Artificial Intelligence (AI) has been taking over different industries for the past years by providing efficient solutions, automating routine tasks, and streamlining processes.
The use of AI technologies in the healthcare industry has been gaining popularity. In the years to come, the use of AI technologies in health is expected to be of exponential growth.
Currently, AI has been used in automating tasks such as medical data recording, the conduct of necessary tests and providing algorithms to check patients’ safety.
More and more health organizations are using AI to advance their services. However, here are three things to consider when it comes to how and when your organization will adopt AI Solutions:
1. Entry Level AI is Affordable
It would be good to discuss first that there are different types of AI applications in the healthcare industry.
Type 1 AI Application refers to task automation. Type 2 AI Application refers to Pattern Recognition, and Type 3 AI Application refers to Contextual Reasoning.
For the entry-level, we refer to Type 1 AI applications. These refer to repetitive and time-consuming tasks that can be better off being automated. These administrative processes include writing chart notes, prescribing automation, ordering tests, etc. The cost is not high for this type of AI application, and it can yield a significant Return of Investment in a short period. However, Type 2 and Type 3 Applications can be more costly since it involves more complex tasks.
2. The Success Rate is Different Across Different Types of AI Solutions
As mentioned, Type 2 and 3 AI Solutions are more complicated. The reasons behind this are it involves complex processes which can result in various success rates across all types.
The AI Industry heavily relies on information. While there has been a significant increase in electronic data, this is not a guarantee that everything is accurate. If data is lacking and inaccurate, it can negatively impact the outcomes of the analysis and the safety of the patients.
Therefore, there is a need for programmers to “train” AI solutions for it to yield a reliable and valid analysis.
3. Think about AI Long Term
AI is the future, and many health organizations can see that. That’s why it would be helpful for decision-makers to consider a long-term view when it comes to using AI solutions.
AI is still a developing technology. It becomes more intelligent over time. Thus, if an organization decides to use AI, they must also consider significant and sustained leadership to monitor and further enhance this investment.
Organizations who have seen the use of AI for long term purposes have a focus on these three aspects for critical changes. These elements include:
(1) Enterprise-view on solutions
(2) Modernizing Systems
(3) Focusing and Integrating Expertise.
Decision-makers must consider these three things before deciding to venture on AI. Being the thing in the future, AI has the potential to be the solution of the long woes in the medical industries. The efficiency it gives in different medical processes and procedures provides a possibility of solving the deeply rooted problems of the industry.
Policy development has been moving at a slow pace when it comes to the adoption of AI. Thus, it is in the hands of decision-makers to come up with sound judgment in determining whether the institution and its clients are ready for this change.
More so, it should look at itself internally whether it is ready to take on this advancement as an organization. The use of AI can threaten employees. Therefore, it is essential to assess whether your organization is maturely ready for this big leap.