AI, otherwise known as artificial intelligence, has evolved dramatically in the last few years revolutionizing a wide variety of industries, including healthcare. Utilized across treatment processes and facilities, AI is transforming the interaction between patients and medical staff in remarkably positive ways.
What Can AI Do in Healthcare?
AI tools are utilized across the healthcare industry, assisting in the optimization of workflows, the analysis of crucial data, and in the research of future treatments. For instance, AI-enabled software can consolidate patient data across a facility, allowing clinicians and healthcare providers to easily access the same set of data from multiple different platforms. Not only can AI compile data, but it can process it as well and on a grand scale. For example, researchers are currently utilizing AI algorithms to increase the accuracy and prediction of outcomes by tapping into extensive sources of genetic, clinical, social, lifestyle and preference data. The bounds of how AI can help in healthcare are ever-expanding and have been shown to lead to some of the following benefits:
- Development of new healthcare tools and technology.
- Expanding access to healthcare in underserved or developing areas.
- Enhancing the intelligence of medical devices and machines.
- Advanced patient monitoring through wearables and personal devices.
- Revolutionizing clinical decision-making.
The possibilities of AI in medicine are expansive and when utilized appropriately have the capacity to improve all aspects of the treatment process.
How AI Supports Health Equity and Expands Access to Care
Artificial intelligence has the opportunity to expand health equity and increase access to adequate health care across the board. When AI and machine learning tools are developed properly, they can dramatically mitigate the harms imposed by healthcare provider biases. By analyzing health data transparently and impartially, patients can gain better access to the care they need. Additionally, machine learning software can learn from the collected data, and lead to more effective care options that can be tailored to specific cases. Currently, there is a focus on health equity in the development of AI and machine learning systems. In an ideal scenario, a care provider will collect data on their patient, use AI systems to analyze that data, then diagnose and prescribe treatment plans that can accurately meet the needs of the patient while avoiding any potential for provider bias. While more work needs to be done, researchers and experts are convinced that these tools will expand health equity and potentially enhance access to care.
Assist in Diagnosis and Treatment Decision Making
AI has proven incredibly useful in assisting healthcare professionals throughout diagnosis and treatment decision-making. AI software is able to sift through a vast database of electronic health records and compare a large data set against a particular patient. This form of AI can help providers stay alert of potential health problems, and, by comparing against the outcomes of others, can look for early warning signs of potential chronic illnesses. Through this trove of information, healthcare providers can gain better insight into a patient’s condition and set about courses of treatment that align with the patient’s needs and leads to proven successful outcomes.
Software utilizing automated algorithms can be used to analyze and review test results with the purpose of recognizing cancers and identifying rare diseases. For instance, a recent study published in the Journal of the National Cancer Institute found that AI could detect breast cancer with an accuracy level of 95% percent. In another peer-reviewed study performed by the Babylon Health and University College in London, researchers found that machine learning models and AI symptom checkers performed higher than 72% of general practitioner doctors when diagnosing test cases of illnesses. An additional study found that AI can be just as good if not better than trained doctors at detecting eye diseases.
AI for Remote Patient Monitoring
Healthcare providers are also in favor of finding ways to gather more data about their patients. According to a survey conducted by the HIMSS, more than half of healthcare providers believed that wearable tech could be helpful in monitoring patients. Additionally, approximately 70% of physicians surveyed were interested in finding new ways to gather more health data automatically.
Through AI and automated systems, patients can gain the benefit of a vastly improved patient monitoring experience. For example, wearable technology has been utilized to monitor patients remotely, including hardware such as smartwatches and fitness bands that can capture extensive health data. These digital tools can then share this data with healthcare providers and be analyzed by AI systems to provide physicians with greater context on the daily conditions of their patients. Wearable technology can utilize artificial intelligence to monitor the following concerns:
- Fall identification and prevention
- Physical activity and interaction
- Mental status
- Sports medicine
- Weight control
- Patient management
- Chronic pain management
- Heart and blood disorders
- Diabetes care
Utilizing AI Systems with Help from CNECT
Our nationwide team of GPO representatives can provide you with savings opportunities on a wide variety of suppliers that can equip your organization with leading AI software and platforms designed to optimize the way you administer care. When you become a CNECT member you’ll gain the guidance and expertise of a team of nationwide representatives dedicated to supporting your organization and providing custom savings strategies. Contact a CNECT representative to learn more about becoming a member today!