When Good Fields Make Bad Forms: Data-Entry Design in Clinical Research

Series learning objectives

By the end of this series, you'll be able to:

See the work behind data entry

Separate the information being collected from the work required to turn it into usable data.

Recognize useful relationships before the form removes them

Identify useful position, order, grouping, spatial relationships, and other cues in the source that can make entry easier and more accurate.

Design around the person doing the work

Account for what people already know, the routines and conventions they rely on, and the characteristic errors they're likely to make.

Decide what work belongs with the person and what belongs with the form

Determine when the form should simply display the work, support it with guidance, or do part of the work itself.

We've all been there. A new clinical research project is getting underway, and eventually the conversation turns to data capture.

Someone asks:

“What should we collect, and how is it defined?”

Everyone is ready to chime in. Which variables matter? How should they be defined? What response options do we need? What's required? What values are allowable?

Then someone asks:

“How will we collect it, and what should the forms look like?”

A few nervous stares.

We tend to be much better at the first conversation than the second. We're pretty good at thinking about the data half of data entry. We're not nearly as practiced at thinking about the entry half.

And that matters because getting the fields right doesn't necessarily mean we've designed a good data-entry form.

What does someone have to do to get the right data into the right place?

Where does the information come from? What must happen to turn it into data? Who is doing that work, and what do they bring to it?

Those questions point us toward three things:

That's where this series starts. Part 1 puts the three together. Part 2 looks harder at the source, Part 3 at the person, and Part 4 comes back to the work itself.

•Part 1: Source, task, and person

A framework for understanding the work behind data entry.

•Part 2: Relationships in the source

Look for useful relationships and cues in the source before reorganizing the information into fields.

•Part 3: What the person already brings

The same source and task may need a different form depending on what the person already knows and how they work.

•Part 4: How much work should the person do?

Display the work, support the work, or let the form do part of it.

Because the question isn't only:

What data should we collect?

It's also:

What work are we asking someone to do to collect it?

That's how good fields can still make bad forms.