Overview of Services
The Population Health Shared Resource (PHSR) facilitates cancer prevention and control research in the clinic, community, and population settings. These populations are ideal for studies involving clinical and population sciences; addressing diverse communities; requiring access to large samples of patients and/or providers; examining preventive strategies; and investigating the dissemination of proven technologies and interventions. The PHSR allows investigators access to comprehensive computerized patient and provider data, including those available through COMPASS, the University’s integrated health data warehouse, Practice-based Research Networks, and the Colorado Cancer Registry, assists with data management for large administrative data such as SEER-Medicare, and offers support to members developing research proposals within community and academic practice settings. In addition, the PHSR helps investigators with integrating behavioral aims within any basic, clinical, or population science research.
Consult with investigators and provide input on the feasibility of the project including the available sample size and connections to relevant community groups.
Assist investigators with determining appropriate outcome measures and survey methods including economic, psycho-social, behavioral, quality of life, and community-based participatory research
Assist investigators with finding co-investigators within community practice settings and introduce the investigator to the key clinical and administrative staff
Provide preliminary data on available patients or at risk subjects needed for grant preparation
Run exploratory TriNetX queries to generate potential UC Health patient numbers
Assist with the protocol development to best take advantage of the planned study setting
Consultation for behavioral and population based IRB issues
Expertise in developing and maintaining community partnerships and obtaining letters of support
DATABASE RESEARCH ACTIVITIES
PHSR staff are familiar with commonly used datasets (e.g., the SEER research database, SEER-Medicare, Colorado Cancer Registry, COMPASS, ONCORE, ORIEN) along with many others. They work with investigators to:
- Develop inclusion and exclusion criteria
- Determine definitions for cohort initiation
- Construct and validate analytic variables
- Perform database linkages for primary and secondary data including bio-specimen data with other data sources
- Develop database queries
- Provide analytical data base support including ascertainment, extraction, and storage of data
- Maintain data use agreements
- Provide ongoing scientific input, including development or refinement of study protocols, interpretation of data, and manuscript preparation
PHSR staff can assist with geospatial analyses or incorporating geospatial measures into research questions. Services include:
- Geospatial analysis and mapping
- Linkage of geospatial datasets
- Addition of area-based measures to datasets
POPULATION-BASED FIELD RESEARCH
PHSR staff and faculty advisors have extensive experience and support tools to:
- Identify and/or develop questionnaires to meet study requirements
- Develop cohort selection criteria
- Develop recruitment, retention, intervention, and education materials
- Develop technology platforms (e-health) and tools to support recruitment, retention, and data collection
- Website/mobile/app development and hosting for labs, cores, and research projects
- Develop novel approaches to dissemination of research findings through Community Advisory Committee members, University of Colorado Communications Office, and other community-based organizations such as the Colorado Cancer Coalition.
HEALTH DISPARITIES RESEARCH
We work with researchers, clinicians and communities to reduce inequities in the burden of cancer. Services include:
- Assist with minority recruitment and retention
- Outreach, education, formative research and program evaluation activities with underserved communities
- Synthesis of cancer outcomes in underserved populations within the catchment area
- Evaluate the relevance of cancer research studies to the catchment area
- Engage with community partners in improving access, screening and cancer care for diverse populations
- Promote clinical trial participation among underserved patients (e.g., Hispanic Clinical Trial Navigator)
- Optimize prevention and other interventions for dissemination in the catchment area
MEET OUR PEOPLE
Megan Eguchi, MPH
Megan received her M.P.H. in Epidemiology at Emory University and studied Microbiology as an undergraduate at the University of California, San Diego. She has experience working with administrative claims and cancer registry data, and is familiar with SAS, Stata, and ArcGIS
Amy Mellies, MPH
Amy received her M.P.H. in Epidemiology at the University of Georgia and studied Psychology and Genetic Counseling at Washington State University. She has experience working with cancer registry data as well as data from population-based health surveys, including the Behavioral Risk Factor Surveillance System and the Youth Risk Behavior Surveillance System. Amy is familiar with SAS, SUDAAN, and ArcGIS.
Elisabeth Meyer, MPH
Elisabeth received her MPH in Epidemiology from the Colorado School of Public Health and her BA in Psychology and Spanish from Chapman University. She primarily works with claims and cancer registry data, and also has experience in population-based survey analysis and data visualization, using software including SAS, Stata, and Tableau.
Sarah graduated from the University of Illinois with her M.S. in Kinesiology with an emphasis in Exercise Psychology and behavior change. Her research experience includes clinical trials, RCTs, and quality improvement, ranging from lifestyle behavior based interventions to implementing evidence-based practice into integrated care settings.
Sruthi Yekkaluri, MHI
Sruthi received her masters in Health Informatics from Indiana University(IUPUI) and studied doctor of pharmacy as an undergrad at JNTU, India. She has experience working with the clinical data, research data and familiar with SAS, SQL, Tableau and R.