Adela Grando

Dr. Grando's main research interest is the design and use of Information Technology for Patient Empowerment in Healthcare.

Research Projects

• SHARES: Substance use HeAlth REcord Sharing  (NIDA, 2 R01 NS127170-06) 2023-2027. The focus is to elucidate substance use disorder (SUD) data sharing challenges and the feasibility of automated data segmentation to improve data interoperability and health care for those with SUD.
• Machine Learning Design to Predict and Manage Postprandial Hyperglycemia in Patients with Type 1 Diabetes (Mayo and ASU) 2023-2024. In collaboration with the Mayo Clinic Arizona, Department of Endocrinology, the goal is to use mobile and wearable data to predict type 1 diabetes outcomes.
• Southwest Safety Net Embedded Scientist Training and Research (SSNE-STaR) Center (AHRQ) 2024-2028. Our goal is to help improve the health equity of historically disadvantaged populations with a strong commitment to the needs of Native American, Hispanic, homeless, refugee and other under-served populations by strengthening the capacity of our partner safety net healthcare organizations to generate evidence that informs practice for better health outcomes in under-served populations.
• Reducing health disparities with a culturally-based care model for Medicaid recipients: Spanish language validation for socio-cultural risk assessment (Equality Health Foundation) 2022-2023. The purpose is to validate a Spanish socio-cultural risk assessment tool with 300 Spanish speaker Equality Health patients.

Selected Previous Projects 

• Blockchain Applied Project Research Lab (AZ Blockchain applied Research Center) 2020-2023. The ASU Blockchain Research Lab's mission is to advance the research and development of blockchain-based technologies. The goal was to partner with industry leaders to solve real-world problems. Some of those are in the scope of healthcare.
• My Data Choices, Evaluation of Effective Consent Strategies for Patients with Behavioral Health Conditions (NIMH, R01 MH108992) 2016-2022. The project aimed to: (1) Elicit patient, surrogate and provider perspectives on granular data control, (2) . Design educational material to inform patients and providers about the consequences of sharing/not sharing data, (3) Deploy and pilot test an informed consent management tool that supports granular patient-driven data control, and (4) Understand the ethical, clinical, policy and regulatory implications of implementing granular data control choices
• ROOT- Registry of Operations and Tasks (Mayo Clinic) 2016-2019. Before and after the Mayo Clinic underwent an enterprise-wide conversion to a common EHR, the aims of this project was to capture and document high quality snapshots of EHR workflows, with a focus on surgical workflows at Arizona, Florida and Rochester locations.
• Data-driven behavioral-change education interventions to improve type 1 diabetes treatment adherence  (2018 ASU-Mayo Accelerator grant) 2018. Read Mayo Clinic News, watch ABC15 News and PBS Arizona News. The project aimed to assess patient-specific barriers to optimal self-management control from data collected by patient's devices: iDECIDE self-management tracking mobile app, insulin pump and glucose monitor. The study conducted individualized education interventions that targeted patient's adherence barriers and evaluate their effectiveness in blood glucose control. 
• Patient-centered decision support based on device data (IDECIDE) (R21LM011667) 2014-2016. The goal was designed and pilot test a smartphone app, called iDECIDE, to help individuals with type 2 diabetes to better control their glucose. This was a collaboration with the Mayo Clinic, Arizona.