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 process. For instance, mobile apps for in-home disease management control, and tablet-based electronic systems to educate patients on informed consent processes. 

Research Projects

Blockchain-based system for inventory and traceability with application in medical device supply chain management (AZ Blockchain applied Research Center) 2020-2021

The project uses permissioned blockchain (bitcoin) technology in order to create distributed medical device registries with the goals of:

• Improving patient safety, cyber security and response times in supply chain
• Enable digital integration of medical device records across the participating supply chain companies
• Test feasibility of effective device tracking and remote inventory management

My Data Choices, Evaluation of Effective Consent Strategies for Patients with Behavioral Health Conditions (R01 MH108992) 2016-2021

The integration of 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 aims to:

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

• Capture and document high quality snap shots of EHR workflows 
• Study surgical workflows at Arizona, Florida and Rochester by triangulating outcomes from:
  • Leadership, key personnel and clinical activity interviews
  • Observatoins, 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 aims 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 on blood glucose control