Artificial intelligence (AI) as a functioning tool is growing in popularity in the healthcare sector. In fact, it’s proving vital in bridging the service gap between patients and healthcare providers. The need for more efficient and effective AI-based healthcare solutions is causing the healthcare industry to see some of the biggest investments in recent times.
To help you understand the state of AI in healthcare in 2023, we’ve put together some major statistics and trends you should know.
Let’s get right into it.
1. The AI in healthcare market is projected to grow to $20.65 billion in 2023 (Source)
This is an upward trend that saw the market grow from $11.06 billion in 2021 to $15.1 billion toward the end of 2022.
Interestingly, the same report projects the total market value at a massive $187.95 billion by 2030. This follows a 37% annual growth rate from 2021 to 2022.
The main drivers for this growth have been the lack of efficiency in storing, processing, and managing huge and complex datasets, as well as providing quicker and more accurate diagnoses.
However, it would be fair to attribute some (if not most) of this growth to the overall digitization of industries, including healthcare.
Since the expansion of AI and machine learning (ML) into fields such as healthcare, legacy systems have been replaced at a surprising rate. These include but are not limited to healthcare data management systems, medical imaging processors, and diagnosis software.
It’s safe to say that the inclusion of AI in progressively more branches of healthcare will be among the top healthcare industry trends in the coming years.
2. The compound annual growth rate of AI in US healthcare is 36.1% (Source)
The US has among the most advanced healthcare infrastructure in the world.
Considering the advancements in US healthcare in recent years, it makes sense why the nation saw such a significant growth of AI in healthcare.
AI components such as deep learning software, natural language processing (NLP) tools, and predictive analytics are all contributing to the increased AI adoption. All of these components help diagnose and treat conditions earlier and more accurately.
In addition, tools such as ML algorithms were used to detect and diagnose instances of COVID-19 via PubMed’s Best Match algorithm.
One thing to note is that both the global market and the US’s share may grow past the projected compound annual growth rate. This is due to newer solutions being deployed at an accelerated rate, which leads to exponential innovation in a growing market.
Countries such as China and India are examples of such developing markets that are making massive headway in terms of AI development. A lot of that development falls in the service and administration sector, which includes healthcare.
3. The US has a 58% revenue share in the global AI in healthcare market (Source)
Building on the previous statistic, the US commands the majority of revenue generated from AI within the healthcare sector.
There are several reasons for that, including:
- Highly favorable government healthcare initiatives
- Lucrative funding options from both federal and private sources
- An increasing number of key market players
- A healthy environment for software and tech innovation
In addition to the above, there’s a rising level of awareness toward the implementation of AI in healthcare processes and treatments.
On the patient front, there’s an increasing prevalence of chronic conditions, changing lifestyles, and generally lax attitudes toward self-contained healthcare.
Luckily, AI solutions have the capacity to address the issues, given that they are administered and monitored to the extent that it meets the push to implement them.
Outside the US, the Asia-Pacific region has seen the second-largest share at 40.9%. The primary drivers are mostly the same as in the US.
4. Experts predict the global AI in healthcare market value will reach $272.91 billion by 2030 (Source)
This projection comes with an even higher compound annual growth rate of 51.87% over the course of eight years.
The reasons for this are twofold:
- The tech and software market has too many variables to safely pin down in terms of number and statistics.
- There can be exponential growth in sectors that show a positive change from the inclusion of new tech and methodologies.
This is why it’s next to impossible to pin down exactly how much the total AI market within the healthcare sector will grow.
There’s also the fact that AI itself can make major breakthroughs after implementation.
For example, the Best Match algorithm correctly identified 68% of COVID-19 cases in patients who were previously diagnosed as COVID-negative by healthcare professionals.
This alone would warrant a significant increase in investment, improvement, innovation, and implementation of similar systems in more healthcare facilities specializing in COVID care.
This way, healthcare providers can improve patient care, reduce care costs, and bring machine downtime to a bare minimum. Not to mention, providers can better secure patient data and implement more powerful cybersecurity measures overall.
5. 60% of US adults ‘uncomfortable’ with healthcare providers relying on AI (Source)
According to a Pew research survey, around six in 10 US adults are uncomfortable with healthcare providers using AI in their own healthcare procedures.
In contrast, only 39% of respondents are comfortable being treated via some AI usage.
Some of the things people were uncomfortable with include diagnosing conditions and recommending treatments.
The source of this discomfort can be traced back to disbelief among the general population about the beneficial capabilities of AI in medicine.
The survey, which included 11,004 individuals, also found that just 38% believe AI could improve healthcare outcomes. On the other hand, 33% believe it would only make things worse. Interestingly, 27% believed it would make no noticeable difference.
These findings foreshadow the general public’s attitudes toward AI in vital sectors such as healthcare. However, one positive aspect is that 40% of surveyed individuals believe that AI would reduce rather than increase the number of errors made by healthcare providers.
The biggest positive from this survey is that 51% of individuals believe that racial and ethnic bias in healthcare would reduce after the implementation of AI. In contrast, a major concern for 57% versus 13% of individuals is that using AI would impact the human connection between provider and patient.
