Top 4 Ways Artificial Intelligence Will Impact Healthcare


Healthcare systems need to evolve with the patient, ensuring they offer quality care and fill in gaps. They also need to identify patient risks and proactively prevent treatment delays. Using artificial intelligence tools in healthcare, hospitals can better monitor a patient’s journey to ensure it is safe and effective. This technology can help hospitals save money and improve patient outcomes.

AI can improve patient care:

AI-enabled solutions have the potential to improve patient care radically. They can automate diagnostic tasks, support users with faster answers, and improve workflow. They can also help create new treatments and therapies. These technologies will require a concerted effort by providers and professional bodies to ensure they are fully integrated.

It can reduce cognitive burdens for physicians:

Artificial intelligence (AI) is a powerful tool that can free up cognitive and emotional space for physicians. It can organize information overload, such as patient data, evidence-based practice guidelines, and compliance monitoring checkboxes, so physicians can focus on more important tasks. AI can also automate routine tasks that can be a burden to physicians. This will free up physicians’ time for their most important diagnostic tools – their undivided attention.

It can help identify patients at risk of developing a condition:

The use of AI in healthcare has huge potential to improve safety. AI can help detect patients at risk of developing a condition, improve diagnoses and prevent medical mistakes. However, AI is not without its challenges. Organizations will need to gather large datasets from multiple sources to build robust AI models. This includes traditional and novel data sources. Organizations will also need to develop workflows for data-driven analytics.

It can reduce medical liability:

In some cases, artificial intelligence (AI) systems may reduce liability for medical providers. For example, an AI system may detect a lung nodule on a chest radiograph and flag it for a physician. A human expert must also be included in the system to provide additional expertise. However, even the best AI system may make a mistake, resulting in new liability for the provider.

The legal framework for the medical profession does not yet provide any precedent for what happens when AI results in harm. As a result, AI implementation may face stiff resistance from the legal and medical communities. For now, this uncertainty will force providers to make difficult choices in the face of potential liability.