Artificial Intelligence (AI) is gracely bringing changes in how organizations do business. Hospitals are not any exception to the rule. As the technology is advancing rapidly, it will definitely help hospitals in providing better care in so many ways in nearby future.
Indeed, some hospitals have already started making use of the benefits of AI in their process. Let’s take a look at how AI is put to use in health care management.
AI in healthcare
1. Insurance verification
AI can help with verifying insurance for the doctor’s office. The digital verification of insurance coverage information can help in reducing manual calls that are needed to confirm whether a patient’s insurance details are correct and valid.
2. AI chatbots
AI chatbots for healthcare are primarily used for patient engagement. AI bots in mobile messaging applications are able to assist patients quickly by just sending a message.
AI health chatbots are capable of answering health-related queries and also can help patients to manage medications by providing detailed information on varieties of medicines and the doses recommended for them.
Some developments are done to chatbots to embrace the flexibility to:
- Understand and to mime human conversations
- Observe the patient’s emotions to modify empathetic engagement with them
- Integrate language processing, sentimental analysis and thought mining into chat scripts
- Execute complex image recognition tasks to investigate photos, barcodes and handwritten notes
3. Virtual health assistant
Virtual health assistants (VHA) are dedicated to help patients in a wide variety of ways. For example, VHA can offer its hands on helping dementia patients to be on track with their prescribed medicines by sending timely reminders.
In addition, VHA might offer guidance on treating common medical conditions or offer receipes for patients with diet restrictions. Based on information of patients, VHA may monitor patients, enable doctors to interact with patients and help pharmacies in reminding patients about prescription refills and medicine pickups, and even suggest about preventive health screenings.
Artificial intelligence has been used to enhance medical diagnosing. For instance, AI assisted medical image diagnosis is being employed to enhance reading x-rays and CT scans.
The technology, which is employed in hospitals in China, will sight suspicious lesions and nodules in lung cancer patients. This helps doctors in early diagnosing rather than sending tissue samples to a research lab for analysis and then providing treatments.
Researchers at Standford University have developed an AI algorithm that can detect and diagnose skin cancer.
Alphabet, Google’s parent company is focussing on developing AI program to identify metastasis making use of high level image recognition facility.
The particular AI program will be able to identify metastasis faster than a conventional method, which again leads to earlier diagnosis and subsequent treatment.
As AI is capable of analyzing larger volumes of data, it can help a lot in detecting diseases and thereby helping with clinical decisions.
5. Emotional intelligence indicators
As AI virtual health assistants are evolving rapidly, more focus is given into making it emotionally intelligent. Like as mentioned before, focus is to grasp hints from conversation or effort to understand the person’s feelings and mood.
By analyzing the voice of patients, AI platforms might be able to detect depression or even chronic conditions like heart disease.
6. Treatment planning
AI systems are created to research information which includes notes and reports from a patient’s case file, external analysis and clinical experience which can assist in choosing the proper and an individual based customised treatment path.
7. Medication management
Smartphone application like AiCure App is designed to watch the usage of medication by a patient. Smartphone’s digital camera is partnered with AI to make sure that patients are taking their medications and to help them in managing their condition.
Most typical users may be patients with serious medical conditions, patients who are more proned to go against doctor’s advice and folks who are facing clinical trials.
8. Detection of tuberculosis
Researchers are trying their hands on training AI to identify tuberculosis from chest X-rays. It is an initiative that might help in faster screening and evaluation of tuberculosis.
9. Detection of brain bleeding
Combination of AI forces of IBM Watson Health and Medymatch technology can help doctors in hospital emergency rooms to detect intracranial bleeding which can be a result from a head trauma or a stroke.
Based on deep learning, patient information, machine vision and clinical insights, Medymatch algorithm highlights the areas for a physician that could point out the potential presence of brain bleeds.
10. Health monitoring
Health trackers such as FitBit, Apple etc. that can be worn can monitor pulse and activity levels. They will send alerts to the users to induce additional exercise and might share this data to doctors and AI systems for added data points on the wants and habits of patients.
Risks of applying AI in healthcare
Safety and Accuracy
As the artificial intelligence is a fairly new concept, chances are high that it can be less correct and reliable thereby putting patient’s life into a risk.
So AI needs to be reliable enough to keep sensitive information, such as addresses, monetary and health info secure. Establishments that normally handle sensitive medical information are compelled to confirm that their valuable data stays safe.
Adaptation to new health cases
Not solely ought AI to be correct and safe, it has to programmed in such a way that it has to be up to date with exceptional and new health cases.
A program can solely be nearly as good because of the information it learns. Programs ought to be trained, constantly updated and also it should be able to determine new and exceptional cases.
Risk posed for doctors and patients
AI may create risk for patients and doctors. Since AI’s implementation is not completed, doctors cannot totally trust AI and still ought to build selections that supported the doctor’s information and experience.
Patients are also in danger for the same reason. If a program provides misinformation, patients won’t be treated properly.
Challenges faced by AI in Healthcare
Adoption of technology
One of the main challenges faced by AI in healthcare is the widespread clinical adoption of the technology. To appreciate the worth of AI, the healthcare industry has to produce personnel that’s experienced in AI so that they will be comfortable in using the technology thereby sanctioning the AI technologies to study and grow smarter.
Training for doctors and patients
Another challenge faced by AI is coaching doctors and patients to use artificial intelligence. Learning a way to use technology could also be a challenge for a few.
Furthermore, not everyone seems to be hospitable to the information given by a robot. In alternative words, acceptive AI technology could be a challenge that has to be addressed through education.
Complying with regulations is additionally a challenge for AI within the healthcare industry. Additionally, there is the necessity for approvals from Food and Drug Administration before applying AI to the healthcare.
This can be very true as a result of AI being at aborning stage and also not a technology that’s absolutely familiar.
Furthermore, the prevailing approval method deals a lot with AI hardware and not concerning knowledge. Hence, knowledge from AI poses a replacement restrictive challenge for Food and Drug Administration and need to be more thoroughly validated.
How AI can help hospitals in healthcare management?
AI is gaining attention in several fields. AI has the likelihood to own an enormous and positive impact for patients and doctors in healthcare.
Due to the flexibility to mixture and analyze a huge quantity of various information, AI may yield considerably quicker and a lot of correct diagnoses.
Favourably, AI will arm your team with the information and insights you would like to achieve the dynamic environments.
If you perceive doctor performance and variation by type of patients, you will be able to choose the best physicians to handle high risk patients.
The complexness of profiles of patients makes this a tough method without the tools to automatically perceive, sort and analyze the outcomes by physicians.
Likewise, technologies like AI will assist you in guiding behaviour at intervals within your healthcare group in finding out cost areas which can be managed efficiently.
You will not solely able to understand the best physicians to treat certain patients, but also the most effective treatment arrangement that helped those patients to heal quickly and cost effectively.
By adopting technologies such as AI, we are able to contour and improve patient care whereas reducing prices for the whole healthcare system.
The capabilities of artificial intelligence might intimidate some individuals, however futuristic and smart hospital executives would be wise enough to follow developments associated with AI and healthcare.
Also, it is a wise idea to talk with IT to find it out whether your hospital will be able to take up AI smoothly.
To thrive in an environment that is more focused on quality and better patient outcomes, you need to embrace new technologies and incorporate effectively it into clinical workflows.
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