6. Of US adults, 75% believe the healthcare industry will implement AI too quickly (Source)
Various surveys surrounding the public’s attitude toward AI in healthcare have found a mix of positives and negatives.
However, caution regarding implementation is one of the most common themes among all these surveys.
According to the Pew research survey, three out of four US adults are worried healthcare providers and medical institutions will move too fast in bringing this technology on board, without fully comprehending the risks associated with it.
Only 23% of respondents believe that AI implementation is moving too slowly and providers are missing out on opportunities to improve healthcare quality.
This survey also looked at participants who had heard “a lot” about AI versus those who had heard “little” or “nothing.” Of those who had heard a lot, 70% believed that AI was moving too fast, whereas 75% who had heard nothing about it believed the same.
The survey results show an interesting trend, in that U.S. adults who know more about AI are less likely to fear the healthcare industry will move too quickly with its adoption. And those who know less about AI are more likely to fear it will be implemented too quickly. This points to the possibility that fear of the unknown is contributing to the worry of survey respondents.
The findings also bring up an interesting theme surrounding the overall AI conversation, which is caution and distrust of non-human intervention.
Healthcare has always been a very person-to-person field. Introducing AI not only reduces that connection, but it also has the potential to eliminate it altogether.
While this is a cause for concern for some, if it helps deliver better quality of healthcare, it’ll be a step in the right direction.
7. 51% of US adults who say ethnic biases in healthcare are a problem believe AI will reduce bias (Source)
Additionally, 33% of respondents believe biases would stay about the same with AI implementation, and 15% believe it would get worse.
When asked why they believed AI would reduce the instances and prevalence of bias in healthcare, survey participants mentioned the dispassionate and more objective nature of AI versus human healthcare providers.
Expanding on this, 36% of participants believed that AI would improve the overall ethnic biases in healthcare due to AI being more neutral than humans and more consistent in how it saw patients.
Another 28% say that this is because AI does not discriminate based on a patient’s individual characteristics such as their race and appearance, both qualities where they believe doctors may hold biases.
Of the 33% of respondents who say biases would remain the same, 28% believe that since AI is designed and trained by humans, it could carry over the biases of its designers.
In this same group, 8% said there would be no change in racial bias because despite AI being implemented, a human healthcare provider would still be administering direct treatment.
Among the 15% who believe AI will make racial and ethnic bias more prevalent or worse, 28% cite the fact that humans will ultimately train AI, and that the datasets used to train them may contain human bias.
8. 75.7% of radiologists considered AI-based algorithmic results reliable (Source)
A survey by the European Society of Radiology looked at 185 radiologists who used AI-based algorithms to diagnose patients.
Out of those, a 75.7% majority agreed on the general reliability of such algorithms. The same survey found 16.8% of respondents consider AI unreliable, and 7.5% prefer not to answer due to either insufficient or inconclusive knowledge.
The background of this research is a wide range of AI use in healthcare applications in Europe. The surveyed radiologists included those who had used AI for diagnostic purposes for a set period of time and had analyzed results against those of non-AI applications.
Use cases also included help with interpretive tasks, workflow management, and medical image post-processing.
It’s important to note that most respondents considered AI to be generally beneficial and found no problems integrating AI in their daily practice.
9. 65% of US adults want AI to be used in their cancer screening (Source)
This survey looked specifically at using AI for skin cancer screening and treatment.
The overall results were positive, with two-thirds of respondents saying they definitely or probably want AI to be included in the screening process. However, 33% were against the implementation of AI entirely.
The survey also found that 55% of respondents believe AI would improve accuracy of diagnosis, while 30% believe it would not make much of a difference.
This may be due to what we mentioned earlier about patients believing that direct treatment would probably be administered by a human.
10. 67% of adults don’t want AI deciding how much pain medication they receive (Source)
AI is currently being used by physicians to determine how much pain medication an individual should receive. This is to reduce the chances of a person becoming addicted to pain medication, with machine learning algorithms used to determine who is more at risk.
This has been an issue in the healthcare industry, to the point where it prompted a question in a survey.
Unfortunately, patients express concern over letting AI decide their pain medication amounts, with the broad majority saying they don’t want AI making the decision instead of a human.
Moreover, 32% of respondents believe AI making these decisions would make pain treatment worse, while 40% believe it wouldn’t make much difference, and only 26% believe AI would improve pain treatment.
However, 31% of respondents say they definitely or probably want AI to be included in the decision.
Here’s what we can gather from the expansion of AI into more healthcare sub-sectors:
- There will always be a rich market for next-gen work management solutions in healthcare, such as a robust healthcare customer relationship management (CRM) system.
- Data management and automation will continue to be a major driver of AI adoption.
- AI may replace several key human roles in healthcare management.
Considering this, it pays to have a powerful process management system in place at your organization.
If yours is a healthcare organization looking for an all-in-one healthcare CRM and work management platform that allows you to customize and streamline your entire workflow, look no further!
Try FreeAgent CRM today and find out how you can benefit from an effective and stress-free workflow management system today.