Incorporating AI in Healthcare: Challenges to Overcome

Over the last few years, healthcare has advanced dramatically, increasing life expectancy worldwide. However, aging populations have increased the burden on healthcare systems. Managing these patients is costly, requiring healthcare systems to focus on long-term care management rather than episodic care management.

Statista predicts that the global market for Artificial Intelligence (AI) in healthcare will reach $188 billion by 2030. Although AI is being utilized successfully in disease detection and diagnosis areas, challenges are still blocking its widespread adoption in healthcare.

How is AI Being Applied in Healthcare? What Is AI's Potential?

AI in healthcare is projected to significantly impact how we analyze healthcare data, diagnose diseases, create therapies, and ultimately prevent them entirely. Medical personnel can make better-educated judgments based on more accurate information by utilizing artificial intelligence in healthcare, saving time, lowering expenses, and enhancing overall medical records management.

Increasing Effectiveness of Diagnostic Processes: AI can be used to evaluate imaging data, such as X-rays and MRIs, to assist clinicians in identifying disorders and planning therapy. For example, AI-powered systems can detect cancer indications in mammograms with high accuracy, allowing doctors to make a diagnosis and plan treatment more swiftly.

Reducing Overall Healthcare Costs: According to the National Academy of Medicine research, the United States spends roughly twice as much as is necessary on billing and insurance-related (BIR) costs, which results in around $248 billion in excess spending each year.

Many avoidable expenditures are related to fraud, waste, no- or low-value-added activity, and a lack of coordination among stakeholders. In addition to lowering costs, AI systems can accelerate healthcare administrative processes such as medical note transcription by removing manual data entry, correcting human mistakes, and automating the processing of electronic health records (EHR).

Safer Surgeries: Machine learning algorithms train robots to understand the surgical procedure and offer relevant information to the physician. Surgeons can access a high visualization level before surgery by integrating learning methodologies with computer-aided tools. Patients gain from AI's ability to do less invasive surgical operations that usually need open surgery, such as reduced blood loss, lower infection risk, and less pain following surgery.

Furthermore, because AI allows for greater precision when operating on sensitive organs and tissues, patients require fewer incisions, less scarring, and faster recovery times.

Easy Information Sharing: Doctors and other medical professionals can use AI to accelerate and optimize important clinical decision-making by leveraging real-time and precise data. More quick and realistic results can lead to better preventative measures, cost savings, and patient wait times. Real-time analytics can aid in the improvement of physician-patient relationships too.

Despite the ease that AI brings to the healthcare industry, there are some issues you need to be aware of.

Top Most Common Challenges of AI in Healthcare

We know that AI is revolutionizing the healthcare industry. However, by addressing the roadblocks ahead, we can clear the path for better implementation of AI.

Privacy Concerns: Concerns about privacy and cybersecurity are linked to confidentiality and trust. Sometimes, anonymizing the data enough to allow the AI machine to work may be possible. However, other areas, such as image-dependent diagnosis, such as ultrasounds, may be more problematic.

Secondly, as AI's capabilities expand, so will cyberattacks. Computers can hunt for patterns in data using techniques such as advanced machine learning, deep learning, and neural networks and detect and exploit weaknesses.

Advanced machine learning algorithms combined with cloud technology are already analyzing massive amounts of data and identifying real-time dangers. AI may create cybersecurity intelligence reports and locate hotspots where cyberattacks have originated.

Regulation & Data Ownership: There are currently no defined regulations or guidelines governing the use of AI in healthcare. This can make it challenging for healthcare organizations to know how to utilize AI ethically and for patients to know what to expect when interacting with an AI system.

Notably, some AI systems are exempt from regulations. The government also lacks specific rules for openness and explainability - significant hurdles in deploying AI in healthcare.

Lack of Transparency: Many AI systems are called "black boxes" since it is impossible to understand how they reached a certain judgment. Because of this lack of transparency, doctors and other healthcare professionals may find it difficult to trust the outcomes of an AI system.

As a result, one of the most significant problems in building and evaluating prospective AI models for healthcare is the scarcity of high-quality data for machine learning tools. When AI is built with data from unknown sources or underrepresented persons, it can distort the process and modify the findings.

Finally, the healthcare business may realize AI's full potential by promoting consistent data procedures. This will ensure that patients receive accurate, unbiased, and patient-centered care.

What Does the Future of AI in Healthcare Hold?

Despite technological, ethical, and privacy issues, AI in healthcare is now commonplace. It holds significant potential for advancing healthcare through diagnostics, early symptom prediction, and drug discovery.

Furthermore, contemporary AI and machine learning (ML)-based solutions (AI voice assistants) are already assisting healthcare businesses in optimizing their processes. As a result, the future of AI in healthcare is bright. As a result, individuals who want to start a successful career in this industry should stay current on the latest developments.

Mike Szczesny is the owner and vice president of  EDCO Awards & Specialties, a dedicated supplier of employee recognition products, branded merchandise, and work anniversary awards. Szczesny takes pride in EDCO's ability to help companies go the extra mile in expressing gratitude and appreciation to their employees. He resides in Fort Lauderdale, Florida.