Skip to main content

Currently Skimming:

3 Challenges in Using Available Data for Small Population Health Research
Pages 19-30

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.


From page 19...
... Chris Fowler (Pennsylvania State University) focused on using geospatial methods with demographic data to identify populations, while consultant Ellen Cromley discussed using these methods with other health and environmental data for the same purpose.
From page 20...
... She acknowledged the federal statistical system faces broad and often conflicting challenges: funding constraints versus a need for more granular data, the push for efficiency amid declining survey response rates, and a desire to obtain finer data about various populations while carefully considering privacy issues and questions about trust and data usage. She said these forces should serve as drivers to search for complementary data sources like EHRs and other electronic health data, which may require partnering with the private organizations who maintain these records.
From page 21...
... Devers cited several examples in which access to large health insurers or integrated delivery systems in areas with highly diverse populations can provide information on and enable researchers to identify hard-to-reach groups, using data such as language spoken and translation services provided. Devers and her colleagues have identified four illustrative populations that put these issues into context: Asian American subpopulations; lesbian, gay, bisexual, and transgender (LGBT)
From page 22...
... Both Vanderbilt and University of California Davis Health Systems are also now collecting information about patient sexual orientation through EHR patient portals as well on a voluntary basis. Additionally, the more advanced certified EHRs are now required to add gender identity and sexual orientation data, which will further aid research.
From page 23...
... She also noted the need for progress on the legal framework and other policy issues. USING GEOSPATIAL METHODS WITH DEMOGRAPHIC DATA TO IDENTIFY POPULATIONS Chris Fowler focused on the possibilities and problems with using small geographic areas to represent context for studying small populations.
From page 24...
... One tract in his study area contained apartments over storefronts occupied primarily by immigrants and refugees, single-family homes occupied by aging black and Italian populations, and waterfront homes worth millions of dollars. He said that while tract data may be efficient for census enumeration, just as zip code delineation makes postal delivery more efficient, neither may be a useful administrative unit for measurement in other contexts.
From page 25...
... When segregation can be seen at large scales, Fowler noted it is correctly understood as the result of long-standing historical racism, discrimination, and other negative structural factors. But at very small scales, those same observations of people of similar race living together may be associated with social solidarity, political efficacy, social networks, and social capital that bring significant benefits.
From page 26...
... In that sense, any random sample from such a population is implicitly a spatial sample. She added that it is possible to advance health research by making the spatial basis of evidence explicit using geospatial methods; in other words, create the map first, understand the geographical distribution of the sample, and consider the geographical distribution of the population of interest.
From page 27...
... She and her colleagues used data from MassGIS, a statewide, one-stop site for interactive maps and geospatial data for Massachusetts, to look at ­ long-term care facilities. To look more closely at capacity, they measured the distance from specific points to every nursing home using Gaussian spatial weighting to obtain a geographically weighted mean.
From page 28...
... Cromley called for an increase in common repositories for spatial data, where people can access data on their own and develop interventions specific to their communities. She cited the Malaria Atlas Project14 as a great model for how to build spatial data commons.
From page 29...
... referred to 2017 recommendations by the National Cancer Institute (NCI) , American Cancer Society, and other organizations around cancer health disparities research in five areas.
From page 30...
... said she has seen how zip code boundaries can cross over neighborhood boundaries ­ and asked at what level research should start if the primary question is not spatially oriented. She also asked how to mitigate the risk of disclosing personally identifiable information in secondary analyses.


This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More information on Chapter Skim is available.