Why EHR Changes Are Slow and Slight

Healthcare’s dropping the ball. That’s what Michael Cousins, PhD, chief analytics officer of the population health services company Lumeris, thinks about the industry’s handling of electronic health records (EHR) systems. But what’s barring hospitals from making the substantial changes that he says can save lives?

Cousins tells Healthcare Analytics News™ that 3 big obstacles stand in the way between healthcare organizations and overhauled EHR infrastructure capable of providing actionable data. Although each is different, their roots all flow to the past, not the future. And money isn’t necessarily the problem, he says.

If hospitals and providers find ways to overcome these challenges, they may access more information. That includes ever-important social determinants of health (SDH) data, which are key to developing precision care plans for the individual, Cousins notes. Mayo Clinic, University of Pittsburgh Medical Center, and Kaiser Permanente belong to a small league of blue-chip institutions that have taken major steps forward.

“The clarity of the opportunity may not be apparent to executives,” he says. But 1 thing should be clear: Hospitals can’t afford to continue doing what they did yesterday. EHR tweaks aren’t enough, he says.

The Lack of Aligned Incentives

Cousins recalls recently speaking with the leaders of an academic medical center. They showed no interest in reducing hospital readmissions. They did the math, he says, and determined that the fee-for-service model earned the institution more money than a pivot to value-based care. That financial incentive essentially bucks the group’s need to collect SDH data and revamp its EHR system.

Education Gaps

Gathering and using data is difficult. Healthcare companies don’t always employ people who understand which numbers to crunch to advance personalized medicine.

For instance, some EHR systems sift through United States Census data, convincing their hospital clients that the insights will prove valuable for the individual, Cousins says. That’s, of course, untrue. “If you’re trying to make a person-level intervention,” he adds, “you need person-level data.”

The takeaway? Health systems must hire the right data people and commit to learning best practices. But a talent gap might exist here, Cousins says, due to the recruiting power held by premier hospitals and healthcare groups.

Competing Priorities

To keep the day-to-day business going, health systems must manage a boatload of priorities. “Being proactive?” Cousins asks. “They’re just trying to make sure that the patient who showed up in the [emergency department] at 8:30 sees a doctor before noon.”

What’s more, he claims, many hospitals are hesitant to outsource work or build partnerships with similar entities. Those tendencies further restrict EHR systems from reaching their potential.

What Are the Risks?

The general lag in improving EHR management places patients in greater danger, Cousins says. Why? Because SDH data can help foster predictive analytics and increase the quality of care. Those are real-world results, and their absence carries real-world consequences, he says. Not to mention, an optimized EHR system and targeted treatments stand to promote value-based care.

Stagnation also threatens health systems. Cousins points to the wave of consolidation that’s rippling through the industry. Larger organizations are buying smaller ones, especially those in rural areas, where they’re grasping for fee-for-service revenues as insurers and CMS force the move to value-based care, he says. The trend has gone on for years, and analysts expect it to continue. Health systems that can’t adapt might not last, Cousins adds.