CereCore organized a cohort of healthcare CIOs representing different healthcare organizations to delve into the realm of AI, analytics and automation. As they explored the endless possibilities, they acknowledged the tangible risks and valid concerns. The event, led by Peyman Zand, chief strategy officer, and Josh Dunaway, senior director of advanced data solutions, featured the CIOs sharing their expertise on existing and potential use cases, the level of acceptance among healthcare leaders, and crucial factors for health leaders to bear in mind amid rapid advancements.
A report by MarketsandMarkets estimates that the global market for healthcare AI is expected to reach $102.7 billion by 2028. Recent and ongoing advancements could significantly impact strategies to improve operational efficiencies, alleviate burnout, and boost patient satisfaction.
Along with the excitement around AI capabilities, many health leaders are justifiably hesitant about the safety and accuracy of AI tools such as ChatGPT. As AI continues to advance, information technology leaders must think strategically about some considerations pointed out by CereCore’s CIO Cohort members including:
Low-risk ways that AI solutions can be integrated seamlessly into a physician’s workflow.
This strategy has the potential to alleviate physician strain and reduce burnout. “It's all about taking a cautious, reasonable approach [to AI] —not blocking it, but making sure we don't move too fast,” said Alan Ariel, Interim CIO for Delta Dental of Missouri.
Some possible lower-risk healthcare use cases for AI solutions include:
Predictive analysis based on readings collected by devices and alerts issued to care teams.
According to Dunaway, one lifesaving use case for AI solutions is sepsis prediction. “Organizations like HCA Healthcare have gained a better understanding of sepsis risk with the ability to continuously monitor patient vitals and other patient information and quickly alert their health team during the patient’s continuum of care,” said Dunaway.
Cybersecurity and privacy measures for complexities introduced by AI.
Cybersecurity and privacy concerns are always top of mind. Two concerns voiced by the cohort were:
Predictive analytics technology is currently used in various aspects of healthcare to improve patient outcomes. “The technology supports the ability to better assess the overall health and risk of the patient during a visit,” said Dunaway. “Documentation of patient encounters provides physicians with a contemporary chart, which improves clinical outcomes and supports coding and reimbursements.”
Internally, health systems use these tools for readmission risk determination and for service desk optimization. Use cases can drive better business outcomes by improving patient satisfaction and preventing the need for readmission. Analytics technology is also being leveraged to expedite insurance claim submission.
“Transitioning to new platforms of any kind requires a significant amount of build. Often whenever these conversions are occurring within a health system, clinicians have to take time out of their day to do manual data entry which adds additional strain on the clinical staff. Automation can eliminate roughly 40% of the data entry, which helps mitigate burnout and drive efficiency,” said Dunaway. This allows them to focus more of their time and energy on higher priority tasks. However, some CIOs are hesitant to leverage automation for quick fixes. “Simplification should be the predecessor to automating tasks that are not being well managed,“ said Pollack.
In Summary: Navigate AI, Analytics and Automation Carefully
Before implementing these tools, consider the following points to protect your organization and the patient:
AI, analytics and automation offer unprecedented potential to solve current and future problems in healthcare. Responsible implementation is required to ensure positive outcomes for your organization and the patients you serve.