Krishna
Founder, ShylCare
Ask any junior doctor at a busy hospital what the worst part of their job is. A lot of them will say discharge summaries.
Not because the work isn't important — it is. A discharge summary is often the only document that travels with a patient from one point of care to the next. It's the handoff document. But writing it from scratch, from memory, after a five-day admission with multiple investigations, consultant visits, and medication changes, after a full ward round, is genuinely exhausting.
And it shows. Summaries get abbreviated. Key details get left out. Language gets vague. The whole document becomes less useful than it should be.
The 30-minute discharge summary isn't 30 minutes of thinking. It's mostly 30 minutes of retrieval and reformatting:
A doctor who was present for the entire admission knows this story. The problem is reconstructing it from fragments scattered across different records.
This is exactly the kind of task AI is genuinely good at.
When a patient is ready for discharge in ShylCare, the system already has the complete clinical picture: admission diagnosis, ward notes, all lab results ordered during the stay, radiology findings, medications and any changes, vital trends, consultant visit notes.
The AI takes all of that context and generates a structured draft discharge summary — in the format the doctor expects — in about 10 seconds.
The doctor then reviews it. They might adjust the clinical impression, add a nuance the AI missed, change the follow-up instructions, sign it. That review takes 90 seconds to two minutes, not thirty.
The document that comes out is structurally complete. It has everything it needs to have because the AI pulled from a complete clinical record, not from a tired doctor's memory at 6pm.
I want to address this directly because it comes up every time.
"How do we know the AI is accurate?"
The AI is generating a summary from your own data. It's not making clinical judgments — it's not diagnosing, it's not deciding on treatment. It's synthesising and structuring information that already exists in the record. Think of it less like a clinical decision support tool and more like an extremely fast medical writer who read every note in the chart.
The doctor reviewing and signing the summary is the accuracy check. They know the patient. They can see in two minutes whether the summary reflects what actually happened. If it doesn't, they change it.
This is the same workflow as a junior doctor drafting a summary for a senior to review — except faster and without the junior doctor having to do it.
"What if it hallucinates something?"
This is a real concern with AI systems, and it's why the review step is non-negotiable. ShylCare doesn't auto-generate and auto-file. The draft goes to the doctor's screen for review and sign-off. Nothing is finalised without a clinician's explicit approval.
We also ground the generation tightly to the patient's actual record. The AI is explicitly instructed not to add information not present in the data — it synthesises what's there, it doesn't invent.
India has a doctor-to-patient ratio problem. The doctors we have are seeing more patients than any system was designed to handle.
Documentation burden is a meaningful contributor to clinical burnout. It's time that doesn't go to patients, and it accumulates. A doctor who writes fifteen discharge summaries a week, if AI assistance saves 25 minutes per summary, gets back roughly six hours a week. That's a real number.
Six hours a week is more time with patients. It's finishing on time occasionally. It's the difference between sustainable and not.
The AI doesn't replace clinical judgment. It doesn't decide what the patient needs next. It doesn't catch a drug interaction you missed or flag an unusual investigation result (though we're thinking about that).
What it does is handle the documentation scaffold — the structure, the retrieval, the formatting — so that the doctor's attention goes to the parts that actually need their expertise: the clinical interpretation, the nuanced instructions, the empathetic discharge conversation with the patient's family.
That division of labour makes sense. The parts that require medical training should get medical attention. The parts that require typing and reformatting shouldn't.
AI discharge summaries are available on ShylCare's Growth plan and above. If you want to see it work on a real admission workflow, book a demo and we'll walk through it with your actual discharge template.
We'll walk through your actual workflows — no generic demo, no slide deck.