Medical errors are one of the leading causes of death in the United States.
Many studies have established a correlation between healthcare worker exhaustion and medical errors that impact both patient safety and worker safety. Fatigue leads to cognitive defects, especially if it is due to sleep deprivation.
A key finding:
Physicians who worked traditional schedules with recurrent 24 hour shifts reported making 300% more fatigue-related preventable adverse events that led to a patient’s death and experienced 61% more sharp injuries (Joint Commission on Quality and Patient Safety 2007).
We aim to create a solution that reduces patient deaths due to healthcare worker fatigue, increase patient safety and quality of care, and decrease the costs incurred by hospitals due to these errors.
We decided to design an application to determine if a healthcare worker is in the state of mind to handle major medical decisions.
Test an individual's reaction time
Compare it to their previously established basedline
Provide a suggestion regarding the individual's mental state and ability to make decisions involving patients
How do we best test cognitive fatigue?
We decided to measure cognitive fatigue by relating reaction time to the ability to handle highly cognitive tasks. Simple tasks, like typing, would not disrupt the workflow of a healthcare worker's schedule.
To do this, the application consists of two tests: a tap test and a tilt test.
For the tilt test (middle): The application will display arrows pointing to each edge of the phone and a circle in the middle, as shown below. The user will either be prompted to tilt the device in the direction of the arrow or to hold the device still. The purpose of these tests is to validate cognitive ability.
For the tap test (right): Using the volume buttons on the phone, an individual will react to commands that appear on the screen prompting the user to hit the top or bottom button.
These tests introduce a task-switching variable, since switching between different tasks under sleep deprivation is more difficult. The two tests also offer a more extensive measurement of cognitive fatigue than either of the tests would provide on their own.
Based on the test results, they will receive one of the three results:
1. Left: "You're good to go!"
2. Middle: "Looks like you're getting tired."
3. Right: "Looks like you're fatigued."
I used icons and colors that would quickly let the individual know of their results. For accessibility, the results would be sent to their supervisor to notify them of their state.
We wanted to ensure that there was an onboarding process in place when a healthcare worker is fatigued. The hospital inevitably holds a stressful environment, so a healthcare worker may not directly address their fatigue due to a variety of reasons, including: a shortage of doctors on staff, assisting their patients, and more. However, we want to prioritize healthcare workers' wellbeing as much as they care for their patients.
Some features we thought would be helpful include:
1. Left: A timer for a 20-minute nap when set, will notify their coworkers that they will be taking a nap to address their fatigue and practicing self-care.
2. Middle: Explanation of how Reax works and the tests' baselines of fatigue, possible fatigue, not fatigue.
3. Right: A profile to keep track of their test results along with their contact information for accessibility.
Through Reax, we hope to decrease medical errors and increase patient safety. Ultimately, we want to change the culture in the healthcare profession to prioritize the well-being of its healthcare workers.
Thank you to MedHacks for giving us a platform to address patient safety, the judging panel at MedHacks for hearing our solution and awarding us the Wolfram Award, Johns Hopkins University for hosting our team, and to the doctors and medical students, Dr. Nicholas Durr, and researchers at NeuroQWERTY, Elsevier, and TMC BioDesign for offering feedback that helped shape our solution.