In the Overview-by-Category design above, a summary of the patient’s EHR data is displayed in a single screen view, organized by category (CC and History of Present Illness, Previous Assessments and Plans, Allergies, and so forth). Each category of data is presented in a separate pane or table.

These mockups present the EHR data for an elderly woman with glaucoma in her right eye. In constructing them, I used exactly the same patient database I used for the Snapshot-in-Time mockups in my last post.

The rows within the tables contain data from encounters on different dates or display the onset and end dates associated with events.

The tables tend to take up a lot of screen real estate because they are designed to display both present and past information and because the fields within them can contain redundant, overly-detailed, or null data.As a result, the design shown here, based on a widely-used EHR, requires you to scroll or page down (see blue arrows) just to view the lower half of the overview screen.

As you scroll or page down, the information in the upper half of the screen disappears from view. Hence, you have to use working memory to keep that information in mind, as opposed to retrieving it with a glance. Even with paging down, this overview screen omits four data elements displayed in the Snapshot-in-Time design (the visual field, the description of the optic disc, the family history, and the social history).

Suppose you notice that this patient’s intraocular pressure in the right eye (OD) was extremely high on 5/27/2012 (green arrow) and you want to make sense of the clinical situation at that point in time.

First you have to remember the date 5/27/2012 and then visually scan each of the other tables to find rows with a match (green arrows). In the top two tables, however, the complete entry for 5/27/2012 is not visible without scrolling.

For these top two tables, you need to use the scroll bars (blue arrows) to display the full 5/27/2012 entry. In doing so, however, you have shifted the position of the 5/27/2012 data to the top of each table, interfering with your ability to keep track of it visually by its screen location.

When you scroll down to the bottom half of the screen, the task of keeping track of what happened on or around 5/27/2012 becomes even more difficult. After scrolling down within the Medications pane, you see that the status of the glaucoma drop Alphagan changed on 3/05/2012 and the status of Lumigan changed on 5/28/2012. You need to do a quick calculation to figure out that the patient was off Alphagan but still on Lumigan as of 5/27/2012. But unlike the Snapshot-in-Time design, there is no place in this design for the most important data field – the one noting that, in fact, she was not taking Lumigan on that date.

On looking over the Problem List and the Ocular Procedure History tables, you see that a new diagnosis of depression was added on 5/27/2012 and that the patient had glaucoma surgery on 5/28/2012. While you presume that all these events are inter-related, you can’t know for sure because of the fragmented way the information is presented.

So in theory, the Overview-by-Category design allows you to reconstruct the patient’s state of health at a past time. In practice, it’s difficult because of the cognitive effort (green arrows) and mouse/keystroke effort (blue arrows) required. In my opinion, the Overview by Category design is useful mostly for seeing the present state of a patient’s health or for scanning the tables for out-of-range values.

Many EHRs based on this design do provide an expanded or maximized view for some of the data categories.In particular, many EHRs provide an expanded view of the Assessments and Plans pane. By clicking on an ‘expand’ button, the user can . . .

. . . navigate to a new screen. The screen above displays, as a date-sorted list, the full Assessment and Plan data from previous encounters. The question is whether an expanded view of a single category of data is a useful interface design.

For me, trying to comprehend a patient’s story by viewing a single category of data over time is a little like trying to solve a Sudoku puzzle. Sometimes it’s easy and sometimes it’s difficult or impossible, but in either case, doing so requires cognitive effort that could be better spent on patient care issues.

It’s interesting to note that both the Overview-by-Category design (left) and the Snapshot-in-Time design (right) use exactly the same patient database, down to the level of individual data fields. The Overview-by-Category design, however, requires us to make sense of temporal information using relatively slow, cognitive processing. In contrast, The Snapshot-in-Time design allows us to comprehend the same information using our very fast, high-bandwidth visual processing system.

Perhaps because of the cognitive burden imposed by the Overview-by-Category design (shown above), most EHRs that employ it also provide a workaround solution. Unfortunately, the workaround is non-interactive, not organized by screen location, and is of exceeding low data density. More on this in my next post . . .