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Data Security Survival Skills for 21st Century Evaluators

Handouts for AEA 2013 Skillbulding Workshop 112 (slides and "Data Security Survival Guide"--how to develop a data security plan) #DataSecurity #HowTo

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Focus Search - AEA Abt Data Security Survival Guide Final Oct 16 2013.docx...

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Creating Cross-Agency Longitudinal Datasets for Education Research

Big data is everywhere. As evaluators, often our task is to transform data into information that answers questions and guides better decision-making. However, existing data is often collected for a myriad of purposes, siloed in separate agencies, and protected by different privacy laws. The...

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Focus Search - Creating Cross-Agency Longitudinal Datasets for Education Research Authors Security Linking Cleaning Sarah Frazelle Senior Advisor for Research & Evaluation; Education Northwest Jared Silver Data Architect and Manager; Center for Education Policy Research at Harvard University Havala Hanson Senior Advisor for Research & Evaluation; Education Northwest Information & Resources for DATA SECURITY Although laws vary across states and countries, some consistent best practices in data security include: · Designate a team to coordinate policies and IT infrastructure · Make sure there is a data sharing agreement in place for all student level data that is shared by an education agency. · Only share student level data through a password protected and encrypted sites endorsed by your IT group and approved by legal counsel · Never email files containing student level information · Keep printed reports stored in a secure locked location · Always double check your policies with your legal counsel Web Resources Family Educational Rights and Privacy Act Regulations (FERPA) document The U.S. Department of Education’s Privacy Technical Assistance Center (PTAC) offers up to date guidance and free training modules Guidance from the Data Quality Campaign on FERPA compliance from a policymaker’s view Specific guidance for disclosure avoidance Information & Resources for DATA LINKING Steps for designing your own identity resolution software · Identify what data elements you have to match (SSN, name, address, etc) · Define the Exact and “Fuzzy” matching criteria

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The Importance of Data Governance in Evaluation

A table of topics and definitions, with a list of some challenges, key questions and strategies to be completed by session attendees. #UberTIG #DataGovernance

Data governance handout AEA 2013.docx

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Pencil Versus Keyboard: An Assessment of Alternative Methods for Evaluating Social Services Outcomes

For a number of years, the United Way of Greater Houston (UWGH) has facilitated affinity groups of agencies in the same services field to evaluate common outcomes. Among these affinity groups have been those providing services to victims of domestic and sexual violence (six agencies with about...

Pencil Versus Keyboard_CMedits.pptx

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Eval12 Session 277: Growing a Backbone: Place-based Work and Collective Impact

Abstract: Recent work by the Foundation Strategies Group on “collective impact” has been getting a great deal of attention in philanthropic, government and nonprofit arenas. This panel will present three different evaluations of projects in Grand Rapids, Michigan that are applying the collective...

Growing a Backbone Place based Work and Collective Impact.pptx

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Eval11 Session 920: Using Research Electronic Data Capture (REDCap) for Designing a Data Collection System in the Field

Collecting real-time data securely on a mobile device can pose many challenges, particularly when that data requires HIPAA compliance safeguards. Research Electronic Data Capture (REDCap) is a secure, web-based application designed exclusively to support data capture for research and evaluation....

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Focus Search - • Easily customizable and able to be configured in multiple ways to suit the needs of a given project The Consortium • • 288 active institutional partners from around the globe • Typically, a centralized group at each institution houses REDCap to prevent infrastructure duplication • Serves nearly 23,000 research projects and just under 33,000 end users • Project production has grown exponentially in the past five years How Has Been Used • Prospective Research and Evaluation Studies • Data Collection for Chart Reviews • Multi-Site Data Collection (domestic and international) • Basic Research Studies • Behavioral Research Studies (Survey) • CTSA-wide research studies • (Statin Treatment for Influenza Patients Trial) • CTSA-wide research on research studies (Committee #1 IRB + Contracts) • Quality Improvement • Research Operations Support (tracking databases) • Education Support – Teaching Tool • Project Management • Lab Specimen Tracking • Survey can be used as a surrogate web application • State performance management systems for home visitation Key Considerations for Selecting Key Considerations for Selecting • COST: Need a cost-efficient way to collect and manage research and evaluation data • CAPACITY/STAFFING: Need a system that evaluation staff can use with limited knowledge of data sytems • NEW DATA: Need ability to collect new screening or clinical instruments for outcome measuring • EXISTING DATA: Needed a way to interface with existing information management systems (if they exist) • REPORT GENERATION: Need to export data or run ad-hoc reports that are easily configurable for multiple purposes • DATA SECURITY/CONFIDENTIALITY: Need the data to be secure when collecting, storing or importing; need a HIPAA Compliant server to transfer Protected Health Information (PHI) Key Considerations for Selecting • FIELD USE: Need the ability to collect and transfer screening or program data directly into MIECHV database during a home visit if desired • FUNCTIONALITY: Need to de-identify data as needed, restrict user access to some data, create schedules, be used as a case management system (if needed), track program data • VERSITILITY: Need it to be easy to customize, configure, or change as new program data or screening instruments are introduced Key Considerations for Selecting • TECHNOLOGY: Need to be able to securely interface with technology used by research assessors in their office, in the participants’ homes, or on the road if needed to reduce data entry labor costs Key Considerations When Selecting Internet access through Wi-Fi and 3G capabilities for in the field use Interactive use during face to face interviews Example of a Data System for an Evaluation Project • Adolescent Family Life Generations Project • Rigorous research and evaluation study testing the effectiveness of enhancing a home visiting program for pregnant teens with an educational support group for their parents, mental health services, and social media outreach • Kansas’ Maternal Infant Early Childhood Home Visiting (MIECHV) Program • Creating a Performance Management System to enable state to respond to federal reporting requirements and integrate evaluation and CQI • Working with four home visiting program models in each of three counties • Matching and integrating data from multiple agencies with different management information systems with the state’s child welfare data • Nebraska’s MIECHV Program • Working with one home visiting program across three counties in one agency • Matching and integrating data from one agency’s management information system with the state’s child welfare data How We Use • Generations Project Overview • Testing the effectiveness of enhancing a home visiting program for pregnant teens with an educational support group for their parents, mental health services, and social media outreach. • Kansas Children’s Service League -Healthy Families program in Wyandotte and Shawnee Co, KS • KU Institute for Educational Research and Public Service & School of Social Welfare How We Use Office of Adolescent Pregnancy Programs Generations Project Overview Services for Family In-home mental health assessment & services as needed Services for Teen KCSL Healthy Families Home Visiting Referral to Community Mental Health TREATMENT GROUP CONTROL GROUP KCSL Healthy Families Home Visiting Services for Grandparent Grandparent Education & Support Group Social Media & Support Networking Generations Project Overview Immunizations for Babies Reduced Repeat Teen Pregnancies Educational Attainment for Teens Social Support, Mental & Physical Health, Family Functioning Generations Project Data Map KCSL’s Mental Health Database Teen Parent Both Field Interviews with Teens and Parents of Teen What is the construct or outcome we want to measure?

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Handling Data: From Logic Model to Final Report Handout from SI10

Sessions Description: Collect, analyze, and present data from complex evaluation studies in ways that are feasible for the evaluator and meaningful to the client. Explore lessons learned through over twenty years in evaluation consulting to ask the right questions, collect the right data and...