With predictive analytics, clinician buy-in is more important than the algorithm

Doctors talking
If clinicians aren't on board, predictive analytics will fail, according to health IT researchers.

Predictive analytics can help solve some of healthcare’s most vexing problems, but only if clinicians are willing to use it.

Demonstrating the value of predictive modeling for front-line clinicians and providing C-suite executives with measurable benefits are key to integrating analytics into a healthcare system, three researchers wrote in Harvard Business Review.

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Based on interviews with 34 health system leaders, policy experts and vendors, analytics experts from Brigham and Women’s Hospital and Partners HealthCare highlighted the importance of implementation for both in-house and off-the-shelf solutions. Usually, it helps to have a clinical champion that can reach out to colleagues to demonstrate the value of the tool and promote valuable health IT solutions.

“A common reason these tools are underutilized is that frontline employees don’t fully understand their value,” the authors wrote. “Thus, successful programs start with a problem where predictive analytics can make a clear difference.”

Their assessment aligned with several healthcare organizations that have found success using predictive analytics by ensuring new solutions are meaningful for physicians. But there is a clear disconnect among many healthcare organizations. A recent survey showed just over 30% of hospitals are using predictive analytics currently, but 80% of executives believe it can improve patient care.

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A report released this week by the Stanford School of Medicine advocated for better data literacy among physicians since analytics is likely to become a core job function in the future. Stanford is one of several academic medical centers teaming up with Google to enhance healthcare analytics and predict hospitalizations or cardiac arrest.

Presenting hospital executives with quantifiable measures—in the form of quality improvement, lower costs or patient satisfaction—will help secure the funding necessary to maintain or enhance predictive analytics systems, according to the Boston researchers.

Hospitals have faced similar implementation struggles with artificial intelligence, which offers tremendous promise for the healthcare industry even as clinicians and executives are still wrapping their arms around the technology.