Create a medication-tracking solution for inpatient hospital nurses.
We interviewed registered nurses and nursing students. We discovered that tracking medication administration is slow and inefficient, leading nurses to look for shortcuts that may result in mistakes. The data entry involved in medication tracking also takes away from the nurse's primary duty: caring for patients.
We created an as-is journey map of the process of administering medication, identifying design opportunities at each phase of the journey. This, along with research insights, helped us to recognize the core problem. We then asked ourselves: how might we leverage technology to ensure safeguards while allowing a nurse to focus on the patient’s care?
Taking a look at exemplars, we considered ubiquitous computing as a means of more seamlessly integrating data collection into a nurse's current workflow. We considered what artifacts nurses currently interact with when administering medications. We identified the patient's wristband as a tool we could leverage in our solution since nurses already check the band to confirm a patient's identity before giving medication.
An IoT-connected hospital bracelet that pulls patient data to (1) ensure patients are being given the correct medications and (2) automatically track medications that a nurse administers. We created a paper prototype, which we used to conduct usability testing. We iterated based on testing results before presenting a mockup of our final concept.
This project was completed as part of the course Rapid Design for Slow Change, instructed by Professor Marty Siegel at Indiana University. This prompt was provided by Advisory Board, a medical technology consultancy. They acted as our client for this project.
This project was completed as part of the course Rapid Design for Slow Change, instructed by Professor Marty Siegel at Indiana University. This prompt was provided by Clutch, an experience strategy and design agency. They acted as our client for this project.
Selected by Advisory Board as winning project for this design challenge.
5 day sprint
User Journey Map
Paper, pen, markers
To get a better understanding of the problem space, we interviewed 2 practicing nurses, 4 nursing students at Indiana University’s School of Nursing and a behavior health technician, all of whom had familiarity with the process of administering and tracking medication in a clinical environment.
My teammate Emily interviews a registered nurse and professor at IU's School of Nursing
Some insights we gathered from our interviews included:
We organized data from our research into a journey map that represents the current processes nurses follow in giving their patients medication.
Following our interviews, we parsed out some key problems and insights and wrote them out on post-it notes in the form of “How might we…?” questions. Some of these included:
We then clustered these into more general problem areas to identify larger patterns.
Based on the problem presented by Advisory Board, we recognized that medication tracking and patient/provider identification should be included as part of the core design. We also determined that finding ways to increase efficiency and integrate existing workflows into the design would allow us to address critical pain points identified in our research.
What does "efficiency and integration" mean? From talking to nurses, we realized that many of the tasks involved in medication tracking require them to divert their attention from providing patient-centered care. For example, nurses have to carry around a large and cumbersome computer on wheels (“COW”), slowing them down and requiring them to view and confirm data on a screen. We decided to focus on finding ways to integrate medication tracking into the flow of patient care, while still maintaining safeguards that provide nurses with peace of mind.
As they exist, EHR systems remove nurses’ attention away from their patient and onto the computer screen. Traditional approaches to incorporating technology into hospitals require trade-offs to patient-centered care. Our challenge was to see if we could leverage technology to ensure safeguards while allowing the nurse to focus on the patient’s care.
We can determine the weather in the morning while we’re getting ready by asking Alexa, we can enter our homes without fumbling for our keys, we can pay for toll roads without stopping…
...so why can’t nurses care for their patients while data is inputted automatically?
We looked at exemplars of ubiquitous computing (the integration of computers throughout our surrounding environments) and technology that the user can engage with without disrupting their current routine. This exemplar collection helped us to look at various uses of technology to determine what we may be able to leverage and incorporate in our design.
Looking at these examples, we thought of ways these technologies could be incorporated into a nurse’s daily routine while facilitating more personal interactions with patients rather than the nurse’s focus being split between caring for the patient and data entry.
From here, we were able to create concept sketches that incorporated various uses of ubiquitous computing, all of which attempted to increase the face time between nurses and patients.
Some of these concepts included:
With concept sketches in hand, we presented our ideas to nursing students at Indiana University to get feedback on our design direction. We learned that a daily worry was providing a patient the wrong medication. We received positive feedback on our concepts that provided additional safeguards to ensure correct medications were being given.
To guide our design process, we utilized personas representing characteristics of the nurses with whom we spoke.
Occupation: Pediatric ER Nurse
Location: New York, NY
After concept testing, we created a paper prototype to get feedback on our design direction.
We recruited 5 participants to try our prototype. We asked them to imagine that they were a nurse administering a medication to their patient and presented them with our band. We presented three possible scenarios:
After briefing them, we simulated the indicator light showing one of three colors and played the corresponding audio tone. We asked them which of the three scenarios they thought was indicated by each light/tone combination.
