Catching Zs
Project status
Collaborators
Denise Xu, MD
Laura Stein, MD, MS.Ed
Colleen Peachey, MSN
Charles Bae, MD, MHCI
Chip Chambers
Michael Karamardian
Angela Malinovitch
Michael Buckley, MD
Innovation leads
Funding
Innovation Accelerator Program
Penn Medicine/Optum Labs innovation initiative
Opportunity
For places with so many beds, hospitals are far from restful. Studies show that patients sleep, on average, two fewer hours in the hospital than at home. Clinical care, such as medication administration, vital sign checks, lab draws, and even baths, continues throughout each night, disregarding natural sleep cycles. Nocturnal disruptions prevent patients from actively participating in daytime care, negatively impacting experience and health outcomes and increasing length of stay and readmission rates. Currently, there is no unit-based approach for improving sleep and preventing patient delirium.
Intervention
Catching Zs aims to improve hospital patients’ sleep, starting with neurology inpatients, by targeting the most substantial drivers of poor sleep identified by the project team: 1) clinician-driven interruptions, 2) patient anxiety and discomfort, and 3) the invisibility of poor sleep.
- Minimizing clinician disruptions with “sleep-friendly” default orders: For each hospital patient, there is an associated set of instructions called orders that direct the treatment of that patient. This intervention changes the default orders to a “sleep-friendly” set designed to minimize interruptions at night.
- Reducing patient anxiety with a slate of amenities: Patients are given a “sleep menu” with options intended to support their comfort, build a bedtime routine, and ease anxiety. Sample options include guided meditation, pet therapy, chaplain service, soothing music, earplugs, and blankets.
- Raising the visibility of poor sleep among clinicians with a “sleep data card”: Sleep data, such as duration and number of interruptions and subjective sleep scores, are collected and presented to care teams at rounds the next day.
Impact
The results from pilot studies suggest that Catching Zs interventions can improve both the quantity and quality of sleep. Patients who received the interventions slept 70 percent more than those who didn’t: an average of 7 hours and 20 minutes compared to 4 hours and 20 minutes. In addition, the interventions yielded one-third fewer awakenings, and sleep scores were rated as “good” on average instead of “poor.” Overall, 75 percent of patients participating in the interventions met the expert-recommended six hours of sleep, compared to 25 percent of patients without interventions.
This project is part of our 2021 Innovation Accelerator class. In phase two, the team plans to implement a randomized control trial to rigorously test the interventions in a broader inpatient population. The trial will test refined versions of the original three interventions and two notable additions to help reduce clinician disruptions: a wireless patch for measuring vital signals and a mechanism for needleless blood draws.
Innovation Methods
A day in the life
A day in the life
We put ourselves in patients’ shoes by staying posted outside patient rooms during critical sleep hours. We also spent time shadowing and interviewing staff. These activities helped us learn what kind of disruptions contribute to sleep loss and how often disruptions occur. It also helped us build empathy for the patient's experience.
A day in the life
One of the best ways to learn more about a problem area is to experience it yourself. Immerse yourself in the physical environment of your user.
Do the things they are required to do to gain a firsthand experience of the challenges they face. Completing a day in the life exercise will enable you to uncover actionable insights and build empathy for the people you're hoping to help.
Quantitative data review
Quantitative data review
Quantitative data review
We collected data about patients’ sleep, including durations and number of awakenings per night. These numbers allowed us to evaluate our interventions by comparing sleep length and quality before and after interventions were implemented and benchmark our results against expert guidelines. It was important to gather objective data, so we had each patient wear a Fitbit monitor to track their sleep.
Nudge
Nudge
Nudge
Human decisions and behaviors are heavily influenced by the environment in which they occur.
A nudge is an intervention that gently steers individuals toward a desired action. Nudges change the way choices are presented or information is framed without restricting choice – although some nudges do change available offerings to drive behavior change.
To learn more about this methodology, visit our Nudge Unit page.
Nudge
We noticed that patients were reluctant to choose specific options from the sleep menu, for example, pastoral care, which has shown to be especially effective. Through motivational interviews, we learned that patients tended to avoid these options because they thought it might inconvenience others. So to increase adoption, we adjusted our approach to be prescriptive rather than opt-in for high-impact options when deemed appropriate.