Your Reporting Preferences Should Travel With Every Case

Radiology quality is not only about whether the finding is correct. It is also about whether the report is written in the way the referring clinician, hospital, and care pathway expect to use it.

Every hospital has a reporting style.

Some preferences are obvious: the template, section order, or whether the impression should be brief or detailed. Others are more local and more operational. A clinician may want certain negative findings explicitly stated. A surgical team may prefer measurements in a particular format. An oncology program may expect comparisons to be phrased in a consistent way. A hospital may have its own terminology for follow-up recommendations, triage urgency, or incidental findings.

These details matter because radiology reports are not written for storage. They are written to move care forward.

A technically correct report can still create friction if it does not match the receiving team's mental model. The radiologist may have interpreted the case well, but if the report misses the local structure or preferred phrasing, someone downstream has to clarify, reformat, or mentally translate it.

That is wasted effort in a system where everyone is already short on time.

The old model: preferences live outside the case

In most radiology workflows, customer preferences live somewhere outside the actual reporting moment.

They may sit in an SOP document. They may be buried in onboarding notes. They may exist in a chat thread, a spreadsheet, a manager's memory, or the experience of a few senior radiologists who have handled that client before.

This works when volumes are small and the same radiologist reads for the same hospital every day. It breaks down at scale.

At scale, radiology becomes a distributed workflow. Cases move across shifts, subspecialties, locations, and availability pools. A report may be read by a radiologist who is clinically competent but not deeply familiar with that hospital's local preferences.

The result is predictable: avoidable edits, repeated reminders, inconsistent report presentation, and occasional dissatisfaction even when the clinical interpretation is sound.

The problem is not that radiologists do not care. The problem is that the workflow asks them to remember too much context at the wrong moment.

The reporting moment has too much hidden context

When a radiologist opens a case, the visible data is usually clinical: images, history, prior studies, modality, body part, and sometimes a protocol note.

But the invisible context can be just as important.

What does this hospital expect in the body of the report? Which measurements are mandatory? Which phrases should be avoided? Does the orthopaedic team want a grading system? Does the ICU team prefer a more direct impression? Should a normal appendix be explicitly mentioned? Should lung nodules be described in a particular sequence? Should every CT brain mention midline shift even when absent?

These are not trivial formatting choices. They shape how quickly the report can be consumed and acted upon.

When that context is not present inside the case, the radiologist has to reconstruct it from memory. That is cognitively expensive. It is also unreliable, because even good radiologists cannot carry hundreds of local reporting preferences in their head while reading high-volume lists.

The workflow should not depend on heroic recall.

The better model: preferences travel with the case

At 5C, we are working toward a different model.

The hospital's reporting preferences should not live separately from the reporting workflow. They should travel with the case itself.

That means when a radiologist opens a case, the starting report template should already reflect the relevant customer context. The section structure should be appropriate. The expected negatives should be included. The terminology should match the hospital's style. The report should begin closer to what the final customer-ready version needs to look like.

This is not about forcing every radiologist into rigid automation. It is about removing unnecessary memory work so the radiologist can focus on the medicine.

A good reporting workflow should behave like a clinical assistant that knows the customer context before the radiologist starts typing.

It should know that Hospital A wants a particular MRI knee structure, Hospital B wants a shorter CT chest impression, and Hospital C wants specific post-operative language for spine cases. It should know which preferences apply to modality, body part, clinical indication, and customer.

Most importantly, it should surface that context at the right time: inside the case, not after the report has already been written.

Why this matters for quality

Quality in radiology is often discussed as accuracy, turnaround time, and communication of critical findings. All of those are essential.

But there is another layer: report usability.

A usable report is not merely correct. It is easy for the intended clinician to read, trust, and act on. It uses familiar structure. It highlights the right details. It avoids unnecessary ambiguity. It fits the way that care team works.

Customer-specific reporting preferences are one way hospitals express that usability requirement.

When those preferences are remembered consistently, the report feels aligned with the institution. When they are missed, even a good report can feel generic.

That distinction matters in teleradiology, where trust is built not only by the diagnosis but by the repeated experience of receiving reports that fit the hospital's clinical rhythm.

What this looks like in practice

The practical version is simple.

Capture preferences once. A hospital's expectations should be documented centrally, not scattered across SOPs, onboarding notes, chats, and memory.

Attach them to the right case types. Preferences should map to the customer, modality, body part, clinical indication, and reporting context where they actually apply.

Bring them into the reporting moment. When a case opens, the template, expected negatives, measurement prompts, comparison language, and preferred phrasing should already be close to what the hospital expects.

For example, a CT abdomen from one hospital may open with a structured template that explicitly includes bowel obstruction, appendix, free air, free fluid, and comparison language. The same study from another hospital may use a shorter emergency-style format with a sharper impression and less descriptive body text.

Both reports can be clinically sound. The difference is that each report begins in the customer's preferred language.

This is especially useful when new radiologists join a workflow, when case volumes surge, when subspecialty cases move between teams, or when a hospital updates its reporting expectations.

Instead of retraining every radiologist through repeated feedback, the workflow itself carries the instruction.

That is the real opportunity: not replacing radiologist judgment, but surrounding it with better context.

The radiologist should focus on the medicine

Radiologists should spend their attention on the image, the diagnosis, the differential, the comparison, the clinical implication, and the final communication.

They should not have to remember whether a particular hospital prefers "no acute intracranial abnormality" or "no acute intracranial haemorrhage, infarct, or mass effect" as its standard phrasing. They should not have to keep track of which customer wants every normal chest X-ray to explicitly mention cardiomediastinal silhouette, costophrenic angles, and osseous structures.

That is workflow memory. It belongs in the system.

The more customer context the workflow can carry, the less unnecessary rework radiologists and operations teams have to absorb. Reports become more consistent. Feedback loops become cleaner. New preferences can be implemented faster. The reading experience becomes less dependent on who happens to remember what.

We are still building this out at 5C, but the direction is clear.

Radiology reporting should not start from a blank generic template and depend on human memory to become locally useful. It should start with the right context already in place.

Bottom line: the radiologist should focus on the medicine. The workflow should remember the customer.