Healthcare is a uniquely complex industry. From the detailed regulations that govern patient information to the extensive training required of practitioners, there is so much to consider in both care and administration.
AI (artificial intelligence) has the power to change healthcare for the better. And it’s not as if transforming healthcare with AI is a far-off goal. There are plenty of examples of AI in use throughout the healthcare industry, as Mobi Health News shares. AI can support everything from more accurate diagnoses to supporting new drug discovery, as well as more efficient processes for administrators.
Let’s take a closer look at three cutting-edge examples of AI in healthcare.
1. Healthcare Smart IoT: Next-Generation Inhalers
Econsultancy highlights a smart inhaler designed to share richer, more complete data about use on the individual patient level with providers. Developed by UK company QIoT, this device will enter trials in Scotland.
The inhaler can play a crucial role in developing more effective and personalized treatment plans. Through an associated app, this smart Internet of Things (IoT) device can also support proper technique and provide reminders to use the inhaler as intended. Additionally, AI will play a key role in connecting patient data with pollen counts and other information about respiratory triggers. That’s even more useful context for patients and providers.
2. AI Supporting More Effective Pathology
Developing more accurate diagnoses is a crucial goal for healthcare professionals. Cleveland Clinic recently entered into an agreement with AI research and pathology tool and service provider PathAI, as Health IT Analytics explains. The collaborative effort will help PathAI enhance its AI pathology algorithms while also supplying practitioners with AI-driven diagnoses.
This is one example of smart healthcare technology offering benefits now and in the future. As these algorithms learn by processing pathology slides over time, the diagnoses provided will only become more accurate. AI and machine learning offer a new path for improvement in the healthcare industry.
3. Predictive Analytics and AI for Utilization Management
Utilization management (UM) is a crucial consideration for every hospital and health system. At the same time, it’s often seen as an administrative burden that limits highly skilled clinical staff to checking off boxes and reduces time spent with patients. Effective and efficient management of this process leads to better outcomes for providers, patients, and organizations as a whole.
With the right combination of AI and predictive analytics guiding UM, that process no longer has to be a pain point for providers. CORTEX, now known as Dragonfly, Xsolis’ AI-driven UM solution, offers support in four vital areas:
- Identifying patient status conflicts, which reduces denial risks
- Improving communication with payers to support more mutually beneficial relationships
- Supporting accurate reimbursement for patient care provided
- Improving efficiency by empowering nurses to focus on the cases that matter most
Through the power of its CORTEX platform, Xsolis is leveraging AI to transform UM into a more precise process that adds increased value for providers and payers alike. Learn more today – request a consultation here.