Building Data Capacity for Patient-Centered Outcomes Research Interim Report 1 - Looking Ahead at Data Needs (2021) / Chapter Skim
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2 Health Disparities Data Needs
2 Health Disparities Data Needs
Pages 19-28
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From page 19... ...
• What data capacity challenges is the U.S. Department of Health and Human Services (HHS)
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As an example of how data silos hinder the ability to answer policy questions, Joynt Maddox discussed efforts to answer the question of how FIGURE 2-1 Example of data available on social determinants of health. NOTES: EMR = electronic medical records; OT = occupational therapy; PT = physical therapy; SDOH = social determinants of health.
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From page 21... ...
The ideas shared by Joynt Maddox for improving the data available in this area were to (1) include hospital and state identifiers in national datasets, such as the National Inpatient Sample, and other related datasets from the Healthcare Cost and Utilization Project; (2)
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She discussed recent work she conducted with support from the Patient Centered Outcome Research Institute (PCORI) to identify research priorities for advancing equitable health care for individuals with disabilities.
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As an example, the sexual orientation item BOX 2-3 Disability Questions for Potential Inclusion in Electronic Health Records 1. Are you deaf or do you have serious difficulty hearing?
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Lunn argued that current clinical approaches, such as electronic health records systems and data models, do not allow patients to comprehensively report their sexual orientation and gender identity. Not using people's stated identity (e.g., grouping or administratively classifying them instead)
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Another challenge is that many studies on American Indians draw on data available from the Indian Health Service, but only about half of this population receives health care through that agency. The American Indian population that is left out of research that relies on that agency's data is heavily skewed toward an urban population.
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Concerning language, Sequist highlighted the need for accurate and reliable data, noting that lack of standardization in the way language information is collected has been a challenge both for research and for improving health care. For example, he underscored the need to differentiate among someone's preferred language, their primary language, the languages in which they are fluent, and the languages in which they have achieved health literacy.
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From page 27... ...
A fundamental reason for the data limitations that make it difficult to answer questions important for PCOR is that most of the data available for research are not primarily collected for research purposes. While research questions require a relational or integrative perspective, the data collected tend to be transactional, that is, collected for payment or treatment purposes, and therefore do not vary according to most personal characteristics.
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From page 28... ...
The workshop underscored the magnitude of the data gaps in the area of health disparities. Improving the data available for understanding and addressing disparities would require an effort concentrated on this goal.
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