Behavioral Insights Team
Many of the most pressing challenges in healthcare — those that are hard to solve yet critical for improving patient outcomes and reducing costs — involve human behavior. Almost every healthcare intervention requires behavior change. But getting people to change their behavior is not always easy.
What is a Nudge Unit?
Geisinger’s Behavioral Insights Team (BIT), also known as the Nudge Unit, uses insights from psychological science and behavioral economics to help our patients, providers and staff improve their decisions. “Nudges” are small changes in “choice architecture” — the way in which available choices are presented to decision-makers — that make choices that improve health outcomes more likely while not restricting people from making whatever decision they prefer. Nudges should be transparent, easy to opt out of or ignore, and aligned with the welfare of the person being nudged. Typical nudges include:
- Setting sensible default options so that failing to make a decision automatically leads to the best outcome for most people
- Reordering choices so that the best options are seen first
- Describing options in a way that increases the likelihood of better choices
- Presenting timely reminders that provide critical information when it will be most useful to the decision-maker
Why nudge?
Nudges do not eliminate any choices or substantially change the costs or benefits of choices for the decision-maker. They make better choices easier, but not mandatory, so they preserve freedom while helping to improve outcomes for our patients, members, and employees, and for the Geisinger enterprise.
The BIT designs, implements, and rigorously evaluates nudges and other behavioral interventions at Geisinger. We also investigate attitudes and reactions to nudges and advance the science of health behavior change.
How we work:
- Collaborating with partners across the health system and health plan as well as outside of Geisinger to diagnose the nature, extent and likely cause(s) of suboptimal behaviors
- Designing and implementing interventions
- Conducting A/B tests (pragmatic randomized controlled trials, also known as randomized quality improvement trials) to quickly and reliably determine which approaches yield the best outcomes
- Supporting teams in implementing successful interventions as standards of care at Geisinger
We measure our success via:
- Greater engagement in healthy behaviors
- Improved clinical outcomes
- Lower health care costs and fewer claims
- Positive return on investment for the health system
We also collaborate on writing grants to support this and similar work with internal and external researchers.
Interested in working with us?
Just email us at: behavioralinsightsteam@geisinger.edu
Example projects
Below are just a few projects the Behavioral Insights Team has worked on:
- Machine learning-based risk nudges: Evaluate whether messages to patients at high risk for flu related complications increase flu shots, and whether messages are differently effective when patients are told (vs. not told) that their risk was determined by a computer algorithm
- AI-informed flu shot nudge selection: Learn whether text-message nudges determined by AI to be best for each patient’s demographic and health profile are more effective than non-personalized nudges
- Shingles vaccination outreach: Test whether text message nudges within three days of vaccine-eligible primary care appointments increase first-dose shingles vaccination compared to no-message controls, and evaluate how effectiveness varies by message number and content
- Flu vaccination mega study 1: Evaluate the impact of 19 text message pre-appointment flu shot reminders across Geisinger and another health system
- Flu vaccination mega study 2: Compare the effectiveness of 22 different text messages for increasing flu vaccination for patients at a large pharmacy chain
- Test whether text messages to patients who were discharged from a low-acuity ED visit are effective at reducing subsequent ED visits
- Evaluate whether sending text messages after a high-acuity ED visit increases follow-up appointment scheduling or reduces subsequent ED visits
- Assess whether nudging nurses to contact patients following outpatient visits reduces subsequent ED visits
- Test different EHR alert configurations to determine the most effective way to increase pediatric lipid screen orders and completions (randomizing patients to alerts)
- Evaluate email timing strategies to increase enrollment in Geisinger’s online patient portal (MyGeisinger)
- Compare email content approaches (loss framing, social norms, testimonials) to increase enrollment in the employee wellness program (myHealth Rewards)
- Evaluate variations in email content to increase use of Geisinger’s mail-order and retail pharmacies, which save money for patients and the health system
Who we are:
Michelle Meyer, PhD, JD – Founding BIT faculty co-director; Associate Professor and Chair, Department of Bioethics and Decision Sciences
Christopher Chabris, PhD – Founding BIT faculty co-director; Professor and Director of Decision Sciences, Department of Bioethics and Decision Sciences
Gail Rosenbaum, PhD – BIT Program Director
Sasha Brietzke, PhD – BIT Staff Scientist
Lena Schaefer, PhD – BIT Staff Scientist
Amir Goren, PhD – Director, Geisinger Program Evaluation
Carroll Walter, MA, MPH – Administrative Director, Department of Bioethics and Decision Sciences
Jen Ludwin, MS, MPH – BIT/GPE Project Manager
Geisinger departments and teams we frequently collaborate with
Family Medicine
Emergency Medicine
Internal Medicine
Infectious Disease
Nephrology
Informatics
Marketing
Analytics
We have a long-term partnership with the National Bureau of Economic Research (NBER) in the NBER Roybal Center for Behavior Change in Health, one of 15 National Institute on Aging (NIA)-funded Roybal Centers.
