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How AI Can Help Doctors Manage Complex Patients Faster

What’s the Problem?

Outpatient clinicians are overwhelmed by the sheer volume and fragmentation of data in medically complex patients’ charts, making it nearly impossible to deliver comprehensive care within standard visit time constraints.

The Problem

The most intellectually challenging cases I’ve managed in the outpatient setting aren’t necessarily the rare zebras. They’re the medically complex patients who’ve been in the healthcare system for years. And I mean years….

You know the type: multiple chronic conditions, thick charts, and a long trail of care from specialists, hospitalizations, and support services. By the time they reach my clinic, their chart reads more like a novel than a note. Labs, imaging, consults, discharge summaries, home health updates, social work documentation, and insurance case management notes—it’s all there, scattered across different sections of the EHR.

Before seeing them, I carve out 15–20 minutes to review everything, which is already stretching my schedule thin. But even then, it’s rarely enough. I’m forced to prioritize—focusing on the diabetes, hypertension, and CKD management—only to realize later that a chronic macrocytic anemia has been slowly worsening, buried in labs from six months ago. That damn, I should’ve caught that moment hits hard—especially when your attending points it out.

The volume and fragmentation of data make it nearly impossible to synthesize everything into a coherent care plan within the constraints of a 20-minute visit.

These patients don’t need one-time fixes. They need continuity, thoughtful care, and frequent touchpoints. But our current outpatient systems aren’t built for this. The infrastructure, the EHR, and even the visit lengths are optimized for volume—not complexity.

So the question is:

How can we better support clinicians in delivering high-quality care to patients who need it most, when the tools we have are designed for throughput, not depth?

Root Cause Analysis: 5 Whys

The Problem: Outpatient clinicians are overwhelmed by the volume and fragmentation of data in medically complex patients’ charts, making it difficult to deliver comprehensive care in a standard visit.

1. Why are clinicians overwhelmed by the volume and fragmentation of data? Medically complex patients have years’ worth of data spread across multiple notes, labs, imaging reports, and consults from various providers, making it hard to synthesize quickly.

2. Why is the data spread across so many sources and formats? The EHR is designed primarily as a documentation and billing tool, not as a clinical decision-support system that organizes and prioritizes relevant information.

3. Why isn’t the EHR designed to organize and prioritize relevant information? Most EHRs were developed with input from administrators and compliance officers rather than frontline clinicians, emphasizing data capture and regulatory needs over usability.

4. Why is clinical usability often deprioritized in EHR development? Healthcare organizations typically prioritize features that meet billing, coding, and compliance requirements—areas that drive immediate revenue or mitigate legal risk.

5. Why is revenue and risk mitigation prioritized over clinician usability and workflow efficiency? The fee-for-service healthcare model incentivizes volume and documentation rather than quality and clinician experience, influencing both administrative focus and vendor priorities.

Impact Analysis

• Patient: This problem means that important details about their health can be overlooked, leading to delayed diagnoses, fragmented care plans, and a loss of trust in the healthcare system. They may leave visits feeling unheard or confused, and may experience unnecessary repeat testing or contradictory advice from different providers.

• Clinician or Provider: This problem creates constant cognitive overload, decision fatigue, and the frustrating sense that they’re missing something critical despite their best efforts. This contributes to burnout, dissatisfaction with clinical work, and a feeling of helplessness in delivering the level of care they know their patients need.

• System: This issue results in inefficiencies, such as duplicative services, increased downstream costs from missed or late interventions, and higher rates of preventable complications. Over time, it erodes both the quality and value of care delivered, while perpetuating a system that rewards documentation volume over meaningful outcome.

Solution

When people talk about ambient AI in healthcare, the conversation usually centers around documentation—automating note-taking or transcribing conversations between physicians and patients. But I think we’re missing the bigger picture.

The real opportunity lies in using AI to streamline the actual workflows that weigh clinicians down—like the cognitive labor required to prepare for a visit with a medically complex patient. These workflows aren’t complicated in theory, but they involve sifting through a massive amount of fragmented data: labs, imaging, specialist notes, hospital discharges, social work documentation, and more.

This is where I think AI can truly shine.

Imagine a tool that doesn’t just listen in on the visit, but works behind the scenes before the visit even starts. It analyzes years of clinical data, identifies important trends (like a slow but steady rise in creatinine), flags incidental findings that were never addressed, and surfaces the most relevant issues for discussion. Then, it compiles this information into a succinct summary or pre-visit briefing—almost like a clinical executive summary—so that the physician is walking into the room already equipped with context, priorities, and talking points.

This would reduce cognitive overload, improving diagnostic accuracy, and making sure no patient falls through the cracks simply because their chart was too dense to digest in 15 minutes.

If we build AI tools to support how clinicians think—not just how they document—we’ll not only improve workflows, but also outcomes.

EDUCATION

I just finished recording my new course—How Healthcare Really Works—launching July 1.

If you want to actually understand how hospitals get paid, why drug prices are so high, and how the system really functions, you can pre-enroll now and get $50 off.

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EDUCATION

I’m working on a new course—How Healthcare Really Works—launching July 1.

If you want to actually understand how hospitals get paid, why drug prices are so high, and how the system really functions, this course if for you. Huddle+ eats for free :).