electronic Medical Records. Voice dictation and talk-to-text applications have proven useful as hospitals seek to streamline the administrative duties associated with maintaining health records.
- Analyze patterns in antibiotic resistance. One major application for artificial intelligence is within population health. Because AI has the ability to analyze large amounts of data (electronic medical records), it is able to identify patterns to determine which patients are at greater risk and notify clinicians so that they can take the appropriate measures to adjust that patient’s care plan.
- Improving precision in pathology images. Physicians are beginning to move toward treatment plans based on AI algorithms rather than clinical staging or histopathologic grade treatments. As AI continues to develop, the hope is that diagnostic accuracy will also improve as a result of more precise pathology imaging.
- Expanding the scope of smart devices. Applications for smart medical devices have also been developed for critical care environments. These devices allow clinicians to monitor patients and notify them if they detect that sepsis may be developing, etc.
- Developing individualized immunotherapy treatments. Immunotherapy has gained recognition in recent years for its potential as one of the most promising cancer treatments. AI is able to analyze large data sets in order to help develop individualized treatment options.
- Using health records to create risk predictors. Through its ability to analyze large data sets, AI has the potential to use electronic health records to create reliable risk predictors that clinicians can in turn use to identify at-risk populations and develop proactive care plans.
- Using wearable devices to share information with healthcare providers. Watches and other devices that gather health data such as heart rate, calorie consumption, etc. can be used by clinicians to monitor patients remotely. In doing so, clinicians may be able to compile a much more accurate picture of their patients’ health by using months of data stored on a wearable device than they would otherwise by just using the information gathered during patient visits.
- Utilizing smart phone technology to enhance telehealth capabilities. Computer algorithms have been used to analyze digital images of patients that they are able to then use in order to diagnose patients. This is especially promising as some healthcare providers are utilizing telehealth capabilities which allow clinicians to provide care in remote locations when they might not have access to care otherwise.
- Leveraging AI to enhance clinical decision making. As healthcare continues to shift its focus from reactive to proactive, AI has the potential to help clinicians get ahead of chronic diseases. It is able to do so by detecting those who are at risk for certain diseases and alerting healthcare providers so that they are able to proactively develop care plans. To add to that, AI can also help detect subtle improvements in data trends that might otherwise go unnoticed which can signal whether a treatment plan is working or if it needs to be changed. AI can be used to leverage clinical decision making and enhance quality of care in a way that has not previously been possible before.
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