The Health AI team joins deep clinical and data science expertise with broad knowledge of health informatics to address UCSF Health’s top priorities. 

Leveraging our extensive knowledge of EHR data infrastructure and clinical workflows, we use data science, visualization, and machine learning to improve care delivery and outcomes.​ To do this, we:​

  • Collaboratively identify opportunities for improvement with clinical and operational leaders​
  • Take a data-driven approach to rapidly prototype tools ​
  • Implement validated and effective solutions both within and outside of the electronic heatlh record

Our group's expertise spans data science, data visualization, machine learning, process improvement, nursing informatics, and medical informatics. Our tools include Microsoft SQL Server, PostgreSQL, Python, R, and Tableau for data analysis and modeling and GitHub, Trello, Jenkins, and Slack for DevOps and project management. 

Read about our team:  "How UCSF’s data science team took on COVID"


Project Highlights:

Data Science, Visualization & Machine Learning

  • COVID-19 data mart, analytics, and visualizations to support UCSF COVID-19 response and recovery
  • Analytics and predictive modeling for enterprise-wide delirium prevention and treatment program
  • Predictive modeling to enable targeted outreach and interventions that reduce clinic no-shows
  • Standardization and evaluation of health equity metrics 
  • Analysis of high-frequency decision-support alerts, with improvements to increase their effectiveness
  • Complex process flow analysis to identify barriers to discharge and provide analytics solutions to improve patient throughput and length-of-stay




Process Improvement 

  • Standardize opioid metrics for the enterprise to facilitate measurement of UCSF Health's impact on the opioid epidemic
  • Use data and analytics to automate manual compliance audits of high-risk medication administration
  • Leverage EHR data and processes to display real-time status of impending discharges and enable day-of-discharge order prioritization

Clinical Project Consultation & Development

  • Translate clinical data requirements into analytic solutions that enable clinicians to improve patient care
  • Translate and align visions of clinical content improvement from diverse stakeholders into usable tools and effective processes in the electronic health record
  • Gather and prioritize requirements for real-time dashboards in the outpatient setting

See more about our recent work: 

Artificial Intelligence in the Health System: Governance and Infrastructure for Safe Deployment Equitable, Targeted Interventions to Decrease No-Shows: An Analytic Approach Preventing Residency Work Hour Violations: A Novel Use of EHR Data Extracting Actionable Insights from External Rankings dashboards.ucsf:
The Enterprise Dashboard Destination
We have developed infrastructure (HIPAC) and a governance process to enable safe deployment of artificial intelligence (AI) in the health system.  We analyzed disparities in existing Apex tools for reducing no-shows in outpatient appointments. We built analytic tools to address those disparities and to support equitable and targeted interventions for reducing no-shows. We built a tool to automatically measure and help prevent work hour violations. The Internal Medicine residency program reduced their inpatient work-hour violation rate by 50% by implementing interventions centered around daily use of this tool. We designed and deployed analytic tools to identify where strategic improvements will have the most meaningful impact. We created a one-stop shop for unrestricted, secure enterprise-level dashboards for the entire UCSF community. 





Sara Murray, MD, MAS, Vice President, Chief Health AI Officer for UCSF Health; Associate Chief Medical Information Officer, Inpatient Care and Data Science; Associate Professor, Hospital Medicine

Rhiannon Croci, BSN RN-BC, Clinical Informatics Specialist

Joanne Yim, PhD, Data Scientist

Hossein Soleimani, PhD, Sr. Data Scientist

Orianna DeMasi, PhD, Data Scientist

Alireza Ebrahimvandi, PhD, Data Scientist

Mounika Guntu, PharmD, MSHI, Data Scientist

Lu Chen, MS, Data Scientist

Yasaswi Avula, MS, Software Engineer

Robert Schechtman, PhD, AI Oversight Committee Manager