An important aspect of medical care is clear and effective communication, which can be particularly challenging for individuals based on race/ethnicity. Quality of communication is measured systematically in the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey, and analyzed frequently such as in the National Healthcare Disparities Report. Caution is needed to discern differences in communication quality from racial/ethnic differences in perceptions about concepts or expectations about their fulfillment.
To examine assumptions about the degree of commonality across racial/ethnic groups in their perceptions and expectations, and to investigate the validity of conclusions regarding racial/ethnic differences in communication quality.
We used 2007 HCAHPS data from the National CAHPS Benchmarking Database to construct racial/ethnic samples that controlled for other patient characteristics (828 per group). Using multiple-groups confirmatory factor analyses, we tested whether the factor structure and model parameters (ie, factor loadings, intercepts) differed across groups.
We identified support for basic tests of equivalence across 7 racial/ethnic groups in terms of equivalent factor structure and loadings. Even stronger support was found for Communication with Doctors and Nurses. However, potentially important nonequivalence was found for Communication about Medicines, including instances of statistically significant differences between non-Hispanic whites and non-Hispanic blacks, Asians, and Native Hawaiian/other Pacific Islanders.
Our results provide strongest support for racial/ethnic comparisons on Communication with Nurses and Doctors, and reason to caution against comparisons on Communication about Medicines due to significant differences in model parameters across groups; that is, a lack of invariance in the intercept.
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 June 2015.
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#23,298,365
of 34,361,833 outputs
Outputs from Medical care
#3,863
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Outputs of similar age
#190,719
of 306,801 outputs
Outputs of similar age from Medical care
#33
of 74 outputs
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