In recent years, healthcare organizations have tackled the massive lift of digitizing health data. Yet, the shift to EHRs has inadvertently created new usability problems and interoperability continues to be an enormous challenge.
During a workshop at Becker's Hospital Review's 12th Annual Meeting sponsored by Cerner, David Feinberg, MD, Cerner's president and CEO, discussed how the future and promise of the EHR can lead to more equitable, cost-effective, easy, convenient and dignified healthcare.
- 1. Cerner has a comprehensive vision for improving EHRs. Dr. Feinberg sees solutions falling into three timeframes:
- Today, some organizations are using Cerner in an unoptimized way. "We can show you which doctors are spending an inordinate amount of time in the EHR compared to others and then do elbow support or change workflows. That can happen right away," Dr. Feinberg said.
- In the mid-term, Cerner is committed to speeding up the modernization of the EHR platform.
- Longer term, Dr. Feinberg expects to make a complete cultural shift within Cerner. Instead of being technologically driven, the company must become clinically driven. "This year, we hired Cerner's first chief health officer," he said. "We have more than 1,000 doctors and nurses at Cerner. Their job now is to be more clinical and to meet with customers to identify problems we need to take action on and fix."
- 2. In five years, interoperability will no longer be a challenge, according to Dr. Feinberg. "We are already seeing progress in the United States and in other countries," he said. "Cerner plans to launch a product called Seamless Exchange later this year to facilitate interoperability."
- 3. However, interoperability doesn't always mean that data is actionable. Data becomes an amazing time saver when it is usable and discoverable. "When we define interoperability in this way, it sends a message to patients that they matter and a message to clinicians that we aren't going to turn them into digital archaeologists," Dr. Feinberg said.
- 4. Nearly every large data set has inherent biases that must be flagged for users. Experience has shown that big data sets can improve human performance. But if AI and machine learning models are trained on data that isn't equitable, the resulting care recommendations also won't be equitable. "It's a real contradiction — the results [of AI and ML] are better than humans, but it's not suitable for everyone," Dr. Feinberg said. "We have to adopt to this technology capability, but there needs a very clear label on when not to use it. It's similar to a nutrition label we find on food products: warn me in bold letters about problems that will arise if I apply this to a certain population."
- 5. The United States must move to a system that rewards healthcare organizations for value, not volume. In volume-based systems, providers don't make money on poor patients who need mental health services and have multiple chronic morbidities. "If you are paid to care for these individuals and to keep them healthy, suddenly they are your most important patients," Dr. Feinberg noted.
Using data to address social determinants of health and health equity also needs to be front and center. "If we don't address these issues, we will continue to perpetuate terrible racism in healthcare," Dr. Feinberg said.
Looking ahead to the next decade, Dr. Feinberg said, "If we haven't fixed access to mental healthcare, closed the gaps so fewer Black women die in childbirth and given diabetics access to healthy food and a safe place to exercise, then I don't think anything else we're doing matters. I can come up with the most amazing technologies, but fundamentally, healthcare is about loving your neighbors."
This story originally appeared on Becker’s Hospital Review.