Data is driving many of the federal government’s initiatives around equity, including health care. The Centers for Medicare and Medicaid Services, for example, is working to identify gaps in care and develop interventions to address them by focusing on stronger data collection and intersectional analyses for populations defined by race, ethnicity, language, geography and disability.
In the past, the government’s approach has been limited to simply providing funding to a community, which is not sustainable. Instead, agencies should understand social drivers of health equity, which include factors like education, economics, mental health, environmental safety and food access. By collecting and analyzing data regarding the social drivers of health equity, agencies can lay a foundation allowing for the best decisions about providing effective health care to vulnerable communities…
Historically, data management has influenced policy. Agencies viewed data about a region or community, and then made a decision regarding the distribution of resources to inform policy. But the current administration flipped that script; choosing health equity as a policy, and letting it inform data management.
The first step was a discussion on how to achieve equity. The second step is improving data collection and standardization, which is why agencies need to evaluate their focus around health equity: What specifically are they trying to address or accomplish? They must evaluate their current health equity and outcomes data, and determine if they have the right information. If not, they should examine their data collection processes to get to that point. Only then will they be able to determine if their existing policies adequately address health disparities… Read the full article here.
