The hidden clinical work in every patient encounter

The hidden clinical work inside every patient encounter: Why the visit extends far beyond the room

Imagine a scenario when for every 15-minute appointment with a patient, clinicians spend even more time behind the scenes. Consider 10 minutes spent reviewing the patient's chart, lab results, and medication history before the encounter and another 15 minutes finalizing documentation, placing orders, responding to follow-up questions, and coordinating referrals. That hypothetical "15-minute visit" consumes 40 minutes of clinical time.

Research suggests that clinicians spend almost as much time on direct patient care as they do outside of the patient encounter: 27.2 hours per week on direct patient care, but 20.3 hours on indirect care and administrative tasks.¹ This hidden clinical work — the preparation, documentation, and follow-up that surrounds each visit — represents a significant portion of the workday.

While healthcare practices are adopting AI tools to improve in-room efficiency, many are discovering a critical gap: the work hasn't disappeared. It's moved from real-time note-taking to post-visit review and refinement.  

Effective AI solutions must support the entire encounter lifecycle, not just the conversation in the exam room.

The complete patient encounter: Beyond face-to-face time

The patient encounter begins long before the clinician enters the exam room and continues well after they leave. Understanding this complete lifecycle reveals where administrative burden accumulates and where technology can make the most meaningful impact.

Before the visit: Preparation and context-building

Pre-visit preparation sets the foundation for quality care. Clinicians must synthesize information from multiple sources: reviewing medication lists for potential interactions, analyzing trends in lab values over time, and identifying care gaps to address. For patients with complex conditions or those who haven't been seen recently, this context-building becomes more critical and time-intensive.

During the visit: The documentation dilemma

The face-to-face encounter presents a fundamental tension: clinicians must simultaneously engage with patients and capture accurate documentation. Real-time EHR data entry means divided attention — typing while listening, clicking through screens while maintaining eye contact. The alternative, deferring documentation until later, simply moves the work to an already crowded post-visit queue.

After the visit: Where work accumulates

Documentation finalization is just the beginning of post-visit responsibilities. Each encounter generates a cascade of follow-up activities: coding review to ensure billing accuracy, order entry and prescription management, referral coordination, and care team communication. Meanwhile, the inbox fills with test results requiring review, patient portal messages needing responses, and prior authorization requests demanding attention.

High levels of EHR documentation burden tend to crowd out other clinical activities.² As regulatory requirements expand and quality reporting becomes more complex, the post-visit workload continues to grow, potentially pushing chart completion into evenings and weekends.

The AI paradox: Efficiency gains that create new work

Ambient documentation technology has the potential to transform the patient encounter. By capturing conversations naturally and generating clinical notes automatically, these tools help reduce real-time note-taking, allowing clinicians to focus on patient engagement rather than keyboard entry.

After the visit, AI-generated notes still benefit from clinical review and editing to ensure clinical precision, coding specificity, and regulatory compliance. Ambient AI can support a more efficient workflow by capturing the conversation in real time and giving clinicians a strong starting point for final documentation.

Research on workflow fragmentation suggests that technology can shift work rather than eliminate it.³ When documentation moves entirely from during to after the encounter, the post-visit to-do list grows longer. Time saved in the exam room may reappear, and possibly in greater amounts, during evening chart completion sessions.

The critical question becomes: Are we reducing total administrative time, or simply changing when it happens?  

Evaluating AI solutions strategically

As practice leaders evaluate ambient documentation or other AI tools, many are looking beyond in-room efficiency metrics and asking several important questions:  

• Can the solution reduce total time spent on documentation, or does it shift when and where that time is spent?
• Where does the work go, and who does it? If the editing burden has increased, has the problem been solved or transferred?
• How does it integrate with existing workflows? Solutions that require new steps or separate systems may add complexity rather than reduce it.

The most meaningful solutions address administrative burden across the entire encounter lifecycle rather than simply moving it to a different phase.

Supporting the full lifecycle: An integrated approach

Technology works best when it optimizes processes across all phases of the patient encounter, not just one moment in time. Isolated point solutions can create gaps, handoffs, and duplicated effort. An integrated approach helps AI tools work together, sharing context and reducing friction throughout the encounter lifecycle.

Before the visit: Chart Assistant with Sage

Pre-visit preparation becomes more efficient when AI can quickly surface the most relevant patient information. Chart Assistant with Sage™ streamlines chart review by identifying key clinical details, recent changes, and potential care gaps. By reducing cognitive burden and helping clinicians build context faster, it’s designed to support better preparation for each encounter.

During the visit: athenaAmbient™

Ambient documentation technology captures patient-clinician conversations as they occur, generating clinical notes in real time while allowing clinicians to maintain focus on patient care rather than keyboard entry. By reducing the documentation burden during the encounter, clinicians can be more present and engaged with patients.

During and after the visit: AI-native encounter

AI support extends beyond note generation. AI-native encounter enhances the clinical workflow, from helping clinicians capture the visit, refine documentation, and complete encounter tasks more efficiently. By embedding AI throughout the workflow, it helps reduce the administrative burden and helps clinicians spend more time focused on patient care.  

The integration advantage

When AI solutions are designed to work together rather than in isolation, they create compounding benefits. Connected tools share context across the encounter, reducing the need to re-enter information or reconcile data from multiple sources. Clinical insights gathered during pre-visit preparation inform real-time documentation, which in turn supports more accurate post-visit coding and follow-up planning.

This integration reduces redundancy and rework, addressing the paradox of efficiency gains that create new work. Instead of shifting administrative burden from one phase to another, integrated AI solutions are designed to help reduce the total time clinicians spend on documentation and administrative tasks, creating sustainable operational improvement across the practice.

Four tips for practice leaders

As practices evaluate AI solutions, these questions can help distinguish between tools that reduce burden and those that simply redistribute it:  

1. Start with the complete picture. Does the solution address the full encounter lifecycle, or only one phase? How does it integrate with existing EHR workflows rather than creating parallel processes? Understanding the scope of impact helps predict whether efficiency gains will be sustainable and support practice workflow optimization.
2. Focus on net time savings. The most important metric isn't time saved during the visit — it's total time saved across preparation, documentation, and follow-up. Ask vendors to demonstrate how their solution affects the entire workflow, not just one moment. Look for evidence of reduced total documentation time, not just shifted responsibilities.
3. Consider the implementation reality. Does the technology fit into existing workflows, or does it require clinicians to adopt entirely new processes? What oversight and review processes are needed to maintain quality and compliance? Solutions that demand significant behavior change or create new review burdens may struggle with adoption, regardless of their technical capabilities.
4. Monitor the right outcomes. Track clinician satisfaction across all workflow phases, not just during patient encounters. Measure total documentation time consistently over weeks and months. Watch for signs of unintended work shifting. If one role burden decreases while another increases, the practice hasn't gained efficiency; it's simply redistributed the load.

The complete picture matters

The conversation around AI in healthcare often focuses on individual moments — the exam room visit, the documentation session, the chart review. But meaningful administrative burden reduction requires a broader view.  

When AI solutions are designed to work together to support clinicians before, during, and after every encounter, they create genuine efficiency gains and reduce clinicians’ cognitive burden. This integrated approach respects the complexity of clinical workflows while addressing real operational challenges.

As practice leaders evaluate AI adoption, the most important lens is the complete encounter: Does this technology eliminate work, or just move it? Does it integrate seamlessly, or create new processes?

The practices that answer these questions carefully will be best positioned to harness AI's potential to genuinely reduce administrative burden.

Learn how athenaOne® — athenahealth's AI-native solution — supports clinicians before, during, and after every patient encounter.