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This dataset contains measures of the number and density of health care services per United States Census Tract or ZIP Code Tabulation Area (ZCTA) from 1990 through 2022. The dataset includes four separate files for four different geographic areas (GIS shapefiles from the United States Census Bureau).

Many people have health problems that affect how well they can do normal activities, either for a short time or for their lifetime. These problems may be present from birth or result from illness, injury, or aging. Rehabilitation, or rehab, can help patients regain the ability to do normal activities. Rehab providers include doctors, nurses, psychologists, and physical, occupational, speech, or language therapists.

Rehab treatments often lack a common definition. Rehab providers often name treatments by the type of professional who delivers them or the problem they treat, rather than by the content of the treatment. Also, treatments can vary across rehab providers. Using a standard way to define rehab treatments may help researchers compare these treatments.

In this study, the research team created and tested a manual to help rehab providers use standard ways to define rehab treatments.

Part C of the Individuals with Disabilities Education Act authorizes states, with the incentive of federal financial support, to create Early Intervention (EI) systems, which is a primary source of rehabilitation (e.g., physical, occupational, and speech therapy) services for infants and toddlers with, or at risk for, developmental delays. Having worked with two EI Colorado (EI-CO) programs that employed electronic documentation, the researchers sought to leverage their electronic administrative data in order to examine social disparities in EI service use, including specific rehabilitation services.

The dataset for this data archiving project was generated in collaboration with a large, urban EI program in Colorado, a community partner for an NIH/NCMRR R03 study. This academic-community research partnership provided researchers with access to an urban EI program's electronic administrative database; The researchers' goal was to make these data available for further EI research. Therefore, a database was created and a number of variables were derived that could be of importance to EI stakeholders when conducting clinical queries for quality improvement. Examples of derived variables include EI service use intensity (i.e., hours per month) for all EI services, as well as discipline-specific (e.g., physical or occupational therapy) service use. The researchers obtained permission from the partnering EI agency to archive their EI program data through this project.

The dataset included as part of this collection includes 2045 cases for 44 variables; demographic variables include: race, ethnicity, language, sex, age, and developmental condition type.