Every oncologist knows the feeling.

The clinic day ends, but the work doesn't.

The inbox is still full. Portal messages keep arriving. Notes need completion. Laboratory results must be reviewed. Outside records need reconciliation. Before long, the workday extends into evenings, weekends, and what many physicians now call "pajama time."

The problem has become so widespread that electronic health record (EHR) burden is no longer viewed as a technology challenge alone. It is increasingly recognized as a workforce, quality, safety, and physician well-being issue.

Recent data show oncologists are spending nearly 10 hours per week inside the EHR, with more than three of those hours occurring outside scheduled clinic time. Meanwhile, patient portal messaging continues to surge, driven by growing patient expectations for immediate digital access to their care teams.

The reality is that EHRs are unlikely to become simpler anytime soon.

But emerging evidence suggests there are practical strategies that can help physicians reclaim time, reduce frustration, and focus more attention on patients rather than screens.

1. Let AI Handle the Documentation, Not the Clinical Thinking

Perhaps the most promising development in oncology is the rise of ambient AI and automated clinical documentation tools.

These systems listen to physician-patient conversations and generate structured notes, visit summaries, and clinical documentation in real time.

The value isn't simply faster note creation.

It is the return of physician attention.

Many oncologists describe spending significant portions of patient encounters looking at a computer screen rather than maintaining eye contact and responding to emotional cues. Ambient AI can shift the physician's focus back to the patient while simultaneously reducing after-hours documentation.

The key, however, is using AI as an assistant rather than a replacement.

Clinical judgment, treatment decisions, and complex reasoning remain the responsibility of the physician. The most successful organizations are deploying AI to reduce administrative work while preserving clinician oversight.

Practical Takeaway

Use AI to:

• Draft notes
• Summarize prior records
• Reconcile outside documentation
• Organize longitudinal patient histories

Do not use AI to replace independent clinical decision-making.

2. Build a Team-Based Inbox Instead of a Physician Inbox

One of the most striking findings from recent research is the explosion in patient portal messaging.

Patients increasingly view the portal as an extension of the clinic visit. While this improves access, it has also transformed physicians into round-the-clock digital communicators.

The problem is that not every message requires physician review.

Leading health systems are creating structured triage models in which administrative staff, nurses, advanced practice providers, and care coordinators manage messages according to defined workflows before they reach the physician.

Appointment requests, medication refills, insurance questions, scheduling issues, and routine symptom management can often be addressed without direct physician involvement.

This allows oncologists to focus their expertise on the clinical questions that truly require physician judgment.

Practical Takeaway

Ask:

• Does every portal message need physician review?
• Can nursing teams manage symptom triage?
• Can administrative staff handle scheduling requests?
• Can standardized protocols address routine questions?

The goal is not fewer patient interactions. The goal is directing physician time toward the highest-value interactions.

3. Stop Optimizing Documentation and Start Optimizing Information

Many physicians assume the problem is documentation volume.

The larger issue may be information retrieval.

Modern oncology charts contain years of laboratory data, imaging studies, pathology reports, genomic testing, treatment histories, and specialist consultations. Finding the relevant information often takes longer than documenting it.

Several oncology leaders argue that the next generation of EHR innovation should focus less on creating more notes and more on helping clinicians find what matters.

Emerging AI tools are beginning to synthesize data across the medical record, summarize treatment histories, identify critical changes, and surface clinically relevant information before the visit begins.

This may prove more valuable than any documentation tool.

After all, a perfectly written note has limited value if critical information remains buried elsewhere in the chart.

Practical Takeaway

Look for technologies that:

• Summarize longitudinal cancer histories
• Highlight key treatment milestones
• Surface abnormal results
• Consolidate records from multiple institutions
• Generate visit-preparation summaries

The future EHR may not be one that asks physicians to document more efficiently. It may be one that helps them find information more efficiently.

The Bigger Picture

Technology alone will not solve EHR burden.

Many experts believe payment reform, documentation reform, and new approaches to portal reimbursement will ultimately be necessary.

But while those policy debates continue, physicians need solutions now.

The organizations making the greatest progress are not waiting for EHR vendors or policymakers to fix the problem. They are deploying AI thoughtfully, redesigning inbox workflows, and rethinking how information is presented to clinicians.

Bottom Line

The goal is not simply reducing clicks.

The goal is returning physicians to the work that only physicians can do.

For oncologists, the three most promising strategies today are:

1. Use AI to automate documentation and record review.
2. Create team-based workflows to manage portal messaging.
3. Deploy tools that surface critical information rather than generating more documentation.

The healthcare system may not solve EHR burden overnight. But these approaches offer a path toward something many oncologists feel they have lost: more time with patients and less time with the screen.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.