5/5 subjects recognized the error tone and color
5/5 subjects recognized green as an already-prescribed medication that is OK to give to the patient
Only 1/5 subjects recognized the difference between the new medication tone and the already-prescribed medication tone
When asked, 4/5 subjects recommended using yellow as the visual indicator for a new medication, as they felt it better signaled caution
Participants had a difficult time distinguishing between the meanings of the green and blue lights. When they were shown the blue light and exposed to the “new medication” tone prior to the green light and the “correct medication” tone, it was unclear to them which represented which.
At first, we were hesitant about the possible associations that would result from the pairing of green, yellow, and red. However, based on our testing results, we swapped blue for yellow to better conform to people’s expectations. After all, this fits more with existing models: yellow is associated with caution, and when a nurse administers a new medication for the first time they must take extra precautions.
“It’s like a traffic light…when you see yellow, you take caution.”
— Testing participant, commenting on new medication light
Our final design, MedWatch, can be implemented with existing EHR systems by connecting wirelessly. As the nurse interacts with MedWatch, information is automatically updated in a patient’s eMAR, eliminating the need for the nurse to manually input this data.
Michael has just retrieved the medications Billy is due to receive. Among these three medications is a new antibiotic ordered by the doctor.
On his way to Billy’s room, Michael is stopped by Jane, a social worker, who is inquiring about another patient’s discharge. He talks to Jane for a few minutes before continuing on to Billy.
Michael enters Billy’s room. He verifies his identity on Billy’s MedWatch by placing his finger on the fingerprint scanner. He then confirms Billy’s identity by asking for Billy’s name and date of birth, matching it against what’s written on the band’s display.
Next, Michael scans each of the medications by holding them up to the MedWatch one by one. For the first two medication packets, he hears a tone and sees a green light, confirming these two medications are due for Billy at this time and that they have been verified in the system.
For the third medication, the MedWatch emits a different tone and displays a yellow light. Michael, who had almost forgotten about the new antibiotic during his conversation with Jane, is reminded to provide Billy with a more detailed explanation of what the medication is, including its potential side effects.
MedWatch automates many of the clerical duties performed by a nurse in administering and tracking medication. Additionally, it takes the task of scanning and confirming medication from their computer on wheels and incorporates it into the interaction between the patient and nurse by means of the MedWatch. Meanwhile, the same safeguards that are present in the current EHR system, including patient and provider authentication and verification that the correct medication is being given, are still preserved. MedWatch accomplishes our goal of using technology to facilitate patient-centered care and reducing the amount of attention a nurse must devote to their computer screen.
In Advisory Board's critique of our solution, they pointed out a few potential problems. They felt that green-red color blindness may still be an issue in spite of the tones in cases where someone had difficulty differentiating the tones. Based on this, I created a series of high fidelity mockups.
Here, a message accompanies each warning. This helps new nurses to understand the light/auditory cues and provides more specific information on problems when they arise. The light indicators are also staggered so that they also differ spatially, assisting individuals with red-green colorblindness.
For this problem, we constrained our design to how ubiquitous computing could improve the way nurses track the administration of medication. We realize that our solution alone does not eliminate the nurse’s reliance on their computer in all segments of the process of administering medication, including verifying the accuracy of the dosage instructions (especially for IV routes) and recording additional notes. However, we imagine MedWatch being part of a larger system in which ubiquitous computing technologies are deeply integrated into nurses’ workflows with the intention of facilitating more face-to-face, natural interactions between nurses and their patients throughout— all without compromising a focus on their patients’ safety.
Of all the design projects I have completed so far, this is my favorite in terms of process. Uncertainty is scary. Especially when you are working within such a short time constraint, it is easy to jump straight to solutions in your head without a clear rationale.
Here, we let our insights from research guide us to our concept. Once we arrived at a general concept for the solution (ubiquitous computing), we thought about a variety of ways that could be implemented in medication tracking before we settled on one. And, when we did make assumptions in our design, we validated them through testing. All of this resulted in a more user-centered design.
There were definitely a few unclosed loops in our design that we considered but did not have the chance to address due to time constraints. For example, were there any sanitary concerns with the bands? Would nurses have difficulty accessing the band for certain patients? Would we need a different means of authentication on the device if nurses are wearing gloves?
When we validated our concepts with nursing students, these problems didn’t really come up. I imagine a big part of this was that it was difficult to envision how the solution would work out of context. Moving forward, it would be important to try a prototype out with experienced nurses in a hospital to identify issues with our design that might not arise during an interview.
Copyright © 2018 Brian O'Connor