RWJF loves your data

We love your data, and we want to help encourage its use developing programs and policies that improve population health, well-being, and equity.

by Oktawia Wójcik, PhD, and Margaret Tait, Robert Wood Johnson Foundation

At the Robert Wood Johnson Foundation, we’re working to build the knowledge base of what works for health.  As the largest philanthropic organization in the U.S. focused solely on health, we think a lot about data and how it can be used to identify gaps, measure progress, and inspire action. We’re interested in using data, big and small, to tackle issues of health equity, health system integration, and community transformation. And when we think about data that is related to health, we are thinking about more than just information collected in medical records, we are thinking about social determinants of health data like education, transportation, and criminal justice.

We’ve spent the last two years learning ways to increase openness and transparency in research, with the goal of making the research that results from our investments, and the investments of others, more accessible to those who need it.  Doing so ensures that a wide net of health services researchers are aware of the economic analyses of population-based payment methods and that city planners have the research showing life expectancy variation by location.

Openness is just one part of the equation, though; and funders have to be intentional to ensure the research we support is of good quality, rigorous and representative.  To that end, we see the role that funders can play in data stewardship as one that is twofold: to encourage and challenge. As we develop programs and consider key research studies, we want to encourage the use of data, both quantitative and qualitative, to inform all aspects of an approach and we want researchers to use data at various levels, individual and population. We recognize that there are challenges associated in working with individual level data, such as privacy and confidentiality that need special consideration. As funders, we are keenly aware of and intentional in supporting data of high integrity and quality, as well as methods for the analysis of this data that are shared with others as a standard practice.

In collaboration with the Centers for Disease Control and Prevention (CDC) and CDC Foundation, we support the 500 Cities Project.  This project uses small area estimation methods to provide data on 30 health indicators at the census tract level in 497 of the largest U.S. cities, as well as a city each in West Virginia, Vermont, and Wyoming, covering all 50 states.  This is the first time this amount of data had been available at a city and census tract level, and we hope it is just the beginning. Our vision is that this data will help researchers, practitioners, and policy makers identify issues and encourage collaboration on solutions that will promote more opportunities for better health.

The Foundation has also long supported the Interuniversity Consortium for Political and Social Research (ICPSR) and requires that publicly available datasets that result from our grant making are deposited here in the Health and Medical Care Archive.  ISCPSR has been an important part of RWJF’s work for decades, but recently we’ve been thinking about additional steps we could take to promote openness in the research process.  And, we’d be remiss if we didn’t take the opportunity to ask fellow data lovers: what role do you see for Foundations in data stewardship?

 

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2 thoughts on “RWJF loves your data

  1. I appreciate how the Foundation requires researchers to deposit data sets in a public archive, mirroring what NIH and now other HHS sub-agencies are doing. I would love to see you and other funders create fellowships to encourage data scientists to look at public health data, to seed the field and attract people who may not otherwise focus on health.

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  2. Data Keepers/ Data Concierge – make it easier for outsiders to use data, document tables and fields exquisitely. Investigators rarely document quite as well as they need to for others to understand the data and how it was collected, what the flaws/warts in data collection were. Provide web resources for basic R/SAS/Stata data read-in, data FAQs, warnings about fields w/definitions that are not obvious from field names. De-weaponize the Data Hoarder vs. Data Parasite relationship by being a calm friendly intermediary

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