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Students learn lessons from a teacher.
Great excitement. Grandiose predictions. Huge expectations. While these words describe today’s AI zeitgeist in healthcare, they also describe how many thought about electronic health records in the 2000s and 2010s.
Since then, nearly all U.S. health care systems and medical practices have implemented EHRs, improving health care in some ways and worsening it in others. The outcomes were varied; Organizations that have invested in their workforce and systems have generally done better.
AI is the next phase of healthcare’s decades-long digital transformation. While rollouts will vary, organizations approaching AI would be best served by applying lessons learned from implementing and using EHRs.
Lesson 1: Set realistic expectations
Next decades of hope and hype surrounding the digitalization of healthcare, many expected EHRs to make healthcare safer, cheaper and more effective. Things turned out differently.
EPDs are one mixed bag. First, they provide doctors with information, but overwhelm them with clutter and nonsense. Clinical notes, for example, are now readable and easy to find, but often cluttered with unnecessary, duplicated and sometimes incomprehensible content.
Likewise, EHRs bring doctors and patients closer together while driving them further apart. While portals make it easy for them to communicate between visits, distracting exam room screens and keyboards disrupt human connection.
EHRs make physicians more productive in some ways, but less productive in others. For example, while it is easy to prescribe medications and transmit test results electronically, doctors must process countless alerts and notifications.
Lesson 2: Put people first
Many have criticized EHRs for meeting billing needs more than improving clinical care. As such, nurses and doctors often find it difficult to use EHRs, which contributes to the problems they cause burnout. Yet that’s what organizations are given priority their staff – for example by communicating clearly, investing in implementation and personalizing training better done.
With AI, organizations must begin winning back the hearts and minds of patients and healthcare professionals who no longer believe in the promise that more technology will necessarily improve healthcare. This requires using AI to improve outcomes and experiences (not just billing and efficiency), making AI tools easy to use and supporting change.
Lesson 3: Improve healthcare systems
Healthcare IT does not work in isolation. It becomes part of one socio-technical system involving different teams and workflows.
When implementing EHRs, many organizations have digitized existing paper workflows and kept their teams unchanged rather than updating them for a digital world. This resulted in many inappropriate and wasteful workflows, often forcing healthcare workers to find solutions and perform tasks that others previously did for them. Organizations that have redesigned their workflows and… reconstituted teams for a digital world have done better.
Organizations must avoid making the same mistakes with AI. Bill Gates explained: “The first rule of any technology used in a business is that automation applied to efficient operations will increase efficiency. The second is that automation applied to an inefficient operation will increase inefficiency.”
So instead of rushing to automate broken processes or using AI as a band-aid for poorly designed technology, organizations should first optimize their EHRs, streamline work and eliminate wasteful tasks. Initiatives like getting rid of stupid things (GOOR) program can help.
Lesson 4: Keep investing in the change
Many organizations viewed EHR implementation as a one-time event and did not realize that it was impossible to fully anticipate what the “live” EHR would look like before putting it into production and training their workforce all at once.
As a result, many EHR tasks are burdensome (as must physicians in one healthcare system). click 61 times to place a Tylenol order), and many doctors don’t use powerful EHR features (for example, Epic reports that only one in three doctors use the search function). Conversely, organizations are those given priority continued training and EHR improvements have significantly improved performance.
The point is that with AI, implementation should never end. Organizations must continuously monitor AI, evaluate its effects, support frontline staff, and ensure that AI-based tasks stay in step with the work at hand.
The stakes are too high to fail
Healthcare organizations could use AI to make healthcare more accessible, effective and efficient. Yet success is not guaranteed. Those who leverage the lessons learned from EHR implementation – setting realistic expectations, putting people first, improving systems of care, and continuing to invest in the change – are most likely to succeed.