k
Records for Life: visualizations designed to collect (better) data

It should come as no surprise that we spend a lot of time geeking out over data. Unless we’re busy watching movies, you’ll find us exploring existing datasets, and working towards a clear and compelling visual representation of the stories we find inside. Reimagining the child health record as a part of last year’s Records for Life contest offered an exciting opportunity to apply those same design concepts to the input mechanisms themselves — both digital and analog — in order to increase the volume and accuracy of global health data.

The weight-for-age chart, for example, was not a required component of the contest. We were drawn to it for its ability to engage parents in the immunization process, making them more likely to both participate in — and complete — a vaccination program for their child. Attrition is a big problem in developing nations. In one study only 39% of the children surveyed completed their immunization, if they started at all. We saw the weight-for-age chart as a key way to convert parents into participants in the medical process. A parent who contributes to the vaccination record is a parent who takes care of the card, knows when their child’s next appointment is, and brings the card with them. They also have it readily available should a national health surveyor pay them a visit.

We started by examining existing records, which are often dense, confusing, and assume a level of literacy that some populations just don’t have. Plotting single dots on top of a full color document can also make future scanning and digitization efforts less accurate.

While the visual design might vary widely, these records are built on top of a rigorous dataset provided by the World Health Organization. The dataset contains daily median weight for boys and girls from birth to five years, accurate to four decimal points, as well as four z-scores above and below median.

This is the first stab at pulling real data into this chart. The intent was to compress cues for what is normal or healthy into the chart itself. The data comes from the WHO infant growth standards. There is a set published every few years for both boys and girls, including four standard deviations from the norm.
Our first stab at pulling real data into a Processing sketch. From left to right, there is a bar for each month from birth to five years of age. Each open dot is the median weight for girls plotted on a scale from zero to twenty kilograms. The four closed dots above and below represent z-scores.

The chart above demonstrates an instance where the needs of the parent may be different from those of a doctor or a policymaker. From a medical or research perspective, data gathered at this level of detail is essential. To a parent, however, the difference between a child weighing 15 kilograms and 15.1 kilograms is negligible. Their question is more fundamental: “Is my child healthy?”

boys-vs-girls
In an early iteration, we replaced plotted circles with a column of squares for each month. Each square is a single digit value from zero to forty kilograms. Cells with thicker borders indicate statistically “normal” values (in this case, two z-scores above and below median), while blue and red cells indicate where the normal range was unique for either boys or girls.

We made a conscious choice to simplify the standard weight-for-age chart, enabling parents to use it as a tool to answer that one basic question. Our challenge lay in deciding what range to highlight, and how to calculate it. Since falling exactly inside or outside a certain range isn’t an absolute indication of health, and just getting close to the edge should be cause for alarm, we used an average of male and female values at two z-scores above and below the median to define “normal” — a range that statistically captures about 95% of the population. This allowed us to create a chart that worked for both genders, saving valuable real estate and cutting large-scale production costs. We also decided to use a single knockout color that can be filtered out easily by optical character recognition (OCR) software.

squares-filledout

Asking parents to fill in an exact square for each month proved to be tedious and error prone. We ultimately shifted to values designed to be circled, with structured inputs for more exact decimal weights only at key milestones. Circles only appear around the values in the “normal” range, highlighting when a parent should be concerned.

There is one column for each month of the baby’s life from birth to 60 months (five years old). Potential values for the baby’s weight are listed in each column. Parents or caregivers circle their child’s weight in kilograms for each month. Along the top there is space for decimal weights to be entered at key milestones.
There is one column for each month of a child’s life from birth to five years. Potential values for the baby’s weight are listed in each column. Parents or caregivers circle their child’s weight in kilograms for each month. Along the top there is space for decimal weights to be entered at key milestones.
The weight-for-age chart. This side is geared toward parents, with a revised weight-for- age chart and a section for recording addresses and notes.
The weight-for-age chart in the larger context of our entry.

For more information check out the documentation of our final contest entry, as well as the original Records for Life brief.

All weight-for-age data was sourced from the  World Health Organization, and handled according to their published standards.

Founded in 2010 by Ben Fry, Fathom Information Design works with clients to understand complex data through interactive tools and software for mobile devices, the web, and large format installations. Out of its studio in Boston, Fathom partners with Fortune 500s and non-profit organizations across sectors, including health care, education, financial services, media, technology, and consumer products.

How can we help? hello@fathom.info.