Navigating the Maze: Reflections from a Superuser
By Alexander Kaysin, Medical Director, MD, MPH, FAAFP, University of Maryland Capital Region Health
Introduction: From High Hopes to Hidden Frustrations
The early promise of Electronic Health Records (EHRs) held the potential for a digital revolution, offering legible clinical notes, smoother data sharing, reduced medical errors, and improved patient outcomes. Remember the now obsolete adage zero should always lead, never follow.” However, the exact flexibility that was once lauded has all too frequently resulted in confusion, delayed care, and decreased productivity for the physician as EHRs have developed to power documentation, revenue cycles, labs, telemedicine, and radiology processes.
Seventeen years ago, as a medical student, I was a witness and participant in the first wave of digitization in U.S. health systems. In that early stage, I encountered frequent system crashes, lost documentation, sluggish chart reviews, buried clinical data, and accidental computer shutdowns that halted patient care. By residency, my colleagues and I encountered the adoption of a more sophisticated enterprise EHR, but optimism gave way to frustration when mandatory trainings felt abstract and irrelevant, trainers unfamiliar with our roles, and workflows proved anything but intuitive. We adapted the way clinicians do by improvising and sharing tips informally.
Now, as a clinician leader and residency faculty, I’m regarded as a “super user” in the same EHR platform. I maintain preference lists, note templates, and provide elbow support to colleagues and trainees facing daily hurdles. Even so, I find myself constantly learning new efficiencies, often from peers or online communities, in what has become a never-ending process of decoding the EHR.
The EHR of tomorrow must evolve beyond a passive, retrospective record of patient encounters. It must transform into a dynamic, intelligent system one that integrates data from diverse sources, recognizes individual patient variations, and delivers predictive insights that actively support and enhance clinical care
The Double-Edged Sword: Flexibility That Fragments
EHRs aim to cater to numerous specialties by offering customizable interfaces from pediatrics to oncology, with menus for everything from cough assessments to detailed surgical histories. But that flexibility often comes at the cost of clarity.
Choice Paralysis: Too Many Paths, Too Little Direction
For a simple task like ordering a stat CT scan for a suspected stroke, a clinician might face a dozen potential pathways: a CPOE (Computerized Provider Order Entry) smart set, a radiology quick order, a free-text entry in a note followed by a verbal order, or a pre-built order set that bundles labs and consults. Each path has its own click-sequence and potential for error, forcing a split-second decision that should be intuitive but is instead a micro-optimization puzzle. This subtle but constant cognitive burden is the true price of flexibility.
Faced with overwhelming templates, drop-downs, and workflows, clinicians often default to shortcuts rather than optimal paths. Consequences include:
- Minutes wasted hunting for appropriate templates.
- Inconsistent entries across users, damaging data reliability.
- Frustration that chips away at morale and contributes to burnout.
These issues align with findings that poor EHR usability and time spent navigating systems are key predictors of clinician stress and burnout.
Hidden Inefficiencies: Complexity Buried in Customization
Even simple actions become fragmented. Prescribing a routine medication requires navigating multiple fields for dosage, frequency, route, and pharmacy. But what about a medication from an external provider? The process is frequently not automated and prone to transcribing errors because the clinician must first scan or manually enter the external note, then locate the relevant medicine in the EHR’s formulary, and finally manually reconcile and add it to the patient’s medication list. The lack of a simple, integrated ‘reconcile external med list’ function adds significant hidden labor.
Deep, multi-layered menus and infrequently used features can slow routine tasks. These inefficiencies, exacerbated by misaligned interfaces and cognitive overload, are well documented.
Tribal Knowledge: When Super-Users Become Gatekeepers
Because formal training often misses practical details, “super-users” nurture informal hacks and tips, an undocumented tribal knowledge economy. This informal knowledge can be a lifesaver to optimize workflows and documentation, like the “secret” dot phrase that automatically pulls a patient’s most recent lab values. But it can also propagate confidently held misinformation, where a clinician uses a method that is not only less efficient but also leaves incomplete data. For instance, a clinician might learn a quick way to document a patient conversation in a “telephone encounter” that doesn’t properly notify the team’s nurse, creating a dangerous communication gap.
The burden of capturing and disseminating these best practices falls on clinical leaders, diverting them from direct patient care, strategic planning, program development and research.
The Interoperability Mirage
EHRs were initially siloed, and it wasn’t until the mid-2000s that accessible Health Information Exchanges (HIEs) emerged. Even now, external records often pose a usability challenge locked behind documents saved as scanned images or incompatible formats, especially in community hospitals using outsourced radiology or specialty providers. A patient’s MRI report from an outside hospital, for example, might be imported as a 50-page PDF, requiring a physician to manually scroll to find key findings. This isn’t seamless data exchange; it’s a digital scavenger hunt. The promise of seamless data exchange often falls short.
What Works: Building Better EHR Pathways
To transcend these challenges, healthcare organizations are pursuing improvements:
- User-Centered Design
Engaging clinicians early to tailor systems ensures familiar tasks feel intuitive rather than onerous. - Standardized Workflows
Streamlined templates and workflows reduce choice paralysis and variability, ensures regulatory compliance and enhances consistency. - Intelligent Automation with AI
Advances like ambient AI scribes and autonomous agents are transforming documentation. Such tools increase patient-clinician engagement while minimizing the need to type, reducing time spent on note writing and increasing note completeness. Broader use of AI scribes has also helped clinicians reclaim time, reduce burnout, and improve patient interaction. - Continuous Feedback Loops
Soliciting ongoing input from end users helps evolve systems in real time, helping training stay relevant and preventing tribal knowledge from ossifying.
Battle Fatigue: Usability, Burnout, and Workflow Burdens
EHR use has contributed meaningfully to clinician burnout. Poor usability and increased documentation demands are widely recognized stressors. In primary care, clinicians report spending up to two extra documentation hours for every hour of patient contact. However, one study cautions that local work culture may play a larger role in burnout than EHR usage alone, 17.6% impact for culture vs. 1.3% for EHR factors.
Despite this nuance, interventions such as Amazon’s “Beyond-GROSS” at Mount Sinai, which solicit physician feedback to remove burdensome EHR tasks, and initiatives like CMS’s “Patients over Paperwork,” reflect momentum toward reducing documentation burden.
Conclusion: Repairing EHRs to Support Care
EHRs aimed to facilitate modern healthcare, but rampant customization, usability flaws, and entrenched tribal workarounds have undermined their original promise. To reverse this trajectory, organizations must design with clinicians, standardize core workflows, deploy intelligent automation, and prioritize iterative feedback. Recognizing both the value and risks of “super-user” tribal knowledge that advances workflows yet may propagate suboptimal practices is essential. By aligning tools with real-world clinical needs and freeing clinicians to focus on care, not documentation, the true potential of digital health can be unlocked.
The EHR of tomorrow must evolve beyond a passive, retrospective record of patient encounters. It must transform into a dynamic, intelligent system that actively supports and enhances care. This entails employing real-time forecasting to identify possible dangers before they become apparent, use predictive analytics to predict unfavorable clinical outcomes, and cleverly combining disparate data from wearables, labs, and genetics. Only by transitioning from a static digital chart to a system that thinks alongside the clinician can EHRs truly support not just records, but better, more human-centered care.