The Biggest Issues with Healthcare AI: Navigating the Challenges Ahead
Artificial Intelligence plays a massive role in healthcare and therefore holds the potential to make medical processes more efficient, along with improving patient care. However, there are significant challenges to consider.
One of the major challenges of AI is the quality of data being used. For efficient results, AI needs high-quality and accurate data – which most users fail to provide. Most of the datasets are incomplete or biased, which can lead to discrepancies in using AI systems in real-life situations.
As AI models are deployed, a phenomenon, called the ‘Performance Drift’ can arise. This refers to situations where AI is used in conditions different from what it was trained on, leading to a change in performance. To avoid this, continuous monitoring is required to ensure that these systems are working efficiently. However, most of the organizations don’t have the right processes set in place to do so.
Challenges faced by AI are not just limited to data and its performance, the user must also consider regulatory and compliance issues. Rules for the usage of AI in healthcare are still under process, which makes it a challenge for healthcare providers to adhere to existing laws while also incorporating new AI-specific regulations. The use of clear and concise guidelines is essential while innovative technologies are developed, to ensure that patient care remains a top priority and is not compromised.
Furthermore, a lot of healthcare facilities rely on older technologies – which may not be entirely compatible with the new AI tools. To successfully integrate the two, there lies a requirement for efficiently training the healthcare staff to enable them to adapt to the upcoming systems. But the rise of AI also brings concerns for the healthcare workforce, since it can change job roles or necessitate new skill sets. To combat this, it is important to prepare healthcare workers for any unforeseen changes, so that they can work efficiently alongside these arising technologies.
The most crucial challenge faced by AI is protecting patient privacy while utilizing their data. This challenge is interlinked with another ethical challenge, where many have various concerns such as, “What happens if an AI system makes a mistake in diagnosing a patient?” – thus, it is important to create an optimum level of trust between patients and healthcare providers. Furthermore, healthcare organizations must develop and implement strong measures to protect patient data and protect their sensitive information from breaches and misuse.
There is no doubt about the greatness of the power of AI – but it comes with its set of challenges, especially in healthcare. Therefore, it is important to thoroughly understand these challenges and combat them accordingly. Increasing focus on solutions to data quality, ethical practices, efficient training and regulatory compliance – the healthcare industry can make the best use out of AI for their patients, given that they work by making patient care their top priority.
