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The Veterans Affairs (VA) Center for Evaluation and Implementation Resources (CEIR) is a QUERI resource center launched in 2017 as part of an integrated effort to enable the rapid translation of research evidence into routine VA clinical practice. CEIR provides time-sensitive consultation and support to VA operational leaders on evaluation and implementation methods to enable the scale-up and spread of policies, evidence-based practices, and technologies aligned with key VA priorities. CEIR strives to be the VA’s centralized resource for implementation science, quality improvement, and program evaluation. CEIR services are guided by three overarching goals which are designed to increase: 1) use of program evaluation best practices in everyday VHA care settings; 2) application of implementation science best practices to accelerate clinical innovation; 3) access to information, tools, and training related to implementation science and program evaluation. CEIR also supports the activities of the Implementation Research Group (IRG). The IRG is a national learning collaborative of more than 350 VA and non-VA implementation scientists. IRG activities include monthly cyber seminars, community of practice calls, and five specialty working groups related to different implementation approaches and strategies.
 
The incumbent serves as a Research Health Science Specialist for CEIR with primary responsibilities as a data analyst. Major duties include, but are not limited to:
 
  • Undertaking assigned statistical analysis tasks in support of program evaluation plans related to the scale-up and spread of evidence-based practices into routine VA clinical practice which may include: variable and measure development, designing and conducting appropriate statistical analysis, attending study meetings, assisting in administrative or data editing tasks.
  • Extracting and building analytic datasets using large administrative databases from multiple sources across a national healthcare system, including relational databases.
  • Identifying VHA administrative (e.g., Corporate Data Warehouse) and non-VA data sources to support of program evaluation plans including identification of resources, identification of relevant data elements, initiating contact with technical liaisons, and ensuring secure data transfers.
  • Using statistical (e.g., SAS, R, SPSS, STATA) and database (e.g., MS Access, SQL) programs to write code for processing data, as well as, constructing and managing datasets and databases relevant to program evaluation plans.
  • Developing and maintaining documentation for evaluation databases (e.g. measures, sources, construction, programs, coding, project data management steps, and analysis approach).
  • Creating and implementing statistical analysis plans as part of a team.
  • Assisting in the collection and processing of primary data (e.g., online surveys and interviews). Identifies problems with missing data and takes corrective action.
  • Assisting with the collection and analysis of qualitative data generated through stakeholder interviews and observations of VA care settings.
  • Performing checks on study data to identify potential problems with participant recruitment, missing data, or data quality, through use of frequencies, listings, summaries, and calculating meaningful data metrics.
  • Conducting descriptive, univariate, and multivariate statistical data analyses, including multivariate regression analyses using ordinary least squares, logistic, and survival models.
  • Reviewing analytical results for accuracy and completeness.
  • Organizing and summarizing results and displaying them using tabular or graphic representation, dashboards, as well as, narrative description (e.g., reports, data dictionaries, FAQs).
  • Proofreading and editing drafts of data analysis materials (e.g., statistical reports, manuscripts) and making recommendations to senior staff regarding clarity, organization, and layout.
  • Contributing to working papers, reports, publications, proposals, presentations.
  • Conducting literature searches, abstracts articles, preparing summaries and critiques of literature.
  • Providing timely, responsive verbal and/or written information to customers. Customers include VA Central Office executives and managers; HSR&D/QUERI centers and programs; VA national offices, centers and programs; Veterans Integrated Service Networks (VISN) directors and leads; operational and VA research scientists; co-workers. Listening effectively to identify customers; questions, concerns, and situations and work to address them. Appropriately refer questions/issues not within the employee’s control/responsibility.
  • Assisting other analysts with development and review of SAS, R, and SPSS programs or database queries.
  • Supervising research assistants in basic statistical analysis and data management.
  • Keeping abreast of new developments in data management and statistical software and programming to be able to apply the most current techniques to new projects.
  • Performing other duties as assigned.

This position requires the data analyst be highly proficient at using data processing languages such as SAS or SQL. The data analyst must have knowledge and experience with management and analysis of complex data used in a variety of projects. Additional knowledge required for this position include the ability to: assist with design of data collection instruments and data quality procedures; assist with resolving data collection problems; design and manage databases and information systems; compile results and interpret findings; maintain accurate record-keeping systems and systems for monitoring progress; establish priorities and coordinate multiple tasks; work independently; communicate technical information in clear and concise professional reports, memos, and correspondence; use Microsoft Office programs to create forms, spreadsheets, tracking databases, graphs, charts, tables, and presentations.

Previous experience working with diverse interdisciplinary teams in health services or health-related environment is key. Familiarity with qualitative methods and analysis is preferred.