Cloud EHRs Are Coming Fast, But Who’s Rebuilding the Clinical Workflow?

U.S. health systems are charging into the cloud with extraordinary speed. According to a recent Deloitte survey, 90 percent of provider organizations now prioritize electronic health record modernization. Intermountain Health and UPMC are transitioning to Epic on AWS and Azure by the end of 2025, while Broward Health has committed $250 million to move from Cerner to Epic. The stated motivations which are interoperability mandates from the Office of the National Coordinator for Health Information Technology (ONC) and adoption of SaaS-based AI modules like Epic’s sepsis prediction reveal a trend that is more technical than clinical source.

The problem is not the technology itself. Cloud-hosted EHRs offer significant infrastructure improvements. They provide more agile update cycles, enhanced cybersecurity responsiveness, and scalability that supports complex AI modules and longitudinal health data sharing. What they have not yet delivered is relief for the exhausted physicians, nurses, and medical assistants logging hours inside interfaces that seem purpose-built to slow them down.

Infrastructure Advances Do Not Equal Workflow Fixes

Most of what gets labeled as “modernization” today centers on backend gains. Hosting Epic in the cloud, for instance, can reduce capital expenditures and allow for better disaster recovery configurations. But clinicians do not experience backend architecture. They experience documentation clicks, disjointed patient summaries, inbox overload, and decision support that rarely matches the subtlety of human judgment.

The shift to cloud EHRs is happening against the backdrop of record-setting clinician burnout. In a 2023 study published in JAMA, over 50 percent of U.S. physicians reported symptoms of burnout, with “burdensome EHR tasks” ranking among the most cited causes source. Another study from the American Medical Association found that physicians spend nearly two hours on EHR and desk work for every one hour of direct patient care source.

Without addressing these root causes, simply moving the same EHR to a new cloud environment risks reinforcing dysfunction with faster bandwidth.

AI Tools Like Sepsis Alerts Are Not Clinically Neutral

AI modules such as Epic’s Sepsis Model are often cited as proof points for cloud-based EHR value. These algorithms use machine learning to flag early warning signs of sepsis, aiming to trigger earlier interventions and reduce mortality. But their performance in the field has raised serious concerns. A 2021 JAMA Internal Medicine study found that the widely deployed Epic Sepsis Model missed the majority of sepsis cases and frequently issued false positives, eroding trust among frontline staff source.

Clinicians report that sepsis alerts, when poorly calibrated or introduced without clinical buy-in, simply contribute to alarm fatigue. More alerts mean more time validating or dismissing machine-driven suggestions. In many environments, these tools become just another layer of complexity added to workflows already cluttered by redundant documentation and billing prompts.

EHR Transitions Are Trauma

Cerner-to-Epic transitions like the one at Broward Health often promise long-term operational gains. But in the short term, they inflict heavy cognitive, emotional, and productivity tolls on clinical staff. Research by the Mayo Clinic has shown that EHR transitions increase after-hours EHR use and decrease clinician satisfaction unless significant workflow optimization and change management resources are deployed in parallel source.

Clinicians frequently describe go-live periods as “chaotic” or “destabilizing.” New note templates, unfamiliar order sets, and restructured inboxes often arrive without adequate time for adaptation or co-design. Most systems lack formal decompression processes to eliminate legacy documentation burdens during the transition. As a result, the “new” EHR ends up carrying forward years of bloat, fragmentation, and user frustration.

A True Modernization Demands Frontline-Centered Design

If the goal is not just modernization but actual clinical improvement, then health systems must elevate the voices of those doing the work. Successful EHR cloud transitions require:

• Workflow redesign teams that include nurses, residents, social workers, and medical assistants—not just informatics specialists and system architects
• Investment in digital hygiene, meaning dedicated time and personnel to remove unnecessary clicks, outdated flowsheets, and low-value documentation requirements
• Inclusion of burnout and usability metrics as core success indicators, with ongoing tracking of time in notes, inbox volume, and EHR after-hours use
• Thoughtful governance for AI modules, including local calibration, clinical validation, and feedback loops for frontline users before full deployment

In short, if the migration to cloud EHRs does not improve the daily experience of delivering care, it is not modernization. It is replatforming.

Cloud-based EHRs absolutely can support more agile, intelligent, and coordinated care. But none of that will matter if physicians still spend their evenings documenting care they barely had time to give. The real opportunity lies not in the servers or the storage but in the redesign of workflows that serve both patients and the people caring for them. Until that becomes the priority, the cloud will remain just another place to house the same broken processes.