Kristin Levine, a registered nurse, calls a patient from Bristol Hospital. Connecticut is one of the few states that don't have a broad health information exchange, a singular place where every practitioner involved in a patient's care can access medical records. Connecticut is preparing to launch one this fall. Yehyun Kim /

In Connecticut, over 60,000 people have tested positive for COVID-19 and over 4,500 have died.  The pandemic has disproportionately affected Black and brown communities, both through direct health consequences and disproportionate economic impacts and new cases are on the rise, with Connecticut surpassing its travel advisory threshold.

But we don’t know enough. Even as schools and businesses reopen, we do not have comprehensive, up-to-the-minute information about how COVID-19 is affecting people. As of October 15, 30 percent of race and ethnicity data are missing from reported COVID-19 cases, according to the daily report released by the Department of Public Health.

If we are to truly understand the problem and effectively address the health inequities exacerbated by the pandemic, we need high quality, real-time data.

One solution that could help address this need is the Connecticut Health Information Exchange (Connie)After more than two decades in the making, Connie, an independent, not-for-profit, nongovernmental organization, was established in 2019 through efforts led by the Connecticut Office of Health Strategy and the Department of Social Services.

Health information exchanges (HIE) —organizations that aggregate and share information across multiple health agencies—could provide that real-time information about community health across Connecticut, during this pandemic and future disasters. HIEs can aggregate data across multiple healthcare settings, from hospitals and urgent care centers to pharmacies, laboratories, public health departments, and other health-related organizations. An HIE can ensure we have full information on people as they access care, whether they check into an emergency room, visit a specialist or a clinic, or get lab work.

Currently, there are a variety of health information systems in Connecticut that collect and maintain patient data, generally operated by private physicians, hospitals, or public institutions. For example, across state agencies and community-based organizations, there is wide variation in the collection of race and ethnicity data, as showcased in the recently published Health Equity Data Analytics: Policy Recommendations Report.

These systems, however, are not meeting the enormous data challenge created by the COVID-19 pandemic, nor were they developed with a health equity framework. In creating Connie, Connecticut’s state officials have committed to a foundation of achieving health equity through the HIE. This means ensuring not only a unified system of data exchange, but mandating measures, including legislation, to ensure the uniform collection and regular reporting of accurate information on self-reported race, ethnicity, preferred language, geography to improve examination of racism and other structural causes of health inequities and incorporating other information such as self-reported health-related social needs, such as housing, food, transportation, and community assets that provide critical services to patients with specific needs.

As the HIE develops, additional support is needed to ensure that the data flow benefits Connecticut’s most vulnerable communities. Resources are needed to create the type of technical support that ensures that community members have access to meaningful, high quality data and data analytic support. Creating a governance structure that involves residents in what is collected and how data are used, and even exploring how residents can access, view, or reclaim their own data in ways that are meaningful, is also crucial. The Office of Health Strategy (OHS) is responsible for developing HIE consent policies and regulations and will rely heavily on consumer engagement to inform these policies.

Overall, a more robust HIE data infrastructure could help to remedy our lack of knowledge. In the context of COVID-19, a fully operational HIE, which centralizes health equity data would improve the current lag in and lack of data on Black and brown communities and other marginalized communities through live data updates, allowing for immediate response to needs. We could have real-time knowledge about access to COVID-19 testing across communities and census tracts.  We could implement measures to improve testing in communities that need it by deploying mobile sites, public information campaigns, and other forms of community outreach. This, in turn, can help us better understand where and to whom COVID-19 poses the most risk, and how we can reduce that risk. A robust HIE can help communities address other critical health concerns as well, such as food insecurity, opioids, and housing.

This pandemic has shown us the state needs to accelerate its work to create a full-fledged and operational health information exchange (HIE).  It is more important than ever that we ground any health information system in the concerns of equity. Otherwise, we will never know what is really happening on the ground or in the streets, nor be able to construct policies that truly improve people’s lives in the places where they are most needed.

Summary of race and ethnicity data fields collected from stakeholder outreach. Source: Abraham M, Everette TD, Rizzo T, Sathasivam D, Wang K. Health Equity Data Analytics Policy Recommendations Report: September 2020.

About authors Mark Abraham, Karen Wang, MD; Tekisha Dwan Everette, PhD; Tara Rizzo, MPH; Dashni Sathasivam, MPH; and Marcella Nunez-Smith, MD. The Health Equity Data Analytics (HEDA) team, comprised of Health Equity Solutions, DataHaven, and the Equity Research Innovation Center at Yale School of Medicine, was contracted by the Connecticut Office of Health Strategy (OHS) from 2018 to 2020 to examine how to embed health equity into the data architecture of the new CT health information exchange (Connie).

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