ORCID

Zachary Bridgewater: 0000-0002-6830-0603

Mary Rachel Keville: 0009-0004-4709-8057

Gilly Cantor: 0000-0001-8890-9259

Document Type

Poster

Date

4-9-2026

Keywords

Coordinated care, Data model, Data standard, Measurement, Interoperability, Data commons

Campus Community

D'Aniello Institute for Veterans and Military Families

Language

English

Funder(s)

Walmart Foundation, Mother Cabrini Health Foundation.

Acknowledgements

This work was funded in part by the Walmart Foundation and the Mother Cabrini Health Foundation.

Disciplines

Military and Veterans Studies | Public Affairs, Public Policy and Public Administration | Social and Behavioral Sciences

Description/Abstract

Coordinated care is a service delivery paradigm that connects health and human service organizations via a shared referral platform managed by care navigators (i.e., coordinators). Referral technologies have proliferated to support this work, but the absence of data collection standards has produced a technology environment where platforms compete on not only their designs and features but on their underlying data models too. Understandably, these distinct data models arise from varying funder and customer pressures. The result, however, is a fragmented data landscape where users and creators of different platforms have different views of the issues faced by communities.

To address this problem, IVMF developed a preliminary data standard (i.e., model) that aims to address the needs of practitioners while offering value to scholars and funders. We built this model using feedback from a small set of interviews with coordinated care stakeholders and internal research team members. Our proposed standard contains five objects relevant to coordinated care: clients, requests, programs, organizations, and networks, each with their own data attributes and permissible values.

We then implemented the standard in IVMF's prototype data commons to test whether it could successfully join and harmonize datasets from different technology vendors. We loaded a large legacy dataset from one vendor, and the other contributor provided monthly uploads over 10 months. The monthly uploads tested our data audit process and the flexibility of our standard to vendors' evolving data models. Except for some interface issues, the standard successfully harmonized both datasets for use in a dashboard that combined the two datasets. We believe creating such a standard paves the road for further interoperability work and joint analyses beneficial to military-connected populations.

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