Can AI be Trusted in Healthcare?
Artificial intelligence (AI) is augmenting the human workforce in many industries and healthcare is no different, where AI is being used to elevate patient care and enhance patients’ health and well-being. But, as with all new technologies, there are always hesitations and concerns. Today we are going to discuss some of the top concerns about AI in healthcare as well as the top benefits to clinicians and to the patients.
Is AI trustworthy and credible?
With so many people now relying on and trying out AI-driven healthcare solutions, it becomes necessary to address the concerns around trust and credibility. For instance, there is anxiety and even social stigma attached to a patient sharing their symptoms around certain diagnosis like depression or bipolar disorder. However, the same patients are increasingly comfortable sharing their experiences and feelings with bots, whose objective understanding and reactions can ease anxiety when talking about such vulnerable, personable information. So more than ever before, from an industry perspective, a healthcare organization needs to be trustworthy about the level of security in which this information is handled.
Similarly, people have been diagnosing themselves using Google search results for as long as the internet has existed and it’s only gaining momentum. Here enters the credibility factor. We trust doctors and surgeons because of their diplomas and degrees. Even if given a better alternative in terms of technology, we may not readily accept it as credible. To help patients more readily trust a bot’s recommendations, a conversation with their clinician may be required. If their trusted clinician can explain to them the recommendations the bot will be making and a little bit about how those recommendations are populated, skepticism can be tempered, and the patient can be put at ease knowing the bot and their clinician are on the same page and working together for the patient’s benefit.
Research in AI — Healthcare
The following fields are undergoing the most research in terms of utilizing AI in healthcare:
● Radiology
The research in AI in radiology has been quite promising. An algorithm prepared by a Stanford University study was able to detect pneumonia in patients with better accuracy than human radiologists. The results were so much better, that some specialists have started looking at the technology as a threat. However, there needs to be the right mix of AI and human involvement for the one common purpose of healing people, because machines cannot show the empathy and other soft skills required for the successful treatment of patients.
● Tele-health
Tele-health is the monitoring of the patients’ various health metrics remotely through AI-driven apps and smart devices. Data from a smart wearable device could be used by the users’ doctors to monitor their condition. These devices and apps can help identify changes so minute that a clinician could have missed them and can sift through large sets of data faster than humans, quickly identifying health problems before they become catastrophic.
● Electronic health records
Digitization of patient health records (EHRs) has been helpful but equally vulnerable to cognitive overload and other sets of problems. Today, customizing EHRs to make them easier for clinicians is largely a manual process, and the systems’ rigidity is a real obstacle to improvement. AI aids in the automation of a lot of these processes and has even included Natural Language Processing tools for process improvement. AI, and machine learning specifically, helps EHRs continuously adapt to users’ preferences, improving both clinical outcomes and clinicians’ quality of life.
Being a sensitive and emotion-dominant field, any technological advancements in the healthcare field must be done diligently. If done right, AI can provide a range of benefits to the patients, major ones being:
● Decreased medical costs
AI is expected to bring down the currently exorbitant costs of getting medical care as the procedures become more accurate and medical staff become more comfortable with new processes.
● Robot-Assisted Surgery
This is projected to be the most invested in AI application for healthcare in the coming years. It’s also a perfect use-case of human augmentation. As Accenture puts it in a recent report, “Cognitive robotics can integrate information from pre-op medical records with real-time operating metrics to physically guide and enhance the physician’s instrument precision.”
● Brain Computer Interfaces (BCI)
A major use of AI in healthcare is going to be better treatment for the patients suffering from inability to move or speak, or those with spinal cord injuries. BCI shall employ AI to help patients move easily and communicate better by tracking their neural activities to allow them to go ahead with their intended movement.
● Virtual nursing
Virtual nursing is expected to become mainstream by utilizing AI to find out the answers to a patient’s queries on a 24/7 basis. This can help patients from frequent and pricey hospital visits and enable wellness checks through AI to drive better medical outcomes at a lower cost. Virtual nurses will also able to manage, monitor, and communicate using unique insights and real-time notifications. (See our previous blog on Remote Patient Monitoring)
It is quite clear that if done right, AI is going to become an important part of our healthcare machinery. It will enable doctors and other specialists to be more efficient in providing the right treatment to their patients in less time.
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