A form (in this case, an electronic case report form, or eCRF) is a digital, usually web-based, questionnaire for collecting data about a study participant. There are many routes data can take into the eCRF: it may be manually entered, piece by piece, by a clinical research coordinator or the participant herself; uploaded in bulk; or transferred from an external data source (e.g. an imaging database) through a process of integration.

Forms hold the data that biostatisticians will analyze to draw conclusion from a study. Given the preciousness of their contents, it’s no wonder that a whole system of required components, controls, and safety features should emerge to ensure that these forms function reliably.

What do laptops, smartphones, and tablets have in common? They’re all extremely sophisticated calculators. (The word “computer” derives from the Latin term computare, which means “to calculate.”) Electronic CRFs are thus uniquely suited to carry out even the most complex calculations in fractions of a second, often while the user is interacting with the form. Together with skip logic and edit checks, these real-time results enable your forms to collaborate with research coordinators, lending a faultless memory and mathematical power to the task of capturing data.

Here are just a few labor-saving capabilities of today’s eCRFs:

• date calculations
• unit of measure conversion
• clinical measures (e.g. Body Mass Index)
• patient-reported outcome scoring

“You say toe-MAY-toe, I say toe-MAH-toe.” Idiosyncrasies like that are just fine for ordering salad. But when it comes to the interchange of clinical data, stylistic differences are the enemy. Analyses of safety and efficacy depend on comparing numbers gathered from around the world. Without a precise, mutually agreed upon system of conventions (e.g. abbreviations, measurement labels, table layouts), such a comparison is impossible.

For better or worse, the standard for health data has yet to emerge. The types of data that research consumes, from settings as various as the exam room, imaging center, and laboratory, are simply too vast. But a finite number of international conventions are gaining traction. Examples include HL7, LOINC and SNOMED. These and similar standards are beginning to institute a universal way of documenting clinical terms, storing and exchanging electronic data, reporting lab results, and more. When it comes to the collection and aggregation of clinical research data specifically, the biggest game in town is CDISC.

Mistakes happen in the course of data entry. A research coordinator, intending to input a weight of 80 kilograms, leaves the field before striking the “0” key. Her colleague, completing a field for temperature, enters a value of 98, forgetting that the system expects the measurement in Celcius. But no adult enrolled in a clinical study weighs 8 pounds. And the patient with a body temp of 98 degrees Celsius? “Fever” is something of an understatement.

Left standing, errors like the ones above distort analysis. That’s why data managers spend so much time reviewing submitted data for reasonableness and consistency. What if it were possible to guard against introducing error in the first place? With electronic forms, it is possible.

Edit Checks in Clinical Data Management

“Edit checks,” sometimes called “constraints” or “validation,” automatically compare inputted values with criteria set by the form builder.  The criteria may be a set of numerical limits, logical conditions, or a combination of the two. If the inputted value violates any part of the criteria, a warning appears, stating why the input has failed and guiding the user toward a resolution (without leading her toward any particular replacement).

Edit checks may be simple or complex; evaluate a single item or a group of related items; prevent the user from moving on or simply raise a flag. You can learn all about these differences below. The goals of edit checks are universal: higher data quality right from the start!

What do we want in a physician? Encyclopedic knowledge, honed intuition, and proven skill, for starter’s. But without a calm and compassionate bedside manner, that physician does far less for their patient than they might. The same applies to forms. All the technical capability in the world means little if interacting with the form causes frustration. The insistence on a great user experience informs every part of this guide. In the section on skip logic, for example, we examined a way of respecting the user’s time. In the section on edit checks, we explored ways to help the user avoid entering invalid data. These are two facets of a positive user experiences, but there are dozen’s more. How should a form look on any given screen? How should we paginate a long form, so that no one screen entails endless scrolling? These design decisions matter. Making them wisely requires carefully considering the user and their environment. The video and article below will show you how to do just that.

Questions, or items, are the building blocks of your form. Each item is a container for exactly one value, entered by the researcher or participant interacting with your form (or computed by your system from these entries). That value might be:

• a number,
• one or more selections from an array of choices,
• one or more regions of an image,
• a word, phrase, or sentence typed by the user
• an uploaded document or media file,
• or even an electronically drawn sketch or signature.

“Please answer the following three questions if you answered ‘yes’ above.”

Instructions like the above are common on paper forms. A biological male, for example, won’t have a history of pregnancy. Asking him questions on this topic wastes his time, contributes to survey fatigue, and makes him more likely to abandon the form. When a users is forced to chart their own way through a form, the chances of missing a critical question increase. Meanwhile, some portions of your forms will be destined for irrelevance, which is a waste of paper and an encumbrance on the data compiler responsible for sifting through completed and skipped boxes.

Enter electronic case forms with skip logic. As with scores and calculations, skip logic takes advantage of the digital computer’s biggest strength: it’s ability to compute. Here, instead of summing or dividing values, the form evaluates the truth of a logical expression. Did the user either select ‘Yes’ for item one or check the box for ‘B’ on item two? Did she include a cancer diagnosis on last month’s medical history form? (Variables in skip conditions can range over multiple forms.) Form logic can deduce the answer instantly, and behave differently depending on what that answer is: showing or hiding an additional item, further instructing the coordinator or participant, or alerting the safety officer. The results? A better user experience, cleaner data capture, and no wasted screen space!