Applying research ideas to improve patient and community outcomes
The Behavioral Economics (BE) Core advises on behavioral economics, implementation sciences, and cost effectiveness analyses to translate research findings into clinical practice.
Behavioral economics explores how people’s actions and biases influence their decisions. Tailoring decision environments can encourage, or “nudge”, people towards making wiser and healthier choices without taking away their freedom of choice.
Implementation science studies the optimal logistics of delivering a given intervention and advances strategies that facilitate the uptake of research-based interventions or best practices. In this way, implementation science helps translate ideas into outcomes by identifying, addressing, and overcoming system barriers.
Cost-effectiveness analyses aim to categorize the relationship between healthcare costs and health outcomes of an intervention or idea.
The Behavioral Economics Core is supported by the Center for Health Outcomes and Population Research (NIGMS CoBRE P20GM121341).
Questions we can help to answers:
- How can I operationalize results from my study in a real-world or clinical setting?
- How can I maximize patient/participant enrollment and participation?
- How should I communicate with patients/participants?
- How can I nudge patients/participants to make healthier decisions without removing their freedom of choice?
- How can I measure the cost-effectiveness of my intervention?
Lang C, Schaap R, Sang H, Weber TL, Weber GA. (in press). Description and Evaluation of a Multilevel Intervention for Improving HPV Vaccination Rates in a Rural South Dakota Clinic. South Dakota Medicine.
Weber TL, Selya A, Wakschlag LS, Dierker L, Rose JS, Hedeker D, Mermelstein RJ. (2021). The effect of maternal smoking on offspring smoking is unrelated to heritable personality traits or initial subjective experiences. Nicotine and Tobacco Research. PMID: 33912956
Selya A, Johnson EL, Weber TL, Russo J, Stansbury C, Anshutz D, Griese E, Hsu B. (2020). Smoking is associated with a higher risk of unplanned medical visits among adult patients with diabetes, using retrospective electronic medical record data from 2014 to 2016. BMC Health Serv Res. May 6;20(1):383. doi: 10.1186/s12913-020-05277-4. PMID: 32375742; PMCID: PMC7204008.
Selya, A.S., Anshutz, D, Griese, E, Weber, TL, Hsu, B, Ward, C. (2021). Predicting unplanned medical visits among patients with diabetes: Translation from machine learning to clinical implementation. BMC Medical Informatics and Decision Making, Mar 31;21(1):111. PMID: 33789660, PMCID: PMC8011134
Meet the Team
Emily Griese, PhD
Dr. Griese's research works to uncover heterogeneity in developmental trajectories from childhood to early adolescence, focusing primarily on sources of resilience among at-risk youth. She further has extensive expertise in advanced longitudinal data analysis including latent growth mixture modeling and various other Structural Equation Modeling (SEM) techniques.
Tiffany Johnson, RN
Quality PartnerTiffany holds a Bachelor of Science in nursing with a minor in biomedical sciences. She is an RN with experience in ED and trauma nursing, supervising and nurse leadership in ambulatory settings and was previously a quality improvement advisor. Tiffany works with clinical staff to identify areas where behavioral economics methodologies would improve patient care and quality outcomes.
Sanford Health News
Sanford Research scientists hope to determine how neurons develop inside the brain
Providers, policymakers talk expanding access to maternal health care
Classes & Events
Tue 10/03/23 5:30 PM - Tue 10/03/23 7:00 PM
Sanford PROMISE Community Lab
Mon 10/09/23 9:30 AM - Mon 10/09/23 4:00 AM
Sanford PROMISE Community Lab