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Taming the Data Entry Parrot: Repeating Forms in Clinical Research · Part 3 of 3

Repeating Study Forms in Clinical Research: How to Keep Instances Straight

Repeating forms can become difficult to manage when the same information appears across visits, dates, and related events. Part 3 looks at how thoughtful layouts and timelines can help people see what already exists, understand how it fits together, and know where new information belongs.

The same Adverse Event number 2 form shown twice side by side on a monitor, and again through a pair of spectacles held up to the screen, bringing one of the two into focus.

At a glance

Ask what the instance belongs to

Some repeated information belongs naturally to a study event. Other information belongs to the participant's history and simply crosses study visits.

Distinguish the dates that matter

The date something happened, the date it was entered, the date it ended, and the date data collection stopped are not necessarily the same thing.

Look at relationships, not just values

Two date ranges can differ and still overlap. Two instances can also be connected through a procedure, event, lesion, assessment, or another relationship that time alone cannot show.

Make the connections visible

When repeated information stretches across visits or depends on other instances, layout can help people understand what already exists and where new information belongs.

Article

Once we've determined whether a new form is needed and how to populate the fields, a different issue pops up. Where does it belong?

That sounds straightforward when the study schedule provides the answer. A Week 4 vitals form belongs to Week 4. A Baseline questionnaire belongs to Baseline.

But repeating forms don't always fit neatly inside the study schedule.

A medication may begin three months before a study visit and continue through the next four. An adverse event may begin between visits and remain active across several of them. An angiogram may occur on a particular date and identify several AVMs that are then followed independently.

The participant has one history. The study may give us several different ways of looking at it. And the person entering data needs to be able to see how those pieces fit together.

What Does This Instance Belong To?

Consider two kinds of repeating information.

Study-event-based. A participant completes three pain assessments during Visit 4. Each assessment clearly belongs to Visit 4. If we're looking for Assessment 2 later, knowing the study event helps us find it.

Participant-history-based. A medication is different. It may have started before Visit 1, continued through Visits 2 and 3, and ended between Visits 3 and 4.

Forcing that medication to "belong" to one of those visits can create a misleading picture. The medication belongs to the participant's history, while individual study visits may simply give us opportunities to review or update it.

The same issue arises with adverse events, diagnoses, tumors, procedures, and other information that can persist across study events.

So the question is not simply, "When was this entered?" It's, "What does this instance belong to?"

Study visits are landmarks. The participant history is what actually runs across them.

When Does It Start?

Dates can look like simple fields on a form, but they often define how a repeating instance relates to everything around it. Sometimes the start date is naturally tied to the study event. If we're recording a procedure performed during today's visit, the relationship may be obvious. Other times it isn't.

  • A participant may report at today's visit that Medication A started six weeks ago.
  • An adverse event may have begun yesterday.
  • A planned medication change may have a start date next Monday.

The study visit date and the instance start date aren't necessarily the same thing.

Even a future date isn't automatically wrong. It depends on what the form is meant to represent.

And When Does It End?

Suppose we're following an adverse event. Two different endings are in play, and they are typically not the same date.

Event end
When the thing itself stops or resolves.
Data-capture end
When the study stops collecting information about it.

An event could resolve on June 12, with a final follow-up assessment completed on June 15. Or data collection could end while the event itself remains unresolved because the participant has completed the study.

If the form gives us a single field called End Date, we've hidden that distinction.

Two kinds of end. Either can come first, and a single End Date field hides the difference.

Some events may not have an end at all. A participant may have a seizure type that remains part of their clinical history throughout the study. Leaving an End Date blank might mean:

  • ongoing
  • unknown
  • not yet entered
  • not applicable

Those are different states. If they matter, the form needs some way to distinguish them.

Dates Can Be Different Without Being Independent

Part 1 looked at a medication entered as 10 mg from January 1 through June 30, followed by an attempt to create another instance of the same medication at 20 mg from March 15 through April 30.

None of the dates match.

But the ranges overlap.

Whether that's allowed depends on what the study is trying to represent.

Two tumors. They can obviously exist at the same time, and two courses of the same medication may also overlap legitimately under some protocols.

Two dose records for the same medication. In another study, that overlap may indicate a contradiction.

So date validation isn't always a matter of asking whether two dates are equal. Sometimes the relationship between the ranges is what matters.

The same overlap is allowed for tumors and a conflict for two doses of one medication.

Relationships Aren't Always About Time

Some repeating instances are connected in ways that dates alone can't show. An angiogram may identify three AVMs. A procedure may treat one specific tumor. A follow-up assessment may exist because a particular adverse event occurred. Those relationships matter during data entry.

Which instance is this related to?

If I'm entering a procedure, knowing that the participant has three tumors isn't enough. I may need to know which tumor this procedure treated. If I'm entering an AVM measurement, I may need to know which angiogram identified it. And if I'm completing an adverse-event follow-up, I need to know which adverse event triggered it.

A list of forms can tell me that all of those records exist, but very little to help me understand how they're connected.

Seeing Is Entering

This is where layout starts doing more than making a screen look organized.

Imagine entering information at Visit 4. The participant has two medications, an adverse event that began after Visit 2, an angiogram at Visit 3, and two AVMs identified from that angiogram.

I can open each form individually and piece that history together. Or the interface can show me the history.

A timeline can make it immediately apparent that Medication A was already active before the study began, Medication B started later, the adverse event remains open, and the two AVMs came from the same angiogram.

Now the display isn't simply reporting what happened. It's helping me enter what happens next.

Before creating another medication, I can see the medications already there. Before entering another AVM, I can see the ones already identified. Before closing an adverse event, I can see where it sits relative to the visits and follow-ups around it.

Seeing becomes part of entering.

When the history is visible, seeing becomes part of entering.

The goal isn't to turn every repeating form into a timeline. Sometimes a list is exactly what someone needs. Sometimes the study event provides all the organization necessary.

But when repeated information stretches across visits, overlaps in time, or depends on other repeating information, showing those relationships can remove work that would otherwise be left to the person entering the data. The information was already connected.

The question is whether the person entering it can see the connections.

Put it to work

Belonging

  • Decide what each instance belongs to.

    Determine whether it belongs to a study event, the participant's ongoing history, another repeating instance, or some combination of these.

  • Don't force persistent information into a visit structure.

    A visit may be when information is reviewed without being what the underlying instance actually belongs to.

Time

  • Define what each date represents.

    Distinguish dates such as occurrence, start, resolution, data-capture end, and study-event date when those differences matter.

  • Validate relationships between dates.

    Look beyond exact matches. Overlap, containment, sequence, and gaps may matter more than whether two dates are identical.

Relationships

  • Capture connections that time cannot express.

    Identify relationships such as which procedure treated a tumor, which angiogram identified an AVM, or which event triggered follow-up.

  • Make existing relationships visible during entry.

    When understanding the history matters to entering the next piece of data, show enough of that history to support the task.

The information may already be connected. Good design makes those connections visible.


Series Summary

Across this series, we've treated repeating forms as more than a "+ New" button.

First, we asked what makes an instance genuinely new and how people recognize what already exists.

Then we looked at what should happen when that instance appears again: whether the form should start blank, show previous information, carry values forward, or ask someone to review and confirm them.

Finally, we've looked at where those instances belong and how dates, visits, and relationships connect them to the rest of the participant's history.

The principle underneath all three parts is simple:

A repeating form is not just another copy of a form. It is another instance of something, with an identity, a history, and relationships to everything around it.

Designing it well means making those things clear to both the system and the person entering the data.

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