Adela Grando

Dr. Grando's main research interest is the development of Clinical Decision Support Systems (CDSS) (e.g., what evidence-based treatment is recommended for a patient case?) for clinicians and patients.

She is passionate about Information Technology for Patient Empowerment in Healthcare. She is leading projects focused on building mobile technology to support patient's decision processes. For instance, mobile apps for in-home disease management control and tablet-based electronic systems to educate patients on informed consent processes. 

Research Projects

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 

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 in healthcare, business, finance, economics, mathematics, computer science, and all other areas of potential impact. The goal is 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 (R01 MH108992) 2016-2022

Integrating behavioral (mental health and substance abuse) and physical care by health information exchanges (HIE) opens new questions on data privacy, stigma, and discrimination. 

The project aimed  to:

• Elicit patient, surrogate and provider perspectives on granular data control  
• Design educational material to inform patients and providers about the consequences of sharing/not sharing data 
• Deploy and pilot test an informed consent management tool that supports granular patient-driven data control
• Understand the ethical, clinical, policy and regulatory implications of implementing granular data control choices

ROOT- Registry of Operations and Tasks 2016-2019

Before and after the Mayo Clinic undergoes an enterprise-wide conversion to a common EHR, the aims of this project were to:

• Capture and document high quality snapshots of EHR workflows 
• Study surgical workflows at Arizona, Florida and Rochester by triangulating outcomes from:
  • Leadership, key personnel and clinical activity interviews
  • Observations, shadowing and video ethnography
  • Process mining recordings of system events, such as "At 9AM on 10/10/17 provider C logs into EHR application A to review data on patient P"

​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.

Despite patients self-management diabetes differently, current education interventions are based on the "one size fits all" approach. 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
• Conduct individualized education interventions to target patient's adherence barriers and evaluate their effectiveness in blood glucose control