Catching Zs

Improving sleep consolidation for neurology inpatients


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 over the course of 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.


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) provider-driven interruptions, (2) patient anxiety and discomfort, and (3) the invisibility of poor sleep.

  1. 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.
  2. 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.
  3. Raising 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.


The results from pilot studies suggest that these interventions can improve both 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 who had no interventions.

This project is part of our 2021 Innovation Accelerator class. In phase 2, the team plans to implement a randomized control trial to rigorously test the interventions in a broader inpatient population. The trial, scheduled to launch in April 2022, will include refined versions of the original three interventions and two notable additions to help reduce provider disruptions: a wireless patch for measuring vital signals and needleless blood draw.

Phase 2: It does work

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

Dave Resnick, MS.Ed, MPH
Roy Rosin, MBA


Innovation Accelerator Program
Penn Medicine/Optum Labs innovation initiative

Innovation Methods

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.

A day in the life

Team member Dave Resnick put himself in patients’ shoes by staying posted outside patient rooms for weeks. The team also spent time shadowing staff and conducting interviews with both patients and staff. These activities helped us learn which disruptions contribute to sleep loss, track how often disruptions occur, and understand the difficulties that these patients experience.

Quantitative data review
Gathering and analyzing quantitative data - the "what" is happening - can help inform your understanding of the problem space and enable you to establish benchmarks for evaluating solutions.
Quantitative data review

We collected data about patients’ sleep, including duration and number of awakenings per night. These numbers allowed us to evaluate our interventions by comparing sleep length and quality before and after they were implemented and to benchmark our results against expert guidelines. It was important to gather objective data, so we had each patient wear a Fitbit monitor to track sleep.


Human decisions and behaviors are heavily influenced by the environment in which they occur.

A nudge is an intervention that gently steers individuals towards 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 types of nudges like defaults, active choice, financial and social incentives, and more, visit the Nudge Unit website.


We noticed that patients were reluctant to choose certain options from the sleep menu, especially some like pastoral care that have been shown to be higher impact. Through motivational interviews, we learned that patients tended to avoid these options because they thought it might inconvenience others. To increase adoption, we adjusted our approach to be prescriptive rather than opt-in for high-impact options when deemed appropriate.