Healthcare Innovation Bridging Research, Informatics & Design Lab Research
Led by Devin Mann, MD, MS, the Healthcare Innovation Bridging Research, Informatics, and Design (HiBRID) Lab works independently as well as collaboratively with research and operational teams across NYU Langone to improve digital systems that aid healthcare delivery and research. We help create health applications, electronic health record (EHR) enhancements, and clinical decision support tools.
Our Research Methods
HiBRID Lab combines research, informatics, and design to build, implement, and disseminate new digital tools that can improve the delivery and experience of healthcare. Our projects leverage novel user-centered, iterative design methods, machine learning, and usability testing simulations to build tools that seek to change patient and provider behaviors.
Digital Health Delivery and Grant-Funded Work
In collaboration with the Department of Population Health’s Division of Biostatistics and sponsored by the National Institutes of Health, our team is researching how to integrate behavioral economics approaches into EHR systems to prompt providers to follow Choosing Wisely® guidelines when treating older adults with diabetes. We are also developing smarter clinical decision support tools using predictive analytics, integrating a digital diabetes prevention program into the EHR system, and designing user-centered clinical decision support tools to reduce inappropriate prescribing of antibiotics.
HiBRID Lab is also teaming up with the Huntsman Cancer Institute (HCI) at the University of Utah to provide HCI with digital health technology support. Our role involves identifying and streamlining access to genetic counseling services for people from minority racial and ethnic groups and those living in rural areas. This work is funded through a prestigious grant from the National Cancer Institute’s Cancer Moonshot initiative.
Our team is involved in implementing digital innovations throughout the NYU Langone system.
HiBRID Lab, in collaboration with the Predictive Analytics Unit, is examining a novel method to reduce provider alert fatigue using machine learning to improve adoption of best practice alerts for vaccine prescription.
Our team is also engaged in Medical Center Information Technology (MCIT)–focused endeavors related to EHR innovation. We are working to improve the patient and provider experiences in managing chronic conditions by integrating remote patient monitoring data and improving data visualization, as well as exploring opportunities to reimagine the digital experience of the future for clinicians.
We provide expertise in user-centered design and design thinking to research teams throughout NYU Langone looking to build useful, useable digital tools. For example, we worked with a research team to build a user-centered decision support tool as part of an intervention aimed at preventing stomach cancer in Chinese American immigrants. As part of a grant-funded project, our team supported the user-centered adaptation of a clinical decision support intervention to help emergency department clinicians build their palliative care skills.