How AI is Revolutionizing Healthcare: Key Insights for CTOs

AI (artificial intelligence) and machine learning are two emerging technologies rising to prominence in the healthcare sector. With applications in medicine, procedural treatment, diagnostic processes, and business operations, AI could represent a new era of more innovative and more efficient healthcare services.

Implementing new technologies is always challenging, especially for CTOs who have to convince multiple levels of staff and management that innovations offer genuine benefits. By understanding the impact of AI in healthcare, CTOs can consider what changes they want to integrate and how to present these as wins for their healthcare practices.

The Rise of Artificial Intelligence in Healthcare

While AI may seem like an innovation, its roots originate as far back as 1950. Alan Turing devised a test called the Imitation Game to determine whether a machine could think and communicate like a human and whether a human would be able to tell the difference. Today, we refer to the Turing Test as the foundation of modern AI. 

It wasn't until the advent of deep learning in the 2000s that AI began to have profound implications for medicine. In 2010, endoscopy processes began utilizing computer-aided diagnosis (CAD) as an aid to processing and interpreting scanned images. Just five years later, Pharmabot, a chatbot dedicated to helping patients or parents understand children's medicines better, was launched.

Today, AI is being utilized at multiple levels of healthcare and across disciplines ranging from gastroenterology to oncology and beyond. 

Pattern Recognition for Faster Diagnoses

One of the most exciting applications of AI is for faster and more accurate diagnoses of various conditions. AI uses pattern recognition algorithms trained on immense datasets to assess scan images and other data. From here, AI can "decide" whether a particular diagnosis is appropriate or not. Of course, human physicians still have the final say, but AI tools can help medical professionals reach a confident diagnosis faster.

Breast cancer is a significant cause of death worldwide and the most commonly diagnosed type of cancer. Mortality rates are higher when cancer eludes early detection. Conversely, with early and precise diagnosis, the prognosis for most patients is good. Integrating AI with mammograms and MRIs used to scan for cancerous tissue can make screening more rapid and assessment more accurate. Current statistics suggest that AI tools help diagnosticians detect 13% more cases of breast cancer than human-only techniques. 

AI Healthcare Tools Promote Profitability

Modern electronic health record (EHR) and electronic practice management (EPM) systems are already using AI to streamline workflows. Automated collections processes help ensure continuous cash flow while forecasting tools assist in capacity planning and other aspects of practice operations. AI increases productivity and profitability by reducing the time required for manual data entry and manipulation. 

Health insurance companies are also utilizing AI for a variety of purposes. AI automates many processes that previously required manual data input, making claims processes more efficient and accurate. However, there are concerns that AI-powered claims denials and other decisions could be harming the most vulnerable. Healthcare practices must also consider that any third-party provider of AI solutions must be HIPAA-compliant and understand the intricacies of balancing patient care with revenue cycle management.

AI in Healthcare: Common Concerns

In addition to ensuring that AI tools offer compliance and data security, CTOs must be aware that there are ethical concerns surrounding the training and use of AI. Generative AI tools may utilize copyrighted material to fuel their natural language processing/generation (NLP/NLG) algorithms. Some AI algorithms contain worrying biases that could impact minorities. 

For example, back in 2019, data uncovered that a system designed to balance healthcare needs and costs was discriminating against black patients. This racial bias came from poor AI training that utilized previous healthcare spending from a limited pool of patients. By failing to consider the diversity of patients and patient needs, the AI became biased and discriminatory.

As AI advances, techniques are being implemented to prevent bias and to ensure proper regulation. Most modern healthcare providers should be able to advise how their AI algorithms are trained and quickly answer any concerns about ethics in AI.

TempDev Can Support You During the AI Revolution in Healthcare

CTOs looking to implement AI into their workflows and processes don't have to struggle alone. TempDev deeply understands NextGen EHR and EPM tools, and we are ready to support your practice with revenue cycle management, project management, and workflow redesign. NextGen is embracing AI as the next step in healthcare innovation and promotes a thoughtful, responsible approach to its implementation.

To learn more about advancements in NextGen Healthcare software and how we can help you optimize its effectiveness, contact us here or call us at 888.TEMP.DEV.