Open AccessSupporting A Developmental Approach for Shared Data Infrastructure
Author(s) -
Aaron Nelson,
Emily Berkowitz
Publication year - 2020
Publication title -
international journal of population data science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.602
H-Index - 7
ISSN - 2399-4908
DOI - 10.23889/ijpds.v5i5.1638
Subject(s) - data sharing , process (computing) , data governance , general partnership , process management , computer science , knowledge management , data quality , data science , corporate governance , data access , presentation (obstetrics) , session (web analytics) , business , engineering , world wide web , operations management , medicine , metric (unit) , alternative medicine , finance , pathology , radiology , programming language , operating system
BackgroundPublic agencies hold important, yet largely unused, administrative data on the families and communities they serve. Integrated Data Systems (IDS) provide the governance process, legal framework, technology, and human capacity to connect these families and communities across data siloes. By securely linking administrative data across siloes, IDS are able to support data-informed decision making.
IntroductionFor 10+ years, AISP has helped jurisdictions through the developmental process of building IDS. We operate a network of 22 U.S. states and counties with fully-functioning Integrated Data Systems, and provide technical assistance to 18 jurisdictions at various stages of IDS development.
Objectives and ApproachThis session presents the outcomes of an independent evaluation of our Learning Community initiative (2019) and presents a new developmental framework that outlines key dimensions of quality and readiness for IDS building and implementation.
ResultsAs of 2020, 20 sites have received formal 18-month cohort based technical assistance. This presentation will discuss site-based approaches to facilitate data sharing, including common challenges and solutions, and progress to date, including findings of an independent evaluation (2019). We will also present a framework developed based on the deep knowledge developed through technical assistance efforts, and findings from a national survey of data integration efforts conducted in 2020.
The framework uses purpose, partnership structure, technical architecture, and organizational model—with respect to the strengths and challenges of each—to categorize and synthesize data integration efforts for social policy and program improvement. The developmental approach to our work emphasizes that we seek to understand methods for sustainability in diverse ways.
Conclusion / ImplicationsWhile there is broad agreement in the value of integrating data across domains, developing the capacity and skills necessary to link administrative data for policy evaluation and research remains an elusive goal. Initial results indicate that an individualized yet collaborative technical assistance approach is successful in developing data integration capacity.