ChatGPT helps Daniel Green coordinate the fragmented work of caring for his wife, Laura, as she lives with Long COVID. His day job is helping executives understand and use AI. At home, that skill became part of how he cares for the person he loves.
Laura is an internal medicine physician. After developing a fast heart rate, muscle spasms, tingling and a sensation like a phone vibrating inside her chest, she had the medical terms to describe exactly what she was feeling. But she couldn’t find a local clinician who could see the whole picture. Her test results sat on separate pages in MyChart. Specialists focused on different parts of her case. Appointments lasted 15 minutes – less time than it took to drive to the clinic.
Daniel began using ChatGPT to bring the pieces together. He collected lab results, imaging reports, prescriptions and notes from different specialists in one place. Before each appointment, he would tell ChatGPT what kind of clinician they were about to see and ask it to prepare what he calls a “clinical executive briefing”: what had changed, what they had already tried and what that particular doctor needed to know.
“Here are all these pieces,” Daniel says. “They don’t talk to each other. Let’s put them into a single place.”
The work extended far beyond medical records. Based in Kansas City, Missouri, Daniel used deep research to look for specialists across the country and ChatGPT to help draft outreach. That search helped Laura reach a clinician in New York City, Brian Kim, whose research addressed some of her chronic symptoms. Daniel and Laura were fortunate enough that they could travel for care, but the experience showed Daniel how often medical expertise is trapped in a local geography, or scattered across specializations and brief appointments.
Caregiving, for Daniel, includes dozens of administrative jobs that had nothing to do with his day job. When Laura changed jobs, he used ChatGPT to compare health plans across dense PDFs, incorporating pharmacy spending, deductibles and the performance of their existing health savings account. The employer’s benefits calculator was broken and returning zero dollars for every plan. When new insurance cards failed to arrive, he used ChatGPT Work to coordinate a chain of support chats and department handoffs.
He now experiments with an interactive dashboard that brings together lab results, prescriptions and health-tracking data. It helps him organize questions and look for changes worth discussing with Laura and her clinicians.
Recent research suggests that Long COVID may affect women more than men. Laura is still struggling with symptoms. Once a month, Daniel drives about two hours to pick up a treatment from a compounding pharmacy. There are many steps on their journey where ChatGPT can't help. Millions of others with Long COVID are further from answers than she is, without a physician in the family or a caregiver who works in AI. The expertise they need exists. Daniel's hope is that these tools will help it reach them.
