Applications received after this date will be reviewed by the search committee if the position has not yet been filled.
Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.
Non-Faculty Academic Position
Specialist 60% FTE
Department of Social & Behavioral Sciences
University of California San Francisco
The Department of Social & Behavioral Sciences announces a search for non-faculty positions to be filled by Oct 1, 2018. Appointment will be at the Full Specialist. This position is permanently based in San Francisco, CA.
The Department of Social and Behavioral Sciences (SBS) is one of four academic departments in the School of Nursing at the University of California, San Francisco (UCSF). Department faculty are actively involved in a wide variety of research activities in local, national, and global arenas. Topics are related to the teaching programs and the mission of the department and include tobacco control and medical marijuana policy, health disparities, health workforce studies, gender and HIV/AIDS, biomedicalization, ethical and social issues in genetics, anti-violence, health professions, health demography, and aging and long-term care policies both domestically and globally.
The Department of Social and Behavioral Sciences is home to the “Community Health After Neighborhood Transformation” (CHANT) and “Health Effects After Renovation” “HEAR” projects.
A unique opportunity exists in San Francisco to examine prospectively the socio- structural dimensions and health effects of efforts underway to rebuild four of the largest and most distressed public housing sites in the City. Through a public-private housing initiative known as HOPE SF, traditional public housing “projects” are being transformed into “mixed- income communities,” offering an unprecedented opportunity to assess empirically and longitudinally how structural changes in low-income communities affect health status, health outcomes and social well-being. HOPE SF is a novel strategy of public housing redevelopment because it utilizes a phased development approach that allows for on-site relocation of residents, thereby minimizing displacement of residents out of their home communities. HOPE SF also includes one-to-one replacement of public housing units to maintain the current stock of subsidized housing with the addition of over 5,000 new, affordable and market rate homes. Site plans include features that promote wellness activities and provide linkages to healthcare, education and employment opportunities, and social services—features typically not available in public housing communities. Other features include outdoor spaces, easy access to public transit, street grids that intersect with broader and bordering communities, safe outdoor recreation areas, embedded wellness centers and child care services, retail outlets, and community services on-site. The net effect is a potential for social transformation and community-level change of public housing developments where residents have historically carried a disproportionate burden of health, social and economic inequalities. HOPE SF is a unique natural experiment opportunity to examine the socio-structural dimensions of this housing transition and the impact it has on residents’ lives and community health. The overarching objective of this research is to examine how the transition from distressed housing to mixed-income communities impacts individual and community health. We seek to understand how and in what ways public housing redevelopment affects the health outcomes and social wellbeing of the target sites’ residents. Two specific aims meet this objective: To document the socio-structural conditions of HOPE SF communities through contextual data and in-depth interviews collected before and after the redevelopment and resident moves; and to examine the effects of socio-structural changes on residents’ social life and perceived health and well-being. To investigate changes in the health status of residents before and after redevelopment by analyzing health service utilization, social service, administrative, and public source neighborhood-level data of target and comparison sites.
Housing renovations have not traditionally been considered health interventions, nor have previous housing redevelopment programs focused on health outcomes. There is an established body of literature on housing-health connections, however, it is modest and to the extent that there are direct measures of health, primarily it focuses on mold, allergens, or toxins and their effects on asthma or the neurotoxicity of lead. Less is known about how the effects of housing refurbishments and the provision of amenities and services might affect communities, their social fabric, and their physical and mental health.
This Specialist will play a central role in quantitative research activities for two related projects measuring the health effects of public housing transformation. Specifically, this Specialist will lead the collection, management, analysis, and interpretation of longitudinal electronic health record (EHR) data from two large San Francisco health systems (San Francisco Community Health Network and UCSF) and integrate EHR data with public housing location and neighborhood context measures. The objectives of this research are to quantify the baseline demographic characteristics, healthcare utilization patterns, and health outcomes for patients at select public housing sites and neighborhoods in San Francisco and measure how these factors change over time in association with public housing redevelopment or renovation. The quantitative data collection and analysis will complement in-depth qualitative research activities led by other project leaders at UCSF and SFSU.
% of Total Work Effort - Description of Duties
Data Analysis - 40%
• Compilation and management of EHR data, communications with hospital data managers, and maintain metadata documentation
• Cleaning of EHR data and assessments of data quality.
• Geocode patient addresses and match with study site addresses
• Review research literature and critically evaluate existing methods for EHR health outcome measures and develop new measures and methods as needed to accomplish research aims
• Conduct spatial and statistical analysis of EHR and neighborhood context data
• Create datasets for project collaborators and contribute to data analysis plans and interpretation
• Oversee/mentor consultants and junior collaborators in one or more above tasks
Collaboration - 20%
• Contributes to project related peer-reviewed articles and progress reports.
• Contribute to CHANT and HEAR team meetings
• Presentation of research results for other research groups and/or at scientific conferences
• Doctoral degree in environmental health, public health, epidemiology, environmental science, or related field
• Experience in advanced methods for epidemiological analyses and statistical methods for exposure modeling
• Proficiency in one or more statistical programming language (e.g., R, SAS, Stata)
• Experience with geocoding and geospatial analysis
• At least 3-5 years of experience in epidemiological studies, project management and teaching or training.
• Ability to manage projects, mentoring one or more other data scientists on complex tasks
• Excellent inter-personal and communication skills
• Ability to write clearly and prepare results for publication
• Publications in social, spatial and/or environmental epidemiology
• Experience working with electronic health record data
• Experience integrating and transforming large datasets (>1 million records)
• Experience with longitudinal data analysis
• Experience working with interdisciplinary research teams
UC San Francisco seeks candidates whose experience, teaching, research, or community service has prepared them to contribute to our commitment to diversity and excellence. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status.
Please apply online at https://aprecruit.ucsf.edu/apply/JPF02126.
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