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She highlights the rapid expansion across ambient documentation, inbox management, revenue cycle optimisation, prior authorisation and predictive staffing, alongside a parallel rise of enterprise data platforms, where“ the EHR remains the system of record, but the data platform becomes the system of intelligence.”
Tim is focused on AI implementation quality – not merely AI volume.“ The next EHR battle won’ t be about who adds the most AI. It will be about who can actually redesign the workflow around it,” he explains.
He says the current momentum around ambient documentation is on proof of concept, as it addresses an obvious source of friction.“ Clinicians [ are ] spending valuable time documenting encounters instead of focusing on patients.”
Tim again points out that this technology adoption only works if organisations resist the temptation to bolt AI onto existing processes:“ Health systems should be careful not to turn AI into another feature layered onto fragmented processes. Automating a broken workflow doesn’ t transform it; it can institutionalise the problem.” Daniel believes that the next phase of EHR development will benefit frontline clinical staff, creating outcomes technology providers may not have initially envisaged.“ 2027 will be the year when that capability reaches the people who actually understand the work,” he says.
“ When a nurse manager or a revenue cycle director can build an agent for the specific bottleneck they live with every day, you get innovation no vendor roadmap would have prioritised: technology that finally helps deliver care instead of merely reporting on it.”
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