Of all the industries where AI has the potential to improve service levels, healthcare is one of the greatest. The complexity of patient needs and the broad range of treatment protocols that must be managed result in significant costs in human capital and wastage at every turn. AI has the potential to streamline operations and make key challenges simple, yet the sector’s adoption of AI remains behind others.
Despite healthcare requiring some of our most intelligent professionals – surgeons, lab technicians, and medical equipment operators among others – only 1 in 1,250 job postings in healthcare require AI skills. This is lower than other skilled industries such as insurance, education, and science.
Why is this the case? Is it that the foundations to implement AI tools aren’t present in healthcare, or is it that hiring managers aren’t aware of the skills they need to recruit? Perhaps it’s because the customer-driven demand for AI technologies that exists in other industries hasn’t yet caught on in healthcare. According to Pew Research released last month, sixty percent of US adults are “uncomfortable” with healthcare providers relying on AI.
But this doesn’t mean providers should ignore the opportunities in AI altogether. They must lead the way and show patients that AI can be trusted, allowing them to reap the benefits of reduced costs and complexity while delivering higher standards of care.
By tackling the four barriers outlined below, healthcare providers can create a roadmap for AI adoption that will increase quality and create better outcomes.
1. The belief healthcare providers will move “too quickly”
Seventy-five percent of Americans are concerned that healthcare providers will move “too quickly” when introducing AI, implementing technology before fully understanding the risks. Only 23% believe that providers will move “too slowly” and therefor miss opportunities.
We sympathise with this concern. Providers can’t suddenly jump from having never used AI all the way to utilizing it to diagnose patients free from human input. AI’s implementation in healthcare must move more slowly and start with solving challenges in ways that are less invasive to the patient-provider relationship.
Healthcare organizations should consider first using AI in their patient communications. If they can demonstrate accuracy when automatically sending patients reminders about their care or coordinating appointments, then patients will eventually come to trust the technology to assist in other areas.
2. Lack of quality data
Research by The Brookings Institution cites challenges with the quality of the data available within healthcare companies. It describes how data is “often difficult to collect and difficult to access” and that “medical professionals often resent the data collection process when it interrupts their workflow”.
Humans, especially intelligent and high-performing ones such as medical professionals, should not be burdened with mind-numbing manual data collection and entry tasks. These things are far better left to the machines. When healthcare professionals experience the benefits of having AI collect more accurate data, patients will reap the rewards of gaining access to a higher quality of care.
3. Awareness of positive patient outcomes
Americans are split on whether they believe AI would improve patient outcomes. Thirty-eight percent say it would make it “better”, 33% say “worse” and 27% say it would “not make much difference”.
There are huge successes to be had in deploying AI to provide better post-op care. Using AI communication, patients can report if they are not progressing as they should after a procedure. This will ensure they receive corrective treatment more quickly and greatly reduce readmission rates.
Anyone whose life is saved or receives a more attentive standard of care, in part, due to AI communications will be unlikely to think the technology results in “worse” patient outcomes.
4. Lack of staff incentive
There is a belief among healthcare providers that acceleration of tech innovation in AI puts their job at risk. Why should a healthcare decision maker explore technologies that they believe threaten their career? Forty-four percent of healthcare workers fear artificial intelligence could eliminate their job.
This is not the case, and we’ll explore why healthcare professionals shouldn’t fear AI with more detail in a later article. For now, we can say that it’s far more likely that AI will serve to complete the healthcare jobs that aren’t happening rather than take over the ones that are. AI can have the conversations with patients that healthcare staff would love to have, if only they had the time.
Using AI as a conversational tool, providers can send millions of interactive prescription reminders to patients that cannot be managed by humans. AI can check in on the thousands of patients who are post-op but need a level of support that healthcare workers simply do not have the resources to give. AI will empower and augment the healthcare workforce, not replace it.
Building on the positives
Despite the barriers, there are positives to take from the Pew Research findings. Americans are slightly more optimistic on the potential of AI to reduce medical errors. They are also more likely to place their confidence in AI to be able to treat people of all races and ethnicities fairly. There is more faith in AI as a customer service tool than there is as a digital medical practitioner.
AI’s strengths are in providing consistent communication, accurate data records, and delivering tasks on-time and within compliance standards. These strengths are critical in delivering high levels of customer service and better standards of patient care.
By taking the smaller step of introducing AI in the customer experience, healthcare operations will pave the way for increased trust in more revolutionary applications that can be deployed in the future.