Project Overview

About OCID

The Oregon Child Integrated Dataset (OCID) is a nonpartisan data-driven project to support policymakers and community leaders as they work to improve outcomes for children and families in Oregon. Created in 2019, OCID contains linked, cross-agency and cross-program information for children born in Oregon and their birth parents beginning in 2001. Additionally, the dataset includes youth who receive services from a range of programs and services regardless of their place of birth. The OCID dataset allows for exploration of the trajectories of children who access state services throughout their development and enables awareness of historical and present patterns that would otherwise be isolated in siloed data for individual programs and services.

OCID is a resource unique to Oregon; no other state is known to have such a robust, comprehensive integrated dataset. With the Oregon-specific and timely data-driven evidence that OCID generates, policymakers will be able to more effectively prioritize scarce resources and efficiently focus on the most meaningful public policy changes.

Funding and Management

The Oregon Legislature appropriated $2 million to support the OCID project in the 2023-2025 biennium.

The Center for Evidence-based Policy (Center) at Oregon Health and Science University (OHSU) leads OCID, providing leadership, management, data analytics, and quality assurance. The Center helps federal, state, and local policymakers shape better decisions by providing them with objective, rigorously analyzed information.

Areas of Development

OCID strives to actively learn and improve our methods to better provide products that are timely, relevant, and actionable for diverse audiences. With our continuous improvement approach, we are currently focusing development in 4 different areas:

  • Strengthening the relationship between OCID and state-level policymaking, with an emphasis on developing OCID products that are timely, responsive, actionable, and represent data and perspectives from across Oregon.
  • Actively testing mechanisms for engaging community perspectives in the work of OCID and build an understanding of how data-to-policy efforts such as OCID can effectively engage and reflect community voice.
  • Developi new approaches to apply cross-program data to better understand potential patterns, interactions, and disparities for children and families served with public resources.
  • Ensuring the continuation and enhancing the breadth of OCID by adding new program and service data in revised and renewed data use agreements.

Project History

Since 2009, the Center for Evidence-based Policy (Center) has been working to develop an integrated and longitudinal child dataset to assist Oregon policymakers in making data-driven decisions to improve the well-being of children in the state. In 2013-2014, the Center received a state appropriation to test the concept of integrated data by examining Oregon foster care entry and exit, incidences of child maltreatment, and associated risk factors and characteristics using a similar integrated set of data.

This work helped to prove the capabilities of such an effort, and in 2019, with the support of former Governor Kate Brown, the Oregon legislature appropriated $2 million for the 2019-2021 biennium, requiring $1 million in matching contributions from private sector philanthropies. The following 9 philanthropic funders provided matching funds to build a more robust dataset:

  • Ford Family Foundation
  • Health Share of Oregon
  • James F. and  Marion L. Miller Foundation
  • Kaiser Permanente
  • Lora and Martin Kelley Family Foundation
  • Oregon Community Foundation
  • Oregon Hospital Research and Education Foundation
  • PacificSource Foundation for Health Improvement
  • WRG Foundation

The project received similar state appropriations for the 2021-2023 and 2023-2025 biennia.

OHSU’s Center for Health Systems Effectiveness (CHSE) was a close analytic partner in the first biennium of OCID development providing analytic support, statistical modeling, and management of the research dataset.