Our colleagues at the University of Maryland Human-Computer Interaction Lab have produced a dramatically effective prototype for medication reconciliation. It is amazingly effective, and gets better with each revision (I'm aware of three versions).

What is medication reconciliation?

That's when a healthcare provider has to compare two versions of your medication list. Say you go see your physician, who gives you a printed copy of your medication list as it was the last time you visited them. Now, you compare it to your personal list (or sack of bottles) of medicine. Do they match? If not, what's missing, what's extra, or what has changed?

If you think that sounds easy, you might think otherwise if you happen to be taking a dozen different medications. It's not that far fetched if you have the big 4 (diabetes, high blood pressure, high cholesterol, and obesity), and then toss in a couple more problems (depression, arthritis, sexual disorders). It's easy to rack up 1-3 medicines per problem.

Watch this short video to see what reconciliation involves. Dr. Catherine Plaisant narrates.

What's the big deal?

When I show this to physicians and nurses who have to do this job manually every day, they are amazed and impressed, and they want it NOW in their own electronic health record software!

Here are some features that make it so effective:

  • Animation: The logic becomes transparent
  • Proximity: Like items merge, unlike items move farther apart
  • Alignment: Columns convey meaning, and condensing adds visual efficiency
  • Color: Meaningfully employed. Green is ready to go, gray is retired to the sidelines.
  • Cognitive effort reduced: Software does the matching, rearranging and condensing, then proposes "near matches" for human adjudication.
  • Highlight differences: The text that doesn't match in two items is highlighted, adding efficiency, accuracy, and safety.
I used to get quality reports once a year, then once a quarter. They were long, opaque, boring, and too detailed to digest. I was usually looking at them when I was too tired (at the end of a long day) and away from the battlefield. As a result, nothing much changed.

So, our team decided to provide "just in time" quality feedback to physicians at the point of care, and only for diabetes, and only for 8 quality indicators (there are dozens competing for my attention). The hope was that by giving feedback as the physician was about to see the patient, then she could take action and address the issues of concern. Here's what we built:

diabetes dashboard
Fig 1. Diabetes Dashboard

Here's a closer view of just the bottom of the dashboard showing the Quality Performance Indicators (back then, the Medicare Quality Program was called "PQRI"):
quality panel of Diabetes Dashboard
Fig. 2 The "quality panel" of the Diabetes Dashboard

I call the little red, gray, and white circles "idiot lights". A more socially acceptable term is "traffic lights". They alert the physician to the actionable items for the task at hand: "Change the medications or diet to lower the blood sugar, order the cholesterol tests and annual urine micro-albumin test, and send the patient to the eye doctor."

Does this approach work?
Yes and no.

It is much easier to see what needs to be done. The effort to navigate around to find these 8 items used to take 60 clicks and about 6 minutes to find all 8 measures in our EHR. With the dashboard, it takes 6 clicks and a minute or two. That's a huge gain in efficiency and reduction in cognitive load. It's also safer and more accurate, because, frankly, most physicians would stop looking for that last item or two (the foot exam and eye exam are hardest to find) before wasting the the whole 6 minutes.

Do physicians improve their quality scores by making this more available?
Not necessarily. It's not a required view, and it's on page 2. If my nurse prints it out, circles the items needing attention, and thrusts it in my face (we are a finely-tuned team), then things happen. Otherwise, the 15 other details may get in the way. Information helps, but system processes need to change to get results.
AuthorJeff Belden MD
I've been involved in numerous conversations about medication lists that our healthcare organizations give to patients, and meaningful use rules require the lists. I used to think it was a hopeless cause to get the picture of the pill your pharmacist gave you at your last refill into your personal medication list.

I am not so hopeless, but I remain sanguine. The incentives aren't aligned yet among all the stakeholders. The data doesn't flow freely. It's a rare patient that would use their smartphone to photograph their pills (good lighting and backgrounds are hard!) to include them in their Personal Health Record (PHR), if they are one of the rare people who maintain a PHR.

So, to give you a taste of the challenges, here is a short video showing the different colors and shapes of one single generically available pill: lisinopril. I captured it from ePocrates, which is a wonderful tool for providers.

If it's a brand name drug (for example, Crestor), getting a picture is far easier.

There is a code called the NDC code that tells the pharmacist which exact generic version of your lisinopril you are taking, but your doctor doesn't know (or care, generally) which NDC code is your particular lisinopril. But as we (patients, nurses, doctors, and pharmacists) start coming to expect the pill pictures as part of our conversations, then the NDC code sharing will become more important.

It's in our future, but not our present.
AuthorJeff Belden MD

Clay Shirkey gave a talk at Web 2.0 Expo in NY  a while back titled "It's Not Information Overload. It's Filter Failure". He challenges the idea that we've got information overload problems, and he was mostly talking about media and the web. It applies in our healthcare lives as well. It is not so much information overload as a series of filter failures. Our systems for managing information abundance are swamped by the amount and growth of data that healthcare providers must manage.

Here's the presentation.

Video (23:50)

AuthorJeff Belden MD

Researchers at the University of Wisconsin recently published a conceptual article on Information Chaos titled "Information Chaos in Primary Care: Implications for Physician Performance and Patient Safety" (J Am Board Fam Med, Nov-Dec 2011, 24:6, 745-751).


Figure from the article at bit.ly/InfoChaos

I had never heard the concept of "Information Scatter" articulated before, but it resonated strongly with my experience as a family physician using a variety of EMRs over the past decade.

I recently did a post on using Information Dashboards. Think of a dashboard serving the same purpose as the dashboard in your car. It gives you the critical information you need for the task at hand.

  • When you start the car, you get the messages like "time to service your car" or "hey! check your engine".
  • When you are driving, you get speed, fuel status, turn signal indicators, bright light indicators, etc. 
    • You don't have to navigate somewhere else for additional information to do the task of driving.
    • You don't get unnecessary information that is not actionable during the act of driving.

Dashboards are well suited to reducing information scatter, and they help manage information overload when skillfully designed. A key feature that is often overlooked is to pare away all unnecessary data elements (removing words that don't add value).  For example, "lisinopril 10 mg daily", and not "lisinopril 10 mg 1 tablet oral daily".

AuthorJeff Belden MD