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While a range of health and health care entities collect data, the data do not flow among these entities in a cohesive or standardized way.Entities within the health care system face challenges when collecting race, ethnicity, and language data from patients, enrollees, members, and respondents.Explicitly expressing the rationale for the data collection and training staff, organizational leadership, and the public to appreciate the need to use valid collection mechanisms may improve the situation.Nevertheless, some entities face health information technology (Health IT) constraints and internal resistance.

It should be noted that a substantial fraction of the U. population does not have a regular relationship with a provider who integrates their care (i.e., a medical home) (Beal et al., 2007).

The flow of data illustrated in Figure 5-1 does not even fully reflect the complexity of the relationships involved or the disparate data requests within the health care system.

Currently, fragmentation of data flow occurs because of silos of data collection (NRC, 2009).

Health care involves a diverse set of public and private data collection systems, including health surveys, administrative enrollment and billing records, and medical records, used by various entities, including hospitals, CHCs, physicians, and health plans.

Data on race, ethnicity, and language are collected, to some extent, by all these entities, suggesting the potential of each to contribute information on patients or enrollees.

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