Artificial intelligence is rapidly becoming part of healthcare. Much of the conversation has focused on efficiency: reducing administrative burden, improving documentation, analyzing data, supporting diagnoses, and helping clinicians work faster.
Those applications matter, but I believe one of the most promising opportunities for AI is much more human: helping patients and clinicians better understand one another.
Healthcare has always been built around clinical goals. Lower the blood pressure. Improve the A1C. Reduce pain. Restore range of motion. Improve a lab value. Those are important measures, but they are not always the reason the patient walked through the door.
A patient may not simply want less knee pain. They may want to play golf again, travel with their spouse, get down on the floor with their grandchildren, or continue living independently. The better we understand what a patient is actually trying to accomplish, the better chance we have of building care around what matters most to them.
AI Can Help Identify the Patient’s Real Goal
One of the challenges in healthcare is that enormous amounts of information are exchanged during a relatively short clinical encounter.
Patients describe symptoms, concerns, priorities, fears, previous treatments, lifestyle limitations, and expectations. Clinicians simultaneously gather a history, interpret diagnostic information, consider treatment options, document the encounter, and make decisions.
Important information can easily become buried.
AI has the potential to help organize that information differently. Instead of only summarizing symptoms and diagnoses, AI-enabled systems could help identify the patient’s stated goals and bring them forward in the clinical conversation.
Imagine opening a patient’s chart and seeing not only, “Primary complaint: right knee pain,” but also, “Patient goal: return to walking three miles with spouse without having to stop because of pain.”
That second statement changes the conversation. It provides context for treatment decisions, creates a meaningful outcome to measure, and gives the clinician and patient something they can work toward together.
AI Can Help Track Whether Care Is Moving the Patient Toward That Goal
Healthcare traditionally happens in snapshots. A patient comes into the office, discusses what is happening, receives a treatment plan, and returns weeks or months later. A great deal may happen between those visits. AI could help create more continuity between those moments.
Patient-reported outcomes, wearable technology, activity data, symptom tracking, questionnaires, and other information could help clinicians understand whether the patient is actually moving toward the outcome they care about.
If someone’s goal is to return to walking three miles, progress should not only be measured by a pain score. How far are they walking now? How often? What is preventing further progress? Has their confidence improved? Have their goals changed?
AI can help organize these different inputs and present them in a way that allows clinicians to see patterns that may otherwise be difficult to identify. That creates an opportunity to adjust care based not only on clinical measures, but also on whether the patient is actually getting closer to the life they want to return to.
AI Can Help Create Better Conversations Between Patients and Clinicians
There is an understandable concern that technology could make healthcare less personal. That is possible if we use it poorly. The objective should never be to replace the judgment, empathy, or relationship that exists between a clinician and a patient. Instead, AI should help clinicians spend less time searching for information and more time understanding the person sitting in front of them.
Technology should help us ask better questions: Is the treatment working? Is the patient progressing toward what matters to them? Are we still pursuing the same goal? Has that goal changed? Is there something we are missing?
If AI helps clinicians answer those questions more clearly, it becomes much more than an administrative tool. It becomes a communication tool.
Defining Success Together
Clinical outcomes will always matter. Evidence-based medicine will always matter. Objective measures will always matter.
But patient goals should matter too.
The best care happens when those things come together. A clinician brings medical knowledge, experience, and judgment. A patient brings their priorities, values, circumstances, and goals. The treatment plan should exist at the intersection of the two.
The future of artificial intelligence in healthcare should not simply be about making healthcare faster. It should be about making healthcare more connected, more personalized, and more focused on what the patient is actually trying to accomplish.
