Many healthcare institutions are looking forward to implement AI into their organizations to improve their operations and quality of patient care. Many such organizations have already implemented AI tools. With many articles being written on how AI is stealing human jobs, actually AI is re humanizing healthcare by helping healthcare professionals focus more on interacting with patients rather than spending time on routine tasks.

A recent survey of more than 900 health-care professionals by MIT Technology Review Insights, finds that health-care professionals are already using AI to:

Improve data analysis Enable better diagnoses and treatment predictions Free medical staff from administrative burdens

Machines must work for doctors and clinicians, not the other way around; much patient consultation time is spent entering data, not drawing inference from it.

Table of Contents

The effect of AI is already here

Current advancements in AI has made machines into a powerful tool for clinical and operational efficiency. A decade back, very few people would have thought that machines could be a partner in medical procedures. Numerous technologies are in play today to allow health-care professionals to deliver the best care, increasingly customized to patients, and at lower costs. It is not a surprise that 72% of the survey respondents show interest in implementing AI.

Bijoy Khandheria, a cardiologist at Aurora Hospital’s Aurora International & Executive Health Program, in Milwaukee, Wisconsin, says that

“the basic interpretation [of an MRI], with the help of machine learning and AI, can be standardized and left to the machine. But there is still a need for human intervention.”

Reducing complexity and errors

AI-optimized schedule management not only makes a doctor’s day more efficient—it creates opportunity to use AI for more patient-facing applications, giving clinicians time back to work with their patients more closely, and with more insight.

Dushyant Sahani, professor and chair of radiology at the University of Washington Medical Center, says that

“with improvement in the physician’s workflow and health-care operations, diagnostic tools will be better applied. If the focus is only on the diagnostic tool, adoption will be much slower.”

Reducing clinical error

Medical professionals using AI applications are seeing immediate gains in reducing clinical error—something that’s still a major challenge for those who have not yet adopted such tools.

AI-enabled decision-support algorithms allow medical teams to make more accurate diagnoses. For Matthias Merkel, professor of anesthesiology and perioperative medicine at the School of Medicine at Oregon Health & Science University, it’s doing something big by doing something really small: noticing minute irregularities in patient information. That could be the difference between acting on a life-threatening issue—or missing it.

Challenges

Implementing AI in health-care operations, like any significant organizational transformation, presents multiple challenges.

Skepticism

Respondents reported multiple hurdles that they found significantly challenging. Among those was skepticism about the provable benefit and overall cost of AI as top factors hindering its adoption. Hospital administration is generally more skeptical than medical staff. Another hurdle is the disruptive impact that AI has on existing processes; a third is the difficulty of integrating AI applications into existing systems.

Data privacy

Medical staff with AI cite concerns about the challenges of data privacy half as often as those without AI. Health-care professionals who have not deployed AI are challenged not only by access to accurate data, but also by issues related to maintaining patient privacy and data integrity.

Breaking myths and concerns

The growth of AI and automated processes often creates concerns that the human touch will be removed from the health-care delivery process. What the industry is finding, however, is the opposite is becoming true: AI can extend the resources and capabilities of overworked health-care professionals and vastly improve processes. Faster access to better patient data is the most critical benefit AI-enabled health-care teams are seeing.

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Reference- https://www.technologyreview.com/hub/ai-effect/