Areas of focus
At Mayo Clinic's campus in Phoenix/Scottsdale, Arizona, health care delivery researchers operationalize the center's mission by focusing on three main guiding principles:
- Supporting methodologically rigorous science and health care delivery projects likely to have an immediate impact on Mayo Clinic's clinical practice
- Collaborating across Mayo Clinic and with other scientific partners, including Arizona State University (ASU)
- Providing education and competitively awarded funding opportunities within Mayo Clinic to advance the science of health care delivery. Opportunities include:
- Acceleration grant. The Arizona team of the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery and ASU Office of Knowledge Enterprise Development together provide one year of funding to an established Mayo Clinic-ASU collaborative team that demonstrates a high likelihood of transforming the Mayo Clinic practice and successfully obtaining extramural funding.
- Incubator grants in health care delivery science. Seed grants to support grassroots scientific ideas and encourage new health care delivery science partnerships between faculty at Mayo Clinic's campus in Phoenix/Scottsdale, Arizona, and external partners, including ASU.
The Mayo Clinic Kern Center for the Science of Health Care Delivery's Arizona team includes a scientific review panel made up of faculty members who are methodologically trained in various domains of health care delivery science. Their areas of expertise include:
- Comparative effectiveness research
- Health services research
- Precision medicine
- Quality of care
- Secondary database analysis
- Surgical outcomes
Scientific review panel members reflect a cross section of Mayo Clinic's clinical practice and research in Arizona. Many members currently hold, or have held, extramural federal funding in health care delivery science. The scientific review panel provides peer review of all research project applications to ensure the highest quality of science and potential impact for clinical practice.
Data-Driven Behavioral Change Individualized Interventions to Improve Type 1 Diabetes Treatment Adherence
The study team hypothesizes that by addressing patient-specific barriers to optimal type 1 diabetes self-management adherence, glycemic control can be improved.
The study is designed to address patient barriers to optimal self-management adherence by reviewing patient insulin pump data, continuous glucose monitoring data and data from a smartphone application created by the investigative team. The team conducts data-driven, individualized interventions and evaluates the impact of the interventions on glycemic control.
Overall, the study aims to permit incorporation of self-care data into the design and delivery of individualized, educational interventions to improve diabetes control.
Short Stay Observation Unit
Mayo Clinic's Clinical Practice Committee — Arizona endorsed a hospital internal medicine pilot program in 2017 to evaluate a short stay observation unit for patients who do not require hospitalization but are not safe to be discharged from the emergency department. Patients in the short stay observation unit benefit from expedited ancillary services, focused care management and ambulatory procedures.
Outcomes of interest include:
- Average length of stay
- Conversion rate (patients who are hospitalized from the short stay observation unit)
- Revisits and readmissions, monitoring both at 72 hours and two weeks
The outcomes data will be used to assess the impact of the short stay observation unit and to clarify which patients are best suited for this type of observation unit.
Speech Changes as Predictors of Migraine Attack Onset
The project team developed a mobile application that samples people's speech with the goal of determining the accuracy of speech variation to predict oncoming migraine attacks.
Subtle changes in speech sometimes occur in some patients during the pre-attack phase of migraine. These changes might be used in conjunction with other variables — such as language changes, cognitive performance and exposure to migraine attack triggers — for early identification of a migraine attack.
Accurate prediction of migraine attacks would allow for early treatment, an approach that may provide superior outcomes compared with the current standard of care.
A Comprehensive Model of Care for Patients With Low Back Pain
The research team sought to identify areas of bottleneck, weakness and vulnerability in caring for patients with low back pain.
Researchers used industrial and manufacturing engineering principles to model opportunities for improving patient flow. The team then compared proposed alternative models with usual care, with regard to clinical and economic outcomes. Among other advantages, implementation of a smart triage system could result in improved patient access and increased surgical patient assessment.
Past project highlights
Read about previous projects conducted by the Arizona team of the Mayo Clinic Kern Center for the Science of Health Care Delivery.