Methods Core Seminars

Upcoming seminars

Title: Better Data Capture Solutions with Medrio

Presenter: Michael Schembri
UCSF Department of Obstetrics, Gynecology & Reproductive Sciences
Women’s Health Clinical Research Center  

Date and Time:  Tuesday, Jan 28, 2020; 11 am - 12:30 pm

Location: AmFAR Conference room, MH-3700 , 550 16th Street (at 4th Street), 3rd Floor, Mission Bay, SF 94158

Abstract:   Data capture solutions can seem to come in two flavors—free or exorbitantly expensive.  What is really needed is a middle solution, one with the sophistication for modern studies, without the bloat of large enterprise products.

Medrio is a cloud based electronic data capture platform with advanced solutions for clinical trials and registry studies.  With flexible form layout, a relational data structure, built in data query and reporting systems, and native data extracts (SAS, STATA), Medrio’s features streamline workflows for coordinators, data managers, and other team members.  And its mobile technology tools facilitate an eSource approach. Come learn about this valuable technology and UCSF’s arrangement with this local company to access it.

Short Bio:  Mr. Schembri is  the data systems analyst for the Women’s Health Clinical Research Center and has over 25 years experience programming in health care research.  He has designed and developed databases for longitudinal studies, clinical trials, study and participant management and bio specimen tracking.  He has worked on statewide and nationwide registry studies including the development of the methodology for the California State Hospital Outcomes Project.  His analysis experience includes linear mixed models, missing imputation, cost effectiveness and utility, and bootstraps, with a list of publications in health policy research, longitudinal studies, cost effectiveness, as well as clinical trials.  

RSVP to Estie Hudes (also let me know if you need building security access)

Materials from past seminars



  • October 8, 2019 - Lila A. Sheira, MPH; UCSF: "Using REDCap Mobile: Practical suggestions for remote data collection"
  • September 24, 2019 - John Sauceda, PhD, MSc; UCSF: "Intro to the Multiphase Optimization Strategy (MOST) Framework for Intervention Science"
  • May 21, 2019 - Maya Petersen, MD, PhD;UC Berkeley: "Targeted Maximum Likelihood Estimation, integrating machine-learning, to evaluate the effects of longitudinal interventions including dynamic regimes"
  • May 7, 2019 - Julia Adler-Milstein, PhD; UCSF: "Exploring UCSF’s Electronic Health Record Data:Turning Digital Fumes into a Breath of Fresh Air"
  • April 30, 2019 - Lilian Brown, MD, PhD; UCSF: "Social network analysis and engagement in care among HIV-infected youth in East Africa"
  • April 23, 2019 - Michael Duke, PhD; UC Berkeley: "Considerations around analyzing, writing up and publishing mixed methods research"
  • February 7, 2019 - Colin Welsh, MD, MA; Vanderbilt U: "Machine Learning to Catalyze Mental Health: From suicide prediction to treatment resistance and large scale phenotyping"
  • October 23, 2018 - Steve Gregorich, UCSF: "Controversies and Unresolved Issues in the Design of Randomized Controlled Trials Testing Clinical/Behavioral Interventions"