The Pros and Cons of Artificial Intelligence in Healthcare

healthcare worker

Artificial intelligence (AI). It’s become so prevalent and capable that it’s almost as if every conversation is peppered with its potential. In the healthcare industry, AI has provided healthcare institutions and practitioners with tools that they can use to reduce pressure on their workloads and redefine their workflows. Some of the tasks undertaken by AI in healthcare are repetitive, time-consuming and tedious. Others are technical, complex and managed by algorithms trained to provide real-time clinical decision support. However, there are pros and cons of artificial intelligence in healthcare – no one technology is the ultimate solution to all that ails an industry – and so AI must be implemented strategically and expectations managed intelligently to get the desired outcomes.

Pros of AI in healthcare 

Clinical decision making

The benefits of AI in healthcare are well documented. According to the Healthcare Information and Management Systems Society Inc. (HIMSS), AI in healthcare has helped change clinical decision making thanks to its ability to provide decision makers with essential, real-time data that can be used to diagnose patients, plan treatments, and manage population health. There are solutions that are capable of leveraging insights in genomic, biomarker and phenotype datasets and solutions that have specialized in radiology, pathology identification and ophthalmology.

Streamlining processes

There are solutions that are intelligent enough to identify possible markers on radiology images and there are solutions that ease the physician admin burden by translating clinical notes or streamlining appointments or tracking patient notes and care recommendations. In essence, the benefits of AI in healthcare are as numerous as the applications for which it is invented and applied.

Information sharing

healthcare data using artificial intelligence

In addition to physician support, the benefits of AI in healthcare extend to information sharing and precision medicine. AI can be used to track specific patient data more accurately – an essential tool in weighty healthcare institutions such as the NHS – and thereby allow for more accurate patient care and improved doctor time to patient ratios. In 2019, the NHS established a national AI lab with health secretary Matt Hancock pledging £250 million to increase its future role within the healthcare sector.  In terms of precision medicine, according to the U.S National Institute of Health, AI can be used to increase outcome precision and accuracy and it can be used to potentially identify patterns within patient data to determine their probability of getting a specific disease or illness. This level of insight can have immense value to the medical profession as it can fully streamline patient care and reduce potential risks by addressing their root causes earlier. AI’s ability to read and analyze vast quantities of information is the key to unlocking the full potential of precision medicine.

Cons of AI in healthcare

That said, there are both pros and cons of technology in healthcare. AI is not perfect and there are numerous challenges ahead. It is not going to swoop in and fix legacy challenges and overcome insurmountable odds. The benefits of AI in healthcare are only as relevant as the strategy that implements the AI and the approaches that recognize the risks and the cons of the technology itself.

Human Assistance

AI is excellent at executing specific commands which it has been programmed to do. One of it’s big cons is that AI is not yet ready to work on its own; AI must continue to work in tandem with physicians.  In the radiology profession, for example, AI systems are utilized as support systems for radiologists who are the ultimate decision makers on patient diagnosis and management. The AI is a second pair of eyes to the intern that never sleeps, but needs the human expertise to ensure that the results are accurate and relevant.

Implementing the right AI platform

Another con of AI in healthcare lies in seamless deployment in clinical environments. The technology isn’t completely in its infancy right now, but it does need to be refined and adapted consistently as lessons are learned and algorithms become more adept. Medical institutions need to invest into AI carefully, strategically, and with the right partners. There are plenty of organizations claiming that their platform and solution is the right one, but not all AI solutions are created equal. The risk is that a healthcare practice implements an AI platform that doesn’t have rigorous controls or accreditations.

Aidoc’s solutions are clinically proven and have deployed at more than 400 leading medical centers worldwide. Its solutions have analyzed studies of more than three million patients to improve the value and accuracy of the algorithm and the AI. The company has several FDA cleared solutions including triaging incidental findings in medical imaging and C-Spine; has received six CE marks; is compliant with the EU safety, health and environmental requirements; and is continuously investing into new ways of providing medical professionals with critical support. Aidoc collaborates with healthcare to build answers to specific problems in a strategic and coherent way. Focusing on strategy, deliverables, and measurable results, Aidoc is focused on eliminating the cons of AI healthcare while emphasizing the benefits.